The Pi-Rate Ratings

January 15, 2019

Advanced Basketball Statistics–Fun Stuff for Stats Buffs, Part 2

Last week, we introduced you to the basics of advanced basketball statistics, the Four Factors.

If you missed that feature, you can find it here:

https://piratings.wordpress.com/2019/01/09/advanced-basketball-statistics-fun-stuff-for-stats-buffs/

This week, we hope to explain how to apply advanced stats to individual players. It is a bit more involved, but if you break it down, it is not difficult to understand.

Then, in our final installment next week, we will attempt to explain offensive and defensive efficiency, which is a multiple step process and quite involved, but once you have the formulas placed in a spreadsheet, you can have the same data that the Selection Committee will have in the room when they meet to select the field and seed the teams.

Let’s start with individual statistics.

True Shooting %
The basic shooting stat for an individual is True Shooting Percentage. It incorporates field goal shooting from behind the three-point line, inside the line, and foul shooting into one percentage that provides a decent look at how efficient a player is when he shoots the ball to his basket.

 
The formula for TS% is: College: Pts/(2*(FGA+(.465*FTA))) &

NBA Pts/(2*(FGA+(.44*FTA)))

Example: Let’s take a look at the incredible Markus Howard of Marquette. As of this afternoon (January 15, 2019), Howard has scored 439 points for the season. He has taken 301 field goal attempts and 116 free throw attempts.

439/(2*(301+(.465*116))) = .618 or 61.8%

Let’s now take a look at a big man and how Howard stacks up as a perimeter player. Let’s look at Gonzaga’s Rui Hachimura. As of this afternoon, the Bulldogs’ power forward has scored 374 points on 233 field goal attempts and 117 free throw attempts.

374/(2*(233+(.465*117)))= .651 or 65.1%
Hachimura is a little more efficient in scoring points when he shoots the ball for any reason than Howard, but they are both quite excellent at scoring for their teams.
How do they compare with a couple of all-time greats from the past?

Let’s look at Steph Curry’s and Bill Walton’s final years at Davidson and UCLA respectively.

Curry: 974/(2*(687+(.465*251)))= .606 or 60.6%, not as good as Howard so far this year.

Walton: 522/(2*(349+(.465*100)))=.660 or 66.%, which is a little better than Hachimura.

Hachimura has benefitted from some three-pointers that did not exist when Walton played at UCLA, but Walton would have never attempted a three-point shot playing in the low post for the Bruins. Walton also missed some games his senior year due to knee troubles, and he was a lousy foul shooter his last two years in Westwood, or else his TS% would have been even higher.

Offensive, Defensive, and Total Rebounding Percentage
For an individual player, the formula for offensive rebounding percentage is:

100 * [(Individual Player’s Offensive Rebounds * (Team Minutes Played/5)) / (Individual Player’s Minutes Played * (Team Offensive Rebounds + Opposing Team Defensive Rebounds))]

The formula looks bulky but it is quite easy to calculate and once you plug them into a spreadsheet, it is a quick process.

Defensive Rebounding percentage is just the opposite formula
100 * [(Individual Player’s Defensive Rebounds * (Team Minutes Played/5)) / (Individual Player’s Minutes Played * (Team Defensive Rebounds + Opposing Team Offensive Rebounds))]

And Total Rebounding Rebounding Percentage brings the whole into the parts.
100 * [(Individual Player’s Total Rebounds * Team Minutes Played/5) / (Individual Player’s Minutes Played * (Team Total Rebounds + Opposing Team Total Rebounds))]

Examples: Let’s compare the key board men from the hot rivals in the Big Ten: Kenny Goins of Michigan State and Jon Teske of Michigan

Goins offensive rebounding: 100 * [(41*3425/5)) / (450 * (201 + 356))] = 11.2%
Goins defensive rebounding: 100* [(119*3425/5)) / 450 * (543 + 185))] = 24.9%
Goins total rebounding: 100 * [(160 * 3425/5) / (450 * (744 + 541))] = 19.0%

Teske offensive rebounding: 100 * [(31 * 3400/5)) / (458 * (156 + 415))] = 8.1%
Teske defensive rebounding: 100 * [(82 * 3400/5)) / (458 * (463+135))] = 20.4%
Teske total rebounding: 100 * [(113 * 3400/5)) / (450 * (619+550))] = 14.6%

Because Michigan and Michigan State have played comparable schedules this year, Goins is a little better on both the offensive and defensive glass than the seven-foot Teske.

For what it is worth, Blake Griffin’s total rebounding percentage in 2009 at Oklahoma was 24.0, so Goins and Teske are not quite up to his lofty standards.

Turnover Percentage

The formula for individual TOV% is: 100 * TOV / (FGA + (.465 * FTA) + TOV)

It is rather simple to calculate, but it has its limitations, because point guards handle the ball much more per possession than other players, and this formula does not include assists which might show that it is worth a couple extra points of TOV% for a point guard to have higher numbers of assists. Additionally, some point guards do not attempt many shots, so the denominator of this equation is skewed too low.

We’ll combine this stat with the next stat to come up with an improvement over assist to turnover rate.

Let’s look at a couple of outstanding playmakers–Cassius Winston of Michigan State and Jared Harper of Auburn.

Winston: 100 * 42 / (205 + (.465 * 69) + 42) = 15.0%
Harper: 100 * 32 / (183 + (.465 * 53) + 32) = 13.4%

Assist Percentage
Now we give the playmakers a chance to shine and balance out the bad turnover percentages they receive for having possession of the ball more than others (like a running back in football will fumble the ball more than the tight end per team possession).
The formula for individial AST% is: 100 * AST / (((MP / (Team MP/5)) * Team FG) – FG)

Winston: 100 * 125 / (((528/(3425/5)) * 517) – 100) = 41.9%
Harper: 100 * 101 / (((506/(3050/5)) * 452) -69) = 33.0%

Assist Percentage to Turnover Percentage

Simply divide AST%/TOV% to get a better ratio than the standard AST/TOV.

Winston: 41.9/15.0 = 2.8
Harper: 33.0/13.4 = 2.5

Both of these rates are outstanding. For Michigan State, the Spartans have an outstanding playmaker in Winston, an outstanding dominator on the glass in Goins, and an outstanding group of shooters and defenders. Coach Tom Izzo has a Final Four caliber team for sure.

Block Percentage
Blocks are very important defensive tools. Obviously every time a player blocks a shot, it is also a missed field goal attempt for the other team. Obviously, a blocked shot is not as valuable as the non-blocked missed field goal attempt, because not every blocked shot would have been a made shot, and more blocked shots become offensive rebounds or offensive team rebounds than regular missed shots. However, an intimidator underneath the basket can influence a lot of shots that he does not block, thus lowering non-blocked field goal percentages. There are multiple algorithms used to calculate how valuable a blocked shot is worth in points with and without the inclusion of intimidation.

We like to compare this variable to baseball’s stolen base variable, where traditional sabermetrics lovers hate the stolen base attempt due to the effects on WAR not being great and needing a base stealer that can consistently steal better than 75% of the bases he attempts. They don’t factor in the extracurricular events such as middle infielders having to cheat a step closer to second base, pitchers worried about throwing off-speed (non fastball) pitches, pitchers having to throw to first a lot to reduce leads, and even the first baseman having to delay by a fraction of a second before moving out to cover his area.

For instance, when Maury Wills was stealing bases left and right for the Los Angeles Dodgers in the early 1960’s, Jim Gilliam benefited from being the next batter in the batting order. Gilliam liked to take a lot of pitches, so taking a couple to give Wills a chance to steal didn’t harm him. Actually, because pitchers worried so much, Gilliam was frequently ahead in the count. A veteran with a 2-0 count can hit about 100 points higher than when he has an 0-2 count. Also, Gilliam was an excellent placement hitter. He could hit the ball in the open space created by the first baseman holding Wills on base. When the switch-hitting Gilliam faced a left-handed batter, and the second baseman was covering the bag, while the first baseman was holding Wills on, Gilliam saw a monstrous hole to slap grounders towards right field that allowed Wills to take third base.

Editorial over

Here is the formula for Block Percentage
100 * (Blk * (Team MP/5)) / (MP * (Opponents FGA – Opponents 3-Point Attempts))

Example: Brandon Clarke of Gonzaga is a true intimidator in the paint. His ability to swat balls away has helped the Zags hold teams to just 38.8% field goal shooting. Here is his BLK%.

100 * (58 * (3600/5)) / 497 * (1148-418) = 11.5%

When a player has a double digit BLK%, it is almost a fact that he is also an intimidator in the paint, which means other teams will miss three or four shots that they normally would make against other teams. This is in addition to the blocks that would have been made baskets had they not been blocked.
If an opposing team normally averages 27 field goals on 58 attempts for 46.6%, but with Clarke’s blocks and intimidation this opponent hits only 21 of their 58 attempts for 36.2%. That is a 10% difference created mostly by one intimidating player. Block percentage is one of the most underrated defensive tools in basketball.

Steal Percentage
The steal is a dying art but for a reason. Ninety-five to ninety-nine percent of the time, the steal comes from an intercepted pass and not from a player actually stealing the ball off a player’s dribble. So, steals should be renamed as interceptions like in football. Because so many teams cannot pass the ball worth a darn these days, steals have been dropping in number for several years. This does not mean that the monotonous dribbling of the ball is the way for offenses to score. It is easier to guard the movement of a dribbled ball opposed to the movement of a passed ball, because a dribbler can rarely exceed 15 MPH, while a weak pass is double that speed and a crisp pass is triple that speed or more. When you see a player dribble the ball all the way up the floor on a fast break attempt, he is actually hurting his team’s chances of scoring points on that break. Two quick passes up the floor can result in a wide open basket and/or defensive foul. Many times, the dribbling player is the last of the 10 players to enter the scoring zone, and then the fast break is dead.

Once again editorial over.

The formula for steal percentage is: (100 * Steals * (Team MP/5)) / (Player MP * Opponents Possessions)

You can find team possessions in many locations today, but if you need to calculate this from scratch, team possessions can be very accurately estimated by this calculation:

FGA + (.465 * FTA) – Off. Rebounds + Turnovers {for college}

FGA + (.44 * FTA) – Off. Rebounds + Turnovers {for NBA}

If you are trying to calculate this for your high school, middle school, or youth league team, you will have to adjust the constant that you multiple with FTA. Unfortunately, we do not know what to use for the constants.

Example: Tremont Waters of LSU has come close this year to recording a triple double the hard way with points, assists, and steals. He needed two more steals against UL-Monroe to pull off a feat that is extremely rare in the 21st Century.
Here is Waters’ Steal %.
(100 * 45 * 3050/5) (478 * 1088) = 5.28%

This is an excellent percentage, but it does not approach the percentages of past years, especially when more teams used full-court pressure defense for 40 minutes per game. Some of the Kentucky players under Coach Rick Pitino exceeded 6%.

Usage Percentage
Usage percentage attempts tp gauge the percentage of team plays in which a specific player was key to the possession. It actually measures percentage of team plays USED by an individual while he was on the floor.

The formula for USG % is: 100 * ((FGA + (.465*FTA) + TOV) * (Team MP/5)) / (MP * (Team FGA + (.465* Team FTA)+Team TOV))

Example: Carsen Edwards of Purdue is heavily involved in all of the Boilermakers’ possessions.

100 * ((313 + (.465 * 90) + 52) * (3225/5)) / (537 * (985 + (.465*194)+174)) = 39.1%

At the same time, teammate Ryan Cline plays about the same number of minutes per game but has a USG% that is less than half of Edwards. Thus, Edwards is vital to Purdue’s offensive success. If Edwards gets in foul trouble, Purdue is in much worse shape than if Cline gets in foul trouble. Of course, Matt Painter doesn’t want either star getting into foul trouble, as they both play better than 33 minutes per game.

In our final installment of Fun Stuff for Stats Buffs, we will attempt to explain offensive and defensive efficiency ratings, the big advance metric that the Selection Committee will use as part of their selection and seeding criteria. It is quite bulky and involves multiple steps to figure. If you ever tried to calculate Base Runs in baseball, you know how involved that calculation was. oRAT and dRAT make base runs calculations look like simple addition.

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January 9, 2019

Advanced Basketball Statistics–Fun Stuff for Stats Buffs

This feature today is not for everybody. You have to be a stats fan for this one to be fun to read. Last year, we were asked to explain some of the advanced basketball metrics used today. Then, a couple weeks ago, we were asked again what certain metrics were. So, this will be an attempt to explain the basic advanced metrics and then to some degree how one might use this data to determine an approximate point spread difference.

If you are not familiar with advanced metrics in sports, it all started with baseball many decades ago. The legendary general manager of the then Brooklyn Dodgers, Branch Rickey, was always many years ahead of his contemporaries. He had basically created the farm system for Minor League baseball in the late 1920’s, and he opened the game to African Americans and then created a pipeline in Latin America for the Dodgers to take advantage there. Around the same time, Rickey was looking for a statistical advantage to evaluating baseball players, using mathematics to find hidden gems of talent that might have been somewhat overlooked by the competition. This was 50 years before Money Ball. Rickey aligned with a mathematics genius by the name of Alan Roth, who had previously tried to show some of his ideas to other baseball owners, but none of these owners had an interest. Rickey was more than interested, and he hired Roth to work for the Dodgers about the same time as Jackie Robinson debuted in Brooklyn.

Roth was one of the first baseball statisticians to realize that RBIs were basically worthless as a stat. For two decades, he worked for the Dodgers charting where players hit balls, what pitches they hit, and who fielded or did not field balls. This technology would not come into the norm for another 40 years.

Many others presented statistical data for baseball through the 1960’s, 1970’s, and 1980’s. Some of these math experts wrote books, such as Earnshaw Cook and his great work called, Percentage Baseball. It is this book that I read many years ago that roped me into the world of advanced baseball statistics.

A lot of you reading this know who Billy Beane is and what “Money Ball” is. Let me clue you in on something. This was not the first big leap into computer-generated advanced baseball statistics. It wasn’t even the first attempt by the Oakland Athletics. Beane’s predecessor, Sandy Alderson, brought the computer big time into baseball, but you could argue that Earl Weaver with the Baltimore Orioles had a basic no frills database of his batters’ and pitchers’ successes and failures against the pitchers and hitters throughout the American League.

About the time that Money Ball had come out in book form, other mathematics experts began looking at different sports. Computer specialists had come up with somewhat successful algorithms to pick winners against the point spread in football, and one or two became quite wealthy until the state of Nevada banned their wagering for life.

In the late 1990’s, the NBA began looking for ways to take advantage of the numbers to maximize talent. Was it worth it to shoot the 3-pointer? Was it better to have a strong rebounding team that maybe didn’t shoot as well than a weaker rebounding team that shot better? What was the best number of minutes to play your star players, and the best number of minutes to play your second team players? Could statistics show enough consistency to partially answer these questions?

Of course, the questions can never fully be answered. Until computers can read the minds of humans, they can never determine if Stephen Curry may have strained his right shoulder lifting his amazing daughter up in the air earlier that day. The computer cannot determine if the star player had a little too much pizza the night before and didn’t get a good night sleep. There is missing data that will be discovered in the future because basketball analytics are far behind baseball in the evolutionary process.
Basketball is starting to catch up now that very expensive software exists in NBA gyms where multiple cameras are placed in the rafters of the arenas, which feed into a computer and can show teams where all 10 players were on the floor for each 1/100 of a second of the game. If the power forward was beaten for an easy jumper when the shooter came off a baseline screen, the computer records this. Within a few years, the game will become every bit as scientific as baseball, and you will see more Cal Tech and MIT grads working in front offices.
By now, you must realize that trying to explain all the advanced basketball metrics would be terribly boring and very difficult to do. I admit that I am not the authority on basketball metrics, but then I get paid for baseball analytics and not basketball analytics.

Here is a brief look at some of the advanced stats for basketball. If you are interested, you should be able to set up these formulas on a spreadsheet and then plug your team’s stats in and have some of the more popular advanced stats for the team you follow. You can even use these stats for lower levels (high school, middle school, youth league), but the formulas must be altered by an amount I cannot give you. There is a difference between NBA and college formulas, and there will be differences as you go down in experience. Some of it has to do with how many fouls it takes to put a team in the bonus and what that bonus is.
Let’s Begin
I must start with the most basic of advanced statistics. This first set of stats will give you a lot more than the basic statistics. They are called, “The Four Factors,” but they are used for both a team’s offense and a team’s defense, so it is really eight factors.

Credit here must be given to the very brilliant Cal Tech statistician Dean Oliver who wrote the number one book on basketball statistics, Basketball on Paper. It is required reading if this is your field of interest. Oliver capitalized on his data and sold it and himself to a handful of NBA teams, but the basketball media wasn’t ready for his ideas.

They scrutinized every move made through his recommendations, forcing the NBA teams to give in to their fans that bought into the media’s opinions. Of course, many of these media hacks cannot balance their own checkbooks, so their scrutiny comes without credibility.  I say this because I was once a media hack in a top 30 market who believed a lot of the preconceived misconceptions of sports.
The “Four Factors” (again eight factors since this is figured for the offense and the defense) are:

1. Effective Field Goal Percentage
2. Turnover Rate
3. Offensive Rebounding Rate
4. Free Throw Rate.

While these factors are still quite valid, they have been surpassed somewhat by more advanced data. For example, True Shooting Percentage is more detailed than EFg%.

Here are the easy calculations for the Four Factors.
1. Effective Field Goal Percentage
This stat adds three point shooting to two point shooting into one stat. A made three-pointer is worth 50% more than a made two-pointer. So, if you make 1/3 of your three-pointers, it is the same as making 50% of your two-pointers.

The formula for eFG% is: (Field Goals Made + (0.5* 3-pointers Made))/Field Goals Attempted.

Let’s say that Duke takes 58 total shots in a game. They make 26 of these shots, and 8 of them are three-pointers. The calculation would be:

(26 +(0.5*8))/58 which equals .517 or 51.7%.

It works the same for defense. Let’s say in the same game, Duke’s opponent took 57 shots and made 24 with 7 of them three-pointers.

(24+(0.5*7))/57 = .482 or 48.2%.

1A. True Shooting Percentage combines Effective Field Goal Percentage with foul shooting into one combined scoring stat. As you will see with the 4th factor, there is debate over how to use FT Rate properly.

The NBA formula for True Shooting Percentage is: Pts/(2*(FGA+(.44*FTA))) but this is the NBA formula. As I mentioned above, the formula for college basketball is a little different, and it has to do with different Free Throw rules in the two organizations.

For college, it is: Pts/(2*(FGA+(.465*FTA)))

Let’s look at this for an individual. Here are Steph Curry’s Shooting Stats for his last year at Davidson.

Curry scored 974 points in 2008-09. He took 687 shots from the field and 251 foul shots.

974/(2*(687+(.465*251)))= .606 or 60.6% which for a guard is outstanding.

Compare this to Kareem Abdul-Jabbar’s sophomore season at UCLA in 1966-67, when the NCAA made the mistake of banning the dunk following his dominant first year on the varsity.  Jabbar, known then by his birth name of Lew Alcindor, scored 870 points that year with 519 shots from the field and 274 foul shots.

870/(2*(519+(.465*274)))=.673 or 67.3%.

You can see that a dominant post player like Jabbar was worth more in shooting than a top outside shooter like Curry. This is a relative statement, but it is like saying Babe Ruth was worth more as a hitter than Ty Cobb.

2. Turnover Rate
This measures the rate at which a team commits a turnover or forces the opponent to commit a turnover. We will stick with team stats for now, because the formulas for individuals are a bit more complex.

The calculation for Tunover Rate is:

TO / (FGA + (0.44 * FTA) + TO) for NBA, and
TO/(FGA+(.465*FTA+TO) for College

We will calculate a couple of extremes here. Let’s look at Temple in 1987-88 and Arkansas in 1993-94. Temple’s Coach John Chaney guided the 1987-88 Owls to the regular season number one ranking using an aggressive 2-3 matchup zone defense and a patient offense that valued every offensive possession like gold. Temple did not gamble on offense or defense, as they never attempted to force their offense or try to create turnovers with defensive pressure, preferring to force opponents to shoot poor shots.

Arkansas coach Nolan Richardson guided the Razorbacks to the national title in 1993-94. His teams pressed full court for 40 minutes (40 minutes of Hell) and played up-tempo fast-breaking offense. Arkansas committed more turnovers on offense, but they forced a lot more turnovers than average, and they came up with a lot of steals that led to easy points.

Temple in 1987-88 in 34 games
Offense: 305 Turnovers, 2,050 FGA, 704 FTA
Defense: 423 Turnovers, 1981 FGA, 513 FTA

Offensive TO Rate: 305/(2,050+(.465*704)+305) = .114 or 11.4%
Defensive TO Rate: 423/(1981+(.465*513)+423) = .160 or 16.0%

Arkansas in 1993-94 in 34 games
Offense: 539 Turnovers, 2,363 FGA, 834 FTA
Defense: 725 Turnovers, 2,234 FGA, 817 FTA

Offensive TO Rate: 539/(2,363+(.465*834)+539) = .164 or 16.4%
Defensive TO Rate: 725/(2,234+(.465*817)+725) = .217 or 21.7%

Which team was better at total turnover differential, Temple in 1988 or Arkansas in 1994? It was basically a wash. Temple played conservative basketball about as good as it could be played, going 32-2 and outscoring opponents by 15+ points per game. Arkansas played havoc basketball and went 31-3 outscoring opponents by almost 18 points per game. Both styles worked.

3. Offensive Rebound Rate (and, of course, Defensive Rebound Rate)
This measures the rate a team gets offensive rebounds and the rate in which it limits its opponents from getting offensive rebounds, which is obviously the rate of getting defensive rebounds. These stats allow the statistician to quickly see the opposite without having to perform double calculation. If Michigan State gets 36% of the rebounds on their offensive side of the floor, then Michigan State’s opponents will obviously get 64% of the rebounds on their defensive end of the floor.

The calculation for Offensive Rebound Rate is: Off. Reb/(Off. Reb + opponents Def. Reb),

 and thus the Defensive Rebound Rate is: Def. Reb/(Def. Reb + opponents Off. Reb)

Coach Tom Izzo has his Michigan State Spartans totally dominating the glass this year. Their rebounding margin of 11 boards per game is giving the Spartans an incredible advantage in games (how much we will see later).

Let’s calculate their Offensive Rebound Rate so far this season:
Offensive Rebounds = 190 Defensive Rebounds = 337
Opponents Offensive Rebounds = 176 Defensive Rebounds = 513

Michigan State’s Off. Rebound Rate = 190/(190+337) = .361 or 36.1%
Michigan State’s Def. Rebound Rate = 513/(513+176) = .748 or 74.8%

You can also figure total Rebound Rate, which isn’t a Four Factor, but easy enough by taking Michigan State’s percentage of total rebounds. (190+513)/(190+513+337+176) = 57.8%

4. Free Throw Rate
This is the most controversial of the Four Factors, and there are now multiple theories about how best to calculate this stat. The original formula was simply FTA/FGA. Many metric specialists (including me) believe this is not the best way to calculate free throw rate. For one, this original formula does not calculate made free throws. Shaquille O’Neal would be just as effective and maybe more effective than Steph Curry, and there is no way you can convince me that Shaq’s free throw rate should be as strong or stronger than Curry’s.
There is another school of thought, which is the one the PiRate Ratings have adopted, and that is Free Throws Made per 100 possessions. The calculation is a bit more involved since you need the number of possessions, but total possessions is now kept as a stat in college basketball, and there is a formula that accurately approximates possessions.

Our Accepted FT Rate Calculation is: FT Made per 100 possessions.

If you do not have the number of possessions, you calculate it this way:

NBA: FGA+ (.44 * FTA) – Off. Rebounds + Turnovers
College: FGA +(.465 * FTA – Off. Rebounds + Turnovers

An example from a real game–last Sunday’s Michigan vs. Indiana game.
Michigan took 58 shots in the game. They had 16 Free Throw Attemps, 7 offensive rebounds, and an amazing 2 turnovers.

Let’s calculate their possessions: 58 + (.465*16) -7 + 2 = 60.44

In the actual game box score, Michigan had 60 possessions. In other words, this formula is very accurate, and when there is a difference of one possession in the calculation, it usually is because the team that controlled the opening tap also had the last possession of the half.
Michigan made 12 free throws in their 60 possessions, so we now have to normalize this to how many they would have made in 100 possessions, which is quite simple.

12/60*100 = 20.0, so Michigan’s Free Throw Rate in this game was 20.0.

If we use the original formula, Michigan had 16 FTA and 58 FGA for a rate of 16/58 or 27.6%. We feel that this overstates Michigan’s rate here. Because there were just 60 possessions in this game (about as low as a 30-second shot clock game can produce), the rate was inflated.

There is a third school of thought by stating this formula as FT Made / FG Attempted, which is a bit more accurate than FTA/FGA, but we still prefer making our rate per 100 possessions.

Putting it all together
So, now you have the four factors. How can we take this data before a game is played and determine an estimated point spread? It is not an exact science.

Let’s return briefly to baseball. In baseball, you have the infamous WAR stat, where players are rated in wins above a replacement player, a replacement player being somebody you can pick up on waivers or call up from AAA. There is no WAR stat at this time for basketball, although many statisticians have tried to calculate one from game stats. The problem is that it is hard to judge defense in basketball compared to judging pitching and fielding in baseball.

So, the answer is to find a way to determine how much weight to place on each of the Four (Eight) Factors to try to determine which team is better.

In the NBA, this calculation is considerably easier than in college, because strength of schedule only marginally differs in pro basketball, as most teams play an equal schedule strength. It can be argued that Golden State’s schedule is easier than Philadelphia’s schedule, because the Warrior won’t play Golden State, while the 76ers don’t benefit from playing Philadelphia, but that becomes negligible as the season progresses.

In college basketball, the Patriot League and the Big Ten are not close to comparable, so Lehigh’s Four Factors’ stats are not equal with Michigan’s Four Factors’ stats.
Originally, Oliver determined that Effective Field Goal Percentage was by far the most important of the Four Factors, and since there are a lot more shots taken in a basketball game than anything else, it goes without saying that this factor should be the most important. If your team can consistently beat its opponents in eFG%, they will win more games than they lose. If your team has an eFG% that is 10% better than the opponents, then your team is playing at a championship level.

Oliver believed that eFG% was about 40% of the success or failure of a team. He stated that turnover rate was worth 25%, offensive rebound rate was worth 20%, and FT Rate was worth the remaining 15%. In back-testing, these numbers approximated success or failure in the NBA.

It took many hours of algorithm testing for the PiRate Ratings to come up with percentages to apply to these factors. In the end, we had to create two more factors to approach legitimate accuracy.
If you have followed this site during basketball season for some time, you have probably heard about our own creation called “R+T Factor.” This is a refined version of the rebounding rate and turnover rate, which probably is the reason why Oliver gave a bit more weight to turnovers than rebounds. The key is to separate turnovers into steals and everything else. A steal in basketball is worth more than a rebound. When a team steals the ball, the chances of getting an easy basket and/or drawing a foul is much higher than obtaining a rebound. After working with the formula for a few years, we finally came up with one we like.

Our R+T rating is: (R*2) + (S*.5) + (6-Opp S) + T, where
R= Rebound Margin
S= Average Steals Per Game
T= Turnover Margin

In 2017, one NCAA Team had a rebound margin of 12.3 per game.  They had a turnover margin of 1.8 per game (which means that they committed 1.8 fewer turnovers per game than their opponents), averaged 7.1 steals per game, and opponents averaged 6.2 steals per game.

This team’s R+T Rating was: (12.3*2) + (7.1*0.5) + (6-6.2) + 1.8 = 17.5

This team played in one of the top power conferences in the NCAA, and their rating of 17.5 was the best among the power conference teams.  When a power conference team has an R+T rating over 10, they are Sweet 16 caliber.  At 15, they are Final Four caliber.  So, it can be deduced that this team did fairly well in the 2017 tournament.

This team was national champion North Carolina.

This R+T stat tries to estimate the number of extra scoring opportunities a team gets in a game. The stat is much more valuable in the NCAA Tournament where there are 25-30 really strong teams playing. When the pressure is on, many times these extra opportunities decide the outcomes. While effective field goal percentage is still the number one variable, the R+T rating becomes more and more valuable as the tournament progresses. By the Sweet 16, the teams with the best R+T rating usually continue to advance, and in many years, the team with the number one R+T rating weighted by schedule strength wins the National Championship. In every season in the 21st Century, the champion has been among the nation’s leaders in R+T factor weighted against schedule strength.
The obvious second added factor in predicting basketball games is schedule strength. If a team in the Ivy League outscores its opposition by 10 points per game, they are not as good as a team from the ACC outscoring opponents by 10 points per game.

At the start of conference play, one SEC team may have played a non-conference schedule that on average is 10 points weaker per game than another team. Kentucky usually plays a much harder pre-conference schedule than Vanderbilt or Ole Miss. Tennessee has played a more difficult schedule than Missouri.

Once conferences have played more than half of their league schedules, you can even calculate ratings based only on conference games played and then take those ratings and rank the conferences overall to get a more accurate rating for every team.

For example, let’s say that on February 20 with 80% of the Big 12 conference games in the books, Texas Tech is 1 point better than Kansas, 3 points better than Iowa State, and so on down to Oklahoma State being 14 points weaker than Texas Tech. Let’s say that Stephen F. Austin is 3 points better than Abilene Christian in the Southland Conference and 5 points better than Sam Houston. Overall, the Big 12 is calculated to be 17 points better on average than the Southland conference, so Texas Tech would be 17 points better than SF Austin, 20 points better than Abilene Christian, and 22 points better than Sam Houston. Oklahoma State would then be 8 points better than Sam Houston, since they are 14 points weaker than Texas Tech.
We don’t actually figure the ratings this way, but we have an algorithm that does a similar calculation for every team based on their overall strength of schedule for the season. It is a close cousin but goes more in-depth than the Quadrant system in place by the NCAA Selection Committee and used by our Bracketology experts when they pick their weekly selections, which by the way you can now see our PiRate Rating Bracketology at the Bracket Matrix, at http://www.bracketmatrix.com/ Our abbreviation there is “Pi.”

There are many additional advanced analytical basketball ratings. Also, you can break down the individual ratings for all of the Four Factors, as well as ratings that calculate individual offensive and defensive efficiency and the Usage Rate, which tries to estimate how much a player is used in his team’s games by looking at what he does while he is in the game. Some teams most efficient players may not have the top usage rates on their teams, while less efficient players get more game usage. Teams can look at these stats and good coaches can adjust their lineups to get their more efficient players more game time, while limiting players that may be harming the team. Then, there are coaches that continue to play the wrong players for too many minutes, while their actual more efficient players don’t play enough. There is a phrase for these coaches that continually do this: We call it “Soon to be unemployed.”

March 14, 2011

2011 PiRate NCAA Basketball Tournament Preview

Filed under: College Basketball — Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , — piratings @ 7:01 pm

1. Which teams meet the upper range criteria in every category?  That means they outscored their opponents by eight or more per game; their field goal percentage was greater than 7.5% better than their opponents; they outrebounded their opponents by five or more per game; they forced at least three more turnovers per game than they committed; and they stole the ball 7.5 or more times per game.

 

ANSWER—No teams this year meet all the perfect criteria described above.  Six teams come close to meeting the perfect criteria, but all fall short in at least one statistic.  This means there is no clear-cut favorite—only six teams that most closely resemble the great champions of the past.  Of the six, three come from power conferences.  These three are Kansas, Ohio State, and Syracuse.

 

Kansas fails to meet the turnover margin requirement, but the Jayhawks surpass all the other qualifications.  Ohio State comes up a tad bit short in field goal percentage margin, rebounding margin, and steals per game, but just misses in all three.  Syracuse misses in rebounding and turnover margin, but they Orangemen do not miss by much. 

 

2. Which teams can be immediately eliminated due to a negative R+T rating?  Which teams have an incredibly low R+T Rating (<2.0)?

 

ANSWER—Three teams can immediately be eliminated due to negative R+T Ratings.  It comes as no surprise that Alabama State and Texas-San Antonio, two teams facing off in the First Round in Dayton, have negative R+T ratings.  The third team is Michigan.  The Wolverines were outrebounded by 1.9 boards per game, and they only had a +1.4 turnover margin with just 4.7 steals per game.

 

Five other teams finished with R+T ratings less than 2.0.  This usually means one and done for these teams, unless they have outstanding FG% margins or cupcake opponents with worse criteria numbers.  Those five teams are: Penn State, Richmond, St. Peter’s, UCLA, and UCSB.

 

3. Which teams are capable of winning it all?

 

ANSWER—We separate the contenders from the pretenders by looking at the total PiRate Criteria score and then looking to see if the high criteria scoring teams receive merit on every individual statistic.

 

Last year, Duke was head and heels better than the other 64 teams.  The Blue Devils had the highest score overall, and they satisfactorily rated in every PiRate category.

 

No teams appear to be as strong this year as the Blue Devils were last year, but nine teams meet most of the minimum requirements to be considered Final Four contenders this year.

 

It should come as no surprise that the top two teams, Ohio State and Kansas, rank at the top in the Criteria.  Kansas actually has the highest score of the 68 teams, a score of 23.  The Jayhawks outscored their opposition by 17.2 points, shot 11.7% better from the field than their opponents, and outrebounded their opponents by 7.8 boards per game.  These stats are worthy of a powerhouse.  However, KU enjoyed just a 0.9 turnover margin and stole the ball 7.9 times per game, giving the Jayhawks an R+T Rating of 9.5.  We tend to look for teams with an R+T Rating in excess of 10, so KU is not a great favorite to go all the way. 

 

Ohio State’s total Criteria score is 21, good for second best.  However, the Buckeyes enjoy an R+T Rating of 13.2, which is a number we really like in a Final Four contender.  This number correlates to 13 extra scoring opportunities that their opposition does not receive.  OSU outscores their opponents by 17.3 points per game, shot 6.9% better from the field than they allows, outrebounded their opponents by 4.9 per game, had a turnover margin of +4.8, and stole the ball 7.2 times per game. 

 

San Diego State comes in third with 19 total criteria points.  BYU, Pittsburgh, and Texas come in next with 18 points; the Panthers have an R+T rating above 10.  The other three teams with PiRate Criteria scores showing themselves to be strong contenders for a Final Four berth are Syracuse, Purdue, and Duke

 

Florida, North Carolina, and UNLV are actually almost in a statistical tie with Duke, meaning those three are dark horse candidates for the Final Four.

 

Overall, this is the weakest field by far in the six tournaments where we have ranked the teams according to our criteria.  Looking back, this could be the weakest field since the tournament expanded to 64 teams. 

 

North Carolina State, Kansas, and Villanova won national titles in the past with less than stellar numbers.  We do not have all the statistics from those years, so we cannot really calculate criteria numbers for those three champions.  Could this be a season in which one team gets hot for six games and comes from out of the pack to win it all?  It could happen, but we are sticking with this mechanical system and going with its results.  Kansas, Ohio State, Pittsburgh, and Texas appear to be the best PiRate Criteria matches to past Final Four teams, and they are the quartet we officially pick to make it to Houston.  Syracuse becomes the wildcard team that could sneak into the mix.

 

Here is a look at the First Four Round One games and the 32 second round games.  The number in (parentheses) represents the PiRate Bracketnomics criteria number.

 

First Four Round

 

#16 Texas-San Antonio 19-13 (Elim) vs. #16 Alabama State 17-17 (Elim)

At first, we thought this was highly ironic, but upon further review, we consider it sort of a compliment.  These two teams both must be eliminated based on negative R+T ratings.  Of course, one of them must win this game so that they can advance to a 25-point or more loss in the next round.

 

Most of you filling out your brackets do not have to worry about these games in Dayton.  You get to turn in your choices after these games have been played.

 

UTSA has better criteria numbers after you factor out both teams’ R+T numbers. 

 

Prediction: Texas-San Antonio 64  Alabama State 55

 

 

#12 U A B 22-8 (2) vs. #12 Clemson 21-11 (1)

If you have been following the “experts” since the pairings were announced Sunday evening, then you know that these two teams do not belong in the tournament in their opinion.  It is not our mission statement to declare which teams should and should not have been included in the Big Dance, but we will tell you that Harvard and Saint Mary’s enjoyed Criteria scores several points better than these two teams, while Colorado and Virginia Tech had equal numbers to these two.

 

This game should be as close as the criteria scores show.  UAB has a one-point advantage in the criteria, but the Blazers just do not excel in any stage of the game.  Clemson’s strong point is forcing turnovers by way of steals, and that leads to a lot of cheap baskets.  Cheap baskets pay off big time in the NCAA Tournament, so we will take the Tigers in this one.

 

Prediction: Clemson 74  UAB 67

 

#11 Southern Cal 19-14 (-1) vs. #11 Virginia Commonwealth 23-11 (-1)

The winner of this game is going home two days later.  Neither team merits inclusion in the Big Dance this year. 

 

Southern Cal has no apparent weakness according to the PiRate Criteria.  In fact, they have a great resume—for an NIT team.

 

The Trojans outscore their opponents by four points per game, and they outshoot them by 3.3%.  They have a small rebounding margin of 1.2, and they have an even smaller turnover margin of 0.6.  They average six steals per game and have a R+T rating of 2.1.  On top of these modest numbers, their schedule was average.

 

VCU is much in the same boat as USC with two exceptions.  They have a negative turnover margin, but they also average 8.5 steals per game.

 

The only other difference in these teams is their records away from home.  USC won only 41% of their games, while VCU won 60%.

 

This one is quite tough to pick, but we will go with the Trojans due to their superior inside talent.  We expect USC to win the rebounding edge by at least five.

 

Prediction: Southern Cal  65  V C U  60

 

#16 UNC-Asheville 19-13 (-5) vs. #16 Arkansas-Little Rock 19-16 (-13)

Obviously, we have two teams that would not even merit NIT bids had they lost in the championship games of their conference tournaments.  UALR has one of the lowest Criteria Scores in the seven years we have been calculating this data.

 

UNC-Asheville actually has a couple of positive Criteria stats.  Their R+T is 5.5, which had it come against a more difficult schedule, would have made them worthy of becoming a possible team to watch in the Round of 64.

 

We will go with UNCA here, as schedule strength is about the same for both teams.

 

Prediction: UNC-Asheville 69  Arkansas-Little Rock 59

 

 

Second-Round Games

 

East Regional

 

#1 Ohio State 32-2 (21) vs. #16 UTSA (Elim)/Alabama State (Elim)

This game will be over quickly.  There will be no scare, not even for two TV timeouts.  The second highest Criteria score versus one of the teams with an R+T Rating of “Eliminate.”

 

The Buckeyes outscored their opponents by more than 17 points per game.  Their strength of schedule was 13 points better than UTSA and 16 points better than Alabama State. 

 

We will go under the theory that UTSA will be the opponent in this game.  Using our Criteria Rating, Ohio State figures to be 30-40 points better than UTSA.  Coach Thad Matta will definitely empty his bench early in this game, so the Buckeyes may “only win” by 25-30. 

 

Prediction: Ohio State 78  Texas-San Antonio 50

 

#8 George Mason 26-6 (8) vs. #9 Villanova 21-11 (5)

George Mason is the higher seed in this game, so if they win, it cannot really be considered an upset.

 

Villanova was on course to be a four-seed when the Wildcats were 16-5 and contending for the Big East Conference regular season title.  The Wildcats could not compete down low against the more physical teams in their league.

 

George Mason has a higher PiRate Criteria Score, but it is not an insurmountable advantage.  The key stat for this game is the R+T Rating.  For GMU, it is 6.8.  For VU, it is 4.9.  Considering that Villanova played a harder schedule, these numbers basically cancel each other out, thus making this a tossup game.

 

There are two variables to consider here.  George Mason performed much better on the road, and Villanova is banged up a bit.

 

Prediction: George Mason 66  Villanova 62

 

#5 West Virginia 20-11 (6) vs. #12 UAB (2)/Clemson (1)

We believe the Mountaineers will be facing Clemson in this game, but the prediction will hold up if they play UAB. 

 

West Virginia is not as good this season as last season, and the Mountaineers will not advance to the Final Four, or even the Elite Eight.  They are liable to be out by the end of the weekend.  However, they are strong enough to get into the Round of 32. 

 

The Mountaineers best attribute is that they put up decent numbers against one of the toughest schedules in the country.  Of the NCAA Tournament teams, only Georgetown played a tougher schedule.  They will have to limit turnovers, or else this game will be close and go down to the wire.  We believe Coach Bob Huggins will be able to keep the pace at a level he likes and not allow Clemson (or UAB) to force the Mountaineers into enough mistakes to turn the tide.

 

Prediction: West Virginia 69  Clemson 62 (Or UAB 58)

 

#4 Kentucky 25-8 (14) vs. #13 Princeton 25-6 (-2)

Princeton has pulled off the big upset in the past, and they came within a missed jumper at the buzzer of becoming the only #16 seed to beat a #1 seed.  However, that was two decades ago.  The Tigers have not been to the NCAA Tournament in seven years, and that big win over UCLA was 15 years ago. 

 

Kentucky is not the type of team that will allow Princeton’s style of play to affect their style of play.  The Wildcats should actually play better than their norm with fewer mistakes. 

 

We believe that Princeton will actually crumble under relentless man-to-man pressure and turn the ball over enough times in the opening minutes of the game to allow the Wildcats to open a quick double-digit lead.  This group of Cats tends to fiddle around a little once they get a quick double-digit lead and then play uninspired ball until the opponent makes a run.  Then, they go on the attack at the right time and put the game away.

 

Adolph Rupp had a team just like this in 1958.  They were called “The Fiddlin’ Five.”  They were also called National Champions.  We won’t go so far as to put UK into this category, but we will advance the Wildcats into the next round and then into the Sweet 16.

 

Prediction: Kentucky 72  Princeton 59

 

#6 Xavier 24-7 (8) vs. #11 Marquette 20-14 (3)

If you are looking for a tough, hard-fought game with two Midwestern teams, then tune into this game Friday evening.

 

If the Musketeers were a little more competent at forcing turnovers, they could be a dark horse candidate to advance to the Elite Eight.  XU shoots the ball well and plays well on defense when it comes to preventing a lot of easy shots.  They do well on the boards, and against a team that cannot exploit their ball-handling and ball-hawking deficiencies, they will hold their own inside.  The only other possible problem for the Musketeers is a lack of depth, but in the NCAA Tournaments, TV timeouts are longer.  It is hard to wear a team down with such long breaks every four or so minutes.

 

Marquette does not have enough depth to take advantage of Xavier’s lack of depth, so this factor will become a non-factor.  The Golden Eagles got to this tournament due to their ability to put the ball into the basket.  Marquette needs to shoot better than 46% to win, while Xavier is adept at holding teams under 45% as a rule.

 

Prediction: Xavier 71  Marquette 65

 

#3 Syracuse 26-7 (17) vs. #14 Indiana State 20-13 (-4)

Syracuse has been getting very little national exposure since their 18-0 start ended with an 8-7 finish.  The Orangemen are a team to watch in this tournament.  If not for a pedestrian 71% winning percentage away from the Carrier Dome, we would have them as one of the top four teams in this tournament.

 

Coach Jim Boeheim’s team outscores their opposition by 10.3 points per game; they outshoot them by 7.6%, and they outrebound them by 3.6 boards per game.  Their turnover margin is +1.9, and they averaged almost nine steals per game.  Their R+T Rating is 7.6, and their Strength of Schedule is somewhere between above-average and very good.  This is the Criteria Score of a team that will advance to the Sweet 16 and compete for an Elite Eight and Final Four berth.

 

Indiana State needs the return of Larry Bird to win this game.  They are too perimeter-oriented.  The Sycamores do not have the beef down low to contend in the paint, and even though Syracuse plays a 2-3 zone, teams rarely beat the Orangemen by firing up 25 long-range bombs.

 

This one smells like a blowout.

 

Prediction: Syracuse 81  Indiana State 62

 

#7 Washington 23-10 (13) vs. #10 Georgia 21-11 (2)

Washington is one of those teams that can play with anybody in this tournament—when they are playing up to their potential.  The Huskies could also exit in the first round if they play like they did the weekend they went to Oregon and Oregon State.

 

Georgia is much more consistent, but their best effort will not defeat the Huskies’ best effort.

 

Washington lacked the seasoned experience this season, and it showed when they ventured away from Seattle.  The Huskies lost to weaker opponents because they lacked the composure to win on foreign courts.  That changed when they arrived in Los Angeles for the Pac-10 Tournament.  Isaiah Thomas took over command of the team and led them to the tournament title.  This makes UW a scary and dangerous team capable of returning to the Sweet 16.

 

Georgia must really dominate the glass in this game, because we believe they will turn the ball over too many times against UW’s pressure man-to-man defense.  It is our opinion that the Bulldogs will play a little timidly at the start of this game and find themselves in a hole.

 

The Bulldogs had trouble against Alabama’s defense, and Washington is similar but with a much better offense.

 

Prediction: Washington 78  Georgia 70

 

#2 North Carolina 26-7 (15) vs. #15 Long Island 27-5 (-1)

 

Long Island is just the type of team that can forget that their opponent is a dynasty program that chews up and spits out little programs like this.

 

Teams from Brooklyn don’t intimidate easily, especially when they are led by a trio of Texans.  So, LIU will not be intimidated, but will they be talented enough to make a game of this contest?

 

That’s the rub.  They lack the defensive ability to slow down the Tar Heels, while Coach Roy Williams’ team will be able to hold the Blackbirds under their scoring average.  The big problem for LIU will be holding onto the ball, and we could see North Carolina forcing 20 turnovers in this game.  When the Tar Heels force more turnovers than they commit, they are almost unbeatable.  This game could be interesting for a short time, but it will eventually get out of hand.

 

Prediction: North Carolina 88  Long Island 70

 

West Regional

 

#1 Duke 30-4 (15) vs. #16 Hampton 24-8 (-8)

Duke has nothing to worry about here.  This will be like one of their November/December home games where they quickly put the cupcake away with a barrage of power and speed.  You know the type: a 37-point win over Princeton; a 34-point win over Miami of Ohio; a 52-point win over Colgate.

 

Hampton got to the Dance using an aggressive defense and three-point shooting barrage on offense.  Duke will not be affected by the defensive pressure, and they will cut off the open shots from the outside.  It will be a mercy killing, and it will be quick.  Look for the Blue Devils to be up by more than 15 points before the halfway point of the first half.  By the time Coach K empties the bench, the Blue Devils should be up by 25-30 points.

 

Prediction: Duke 81  Hampton 61

 

#8 Michigan 20-13 (Elim) vs. #9 Tennessee 19-14 (10)

Michigan is the highest-rated team that fails to meet our R+T Rating requirement, so the Wolverines are automatically tabbed as a first-round loser.

 

Coach Jim Beilein has been in a similar position before.  He guided a West Virginia team with not-so-flashy Criteria numbers to the Elite Eight, where they forced Louisville to come from 20 points down to rally for the victory.  That WVU team had one of the worst negative rebounding numbers of any team in Elite Eight history, but that team made few mistakes and had a nice turnover margin.

 

This Michigan team was only outrebounded by two a game, but they do not create enough extra possessions with their miniscule turnover margin of 1.4 and their average of just 4.7 steals per game.

 

Tennessee has been up and down, and the Volunteers are not going to make a repeat run to the Elite Eight this year.  However, Coach Bruce Pearl’s troops will control the boards in this game and maybe force more turnovers than they commit.  We figure that Tennessee will have 10 more opportunities to score in this game, and that is too many for the Wolverines to make up with their three-point shooting.

 

Prediction: Tennessee 74  Michigan 69

 

#5 Arizona 27-7 (3) vs. #12 Memphis 25-9 (-1)

Memphis was not going to earn an at-large bid this season had they failed to win the Conference USA Tournament.  They received an ideal first round opponent, and the Tigers actually have a fighting chance to pull off yet another classic #12-seed over #5-seed upset.

 

Arizona needs to pound the ball inside and rely on numerous offensive rebounds to win this game.  Other teams might be able to exploit Memphis’s poor ball-handling skills, but the Wildcats do not have the defensive acumen to take advantage here.

 

Memphis will try to make this an up-tempo game where they can neutralize Arizona’s height advantage inside.  It has a chance of working, but Arizona probably has too much power inside and just enough quickness to stop the Tigers’ transition game.

 

Prediction: Arizona 76  Memphis 69

 

#4 Texas 27-7 (18) vs. #13 Oakland 25-9 (3)

This has become a popular upset pick in the media.  Oakland has generated a lot of positive press, and many “experts” are calling for the upset in this game.  We are not one of them.  Not only do we believe the Longhorns will take care of Oakland with relative ease in this game, we believe Texas is a force to be reckoned with in the next two or three rounds. 

 

Let’s look at Texas’ Criteria Rating.  At 18, the ‘Horns rate as our sixth best team in the tournament.  They have a 13.5 point scoring margin, a 7.1% field goal margin, a 6.6 rebounding margin, and a 1.2 turnover margin.  Their only Achilles Heel is a low amount of steals resulting in a R+T Rating of 8.3.  Had that number been above 10, we would be selecting Coach Rick Barnes’ team for the Final Four.

 

Oakland won this year with strong rebounding and an excellent ability to force their opponents into bad shots.  Center Keith Benson is a future NBA player, but he is not enough to propel the Golden Grizzlies into the next round.

 

Prediction: Texas 77  Oakland 65

 

#6 Cincinnati 25-8 (9) vs. #11 Missouri 23-9 (10)

On paper, this looks like the best game of this round between a team with contrasting styles.

 

Cincinnati is one of the top defensive teams in the tournament.  The Bearcats are tough inside, and they have quality depth to continue playing hard in the paint. 

 

Missouri uses the “40 minutes of Hell” approach that Coach Mike Anderson learned under his mentor Nolan Richardson.  The Tigers press full court and run the fast break as often as they get the chance.  They are perimeter-oriented and can score a lot of points in a hurry.

 

When we try to decide tossup games, we look to the all-important defense and rebounding stats, since that is what wins close games in the Big Dance. 

 

Missouri is vulnerable in both of these crucial areas.  They have given up a lot of cheap baskets this year when teams solved their press.  The Tigers were outrebounded by 1.7 boards per game.

 

Cincinnati owns a +2.7 rebounding margin, and the Bearcats held onto the ball quite competently.  We believe Coach Mick Cronin’s crew will advance.

 

Prediction: Cincinnati 68  Missouri 65

 

#3 Connecticut 26-9 (9) vs. #14 Bucknell 25-8 (-4)

Ask Kansas Coach Bill Self if it is wise to underestimate Bucknell.  The Bison know how to hold onto the ball and work for intelligent shots.  Give them an opening, and they can bury you with a high field goal percentage.

 

Connecticut did the unthinkable by winning five games in five days.  Their defense does not get the merit it deserves, because Kemba Walker gets more attention for his offensive antics.  The Huskies actually held teams under 40% from the field.

 

Coach Jim Calhoun knows how to prepare a team for tournament action.  He will have UConn ready for this game, and the Huskies will not overlook the Bison.

 

Prediction: Connecticut 73  Bucknell 58

 

#7 Temple 25-7 (5) vs. #10 Penn State 19-14 (-1)

Temple’s score must be tempered by the fact that they are a wounded team coming into this tournament.  Two starters suffered injuries late in the season, and one is out for the remainder of the year, while the other may or may not be ready to play.  We must throw out Temple’s score of “5” in the PiRate Criteria, because 40% of the key players that produced that number will either not play or be greatly less effective.

 

Penn State is a lot like Southern Cal in this tournament.  The Nittany Lions have the look of a strong NIT team.  Aside from a so-so record against a strong schedule, they really have little to offer outside of one star player. 

 

We believe this Keystone State rivalry game will be close, and it could come down to the last shot.  Because the Owls are limping, we will go with the Big Ten representative.

 

Prediction: Penn State 59  Temple 56

 

#2 San Diego State 32-2 (19) vs. #15 Northern Colorado 21-10 (-6)

Most of you reading this probably cannot remember Texas Western University, but you may have scene the movie where the Miners were too quick for Kentucky and pulled off the big upset to win the 1966 National Championship.  Maybe some of you remember the Long Beach State 49ers ascension into the top 10 under Jerry Tarkanian and then Lute Olson.  Still more can remember when Tark the Shark moved to UNLV and turned the Runnin’ Rebels into a national power.

 

San Diego State is the next Western team to fit this bill.  The Aztecs are legitimate contenders to advance deep into this tournament.  They have few exploitable weaknesses, and they are the best team West of the Rockies.  Coach Steve Fisher knows how to get teams ready for tournament play, as he has three Final Fours on his resume and one National Championship.

 

SDSU’s PiRate Criteria numbers are flashy.  Their scoring margin is 13.3 points per game.  Their FG% margin is 7.1%.  They outrebound their opposition by almost seven per game, and they force 1.6 more turnovers than they commit.  Their one weak spot is a pedestrian 6.2 steals average.  If they run up against a more powerful team inside, they could have trouble getting enough extra scoring opportunities.

 

Northern Colorado will not be one of those teams that can cause trouble for the Aztecs.  The Bears are a good rebounding team, but their rebounding prowess came against a schedule that rates 10 points weaker than San Diego State’s schedule.

 

Prediction: San Diego State 73  Northern Colorado 51

 

Southwest Regional

#1 Kansas 32-2 (23) vs. #16 Boston U 21-13 (-11)

Kansas is a team on a mission.  The Jayhawks will not allow a repeat of what happened last year, and that extra incentive should be enough to send KU to Houston.

 

Kansas has the top PiRate Criteria Score this year.  They meet the basic requirements that most prior National Champions have met—scoring margin: 17.2; FG% margin: 11.7; Rebounding margin: 7.8; Turnover Margin: 0.9; Steals per game: 7.9; R+T Ratings: 9.5.

 

How do you beat this year’s KU team?  Kansas State and Texas pulled it off by matching up well inside and going head-to-head with them in the paint.

 

Boston U has the second lowest PiRate Criteria score of the 65 teams that have positive R+T Ratings.  The Terriers are way overmatched in this game, and they will have to be glad they just made it here.

 

Prediction: Kansas 90  Boston U 62

 

#8 U N L V 24-8 (15) vs. #9 Illinois 19-13 (1)

If our ratings are worth their salt, then this game should not be all that close.  UNLV may be just the third best team in the Mountain West, but the MWC was better overall this year than the Pac-10.  Third best in the MWC makes the Runnin’ Rebels one of the dozen or so teams capable of making a two weekend run.

 

Coach Lon Kruger has taken two different teams to the Elite Eight (Kansas State and Florida).  His teams play intelligently without being flashy.

 

UNLV went 24-3 against teams not named Brigham Young or San Diego State.  They are not particularly strong on the boards, and this will eventually be their downfall.  The Rebels shoot the ball brilliantly, and they alter enough opponent shots to force a lower field goal percentage.  They also take care of the ball and do not make a lot of floor mistakes.

 

Illinois is an inconsistent, underachieving team.  This can be dangerous for the prognosticator, because it is difficult if not impossible to predict which schizophrenic state will appear for each game.

 

The Illini are not particularly strong on the glass or at taking care of the ball, and that is a recipe for disaster when the opponent is as good as UNLV.  Even if Illinois comes out playing their best basketball, it may not be enough to beat UNLV playing their typical game.

 

Prediction: U N L V  72  Illinois 64

 

#5 Vanderbilt 23-10 (5) vs. #12 Richmond 26-7 (2)

Here is another game getting a lot of attention due to its upset potential.  Historically, the #12 seed produces the a lot of great upsets.

 

This game could go either way.  Both teams have exploitable weaknesses, and it just so happens that both teams’ have the assets capable of exploiting the other’s weaknesses.

 

Let’s start with Vanderbilt.  The Commodores are not particularly strong on the defensive perimeter.  Worthy opponents have been able to beat them off the drive and get a lot of open inside shots.  This weak perimeter defense has also led to frontcourt players having to help, thus leaving open holes near the basket.

 

Richmond’s offense is a modified version of the Princeton Offense.  The Spiders have the talent to get open shots inside and in the five to ten-foot range.

 

Richmond cannot rebound against more physical teams.  The Spiders make up for their rebounding liabilities by seldom throwing the ball away.

 

Vanderbilt has an excellent physical presence inside with three beefy players that can rebound the ball on offense and defense.

 

So, which team gets the edge in our PiRate Ratings?  We always look to defense in rebounding in tossup games.  Vanderbilt holds the rebounding edge, while Richmond holds the defensive edge.  It is basically a wash, so we have to look elsewhere.  While Richmond has been much better away from home, Vanderbilt’s schedule is seven points more difficult.  We’ll go with the power conference team, but not by much

 

Prediction: Vanderbilt 70  Richmond 67

 

#4 Louisville 25-9 (12) vs. #13 Morehead State 24-9 (3)

This should be an interesting game, but in the end the big brothers are going to defeat their little brothers in this battle of two Bluegrass State teams.

 

40 years ago this week, another little brother upset a big brother on their way to a surprise appearance in the Final Four (later vacated).  In 1971, Western Kentucky did not just upset Kentucky, the Hilltoppers ran the Wildcats off the floor.  Can there be a repeat two score later?  No!

 

Coach Rick Pitino’s Cardinals are vulnerable on the boards, and Morehead State has the nation’s best rebounder in the nation in Kenneth Faried.  However, the Eagles do not have enough talent or depth to keep up with Louisville.  They may emerge with a slight rebounding edge in this game, but it will not be enough to make up for all the open shots the Cardinals will get.

 

Louisville is going to run into trouble when they meet up with a team that can rebound and play credible defense.  That would be Kansas in the Sweet 16.  Until then, they have a relatively easy route to the Sweet 16.

 

Prediction: Louisville 78  Morehead State 62

 

#6 Georgetown 21-10 (8) vs. #11 Southern Cal (-1)/Va. Commonwealth (-1)

Last year, we discussed Georgetown’s vulnerabilities and the probability that they would fail to make it past the first weekend.  We expected the Hoyas to fall as a favorite in their second game, but they were a one and done team.

 

This year’s team is not much better than last year’s Hoya team, but they received a much more favorable draw.

 

Coach John Thompson III’s Hoyas once again have a rather low R+T Rating thanks to a turnover margin of -1.9 and a low amount of steals per game.  They will exit from the tournament in the next round unless there is a monumental upset in their pairing.

 

Neither USC nor VCU has the talent to take advantage of Georgetown’s deficiencies.  The three teams combined have a R+T rating below Purdue’s.

 

One additional note: The Hoyas will be a tad bit better than their Criteria Score in the tournament.  Chris Wright suffered a hand fracture in the middle of the schedule, and he is expected to be near 100% for the tournament.  You have to add maybe one point to their Criteria Score, but that is not enough to put them over the top in their second game.

 

Prediction: Georgetown 69  Southern Cal 61 (or VCU 60)

 

#3 Purdue 25-7 (16) vs. #14 St. Peter’s 20-13 (-7)

If only… Purdue fans will never know just how good their team might have been with Robbie Hummel joining JaJuan Johnson and E’Twaun Moore playing together.  This would have been the best Boilermaker team since Rick Mount led Purdue to the Championship Game against UCLA in 1969.

 

The Boilermakers no longer have that one glaring weakness that Gene Keady’s teams had and thus prevented Purdue from getting past the second round.  This team does well on the boards like most of those past Purdue teams, but they are particularly strong when it comes to forcing turnovers and taking advantage by converting steals into points.  It is the way many teams go on runs that put opponents out of commission.

 

St. Peter’s just barely avoided being immediately eliminated with a negative R+T Rating.  They squeaked by at 0.1.  It might as well be a negative number, as the Peacocks were outrebounded by 0.4 per game and had a turnover margin of -0.9 against a schedule that was four points below average and seven points weaker than the schedule Purdue faced.

 

Prediction: Purdue 73  St. Peter’s 56

 

#7 Texas A&M 24-8 (8) vs. #10 Florida State 21-10 (2)

The Big 12’s third best team has enough talent to challenge for a Sweet 16 berth.  We’ll leave the next round for another time and talk about this game.

 

The Aggies have no glaring weakness, and they have a few strengths, namely rebounding and defense (which wins games in the NCAA Tournament).  They are much like Kansas Lite.  A&M was not a team of surprises during the regular season.  They beat the teams they were supposed to beat and failed to upset the teams better than they were.  We expect the trend to continue.  They are better than the Seminoles.

 

Florida State does not take good care of the ball, and that costs them in confrontations against good opponents.  The Seminoles do not play particularly well away from Tallahassee, and they should be making a quick exit from the Dance.

 

Prediction: Texas A&M 73  Florida State 65

 

#2 Notre Dame 26-6 (11) vs. #15 Akron 23-12 (-9)

This is the best Irish team since Digger Phelps led Notre Dame in the late 1980’s.  Throw in the fact that this team has a chip on its shoulders following a first round exit last year, and the Irish have to be considered the Sweet 16 favorite in their four-team pairing this weekend.

 

The Irish finished the regular season with a scoring margin of 10.4 points per game.  Down the stretch, they went 7-2 against teams in this tournament.  The Selection Committee placed Notre Dame in a bracket that should provide a very memorable Sweet 16 contest against one of their most bitter arch-rivals.

 

Akron has a big seven-foot center, but the Zips do not rebound the ball all that well.  Zeke Marshall, the aforementioned big man, concentrates his efforts on blocking shots, and he frequently is not in position to rebound the ball.  So, the blocked shot frequently turns into a made basket off an offensive rebound.  The Zips did not fare well on the road this year, and with a considerably weaker schedule than average, this does not bode well.

 

Prediction:  Notre Dame 81  Akron 57

 

Southeast Regional

#1 Pittsburgh 27-5 (18) vs. #16 UNC-Asheville (-5)/U A L R (-13)

One of us here at the PiRate Ratings might be dating himself, but he sees a lot of the 1962 Cincinnati Bearcats in this year’s Pitt team.  The Panthers have a dominating inside power game that will pulverize any finesse team that cannot hit 10 three-pointers.  Neither UNCA nor UALR has a remote chance to make this game a close contest.

 

Pitt outscored their opposition by 13.1 points per game.  This stat looks even better when you factor in that they compiled this gaudy stat playing in a league that produced 11 NCAA Tournament teams.  The Panthers outshot their opponents by 7.6%, and they totally dominated the glass with a 10.4 rebounding advantage.  If you are thinking the way to beat them is to play a packed in zone, think again.  Ashton Gibbs can bury you from outside with his near 50% three-point accuracy, and Brad Wannamaker can still get the ball inside to one of the bruisers waiting to punish you with a thunder dunk.

 

Only a negative turnover margin prevents the Panthers from being there with Kansas as a co-favorite for winning all the marbles.

 

Pitt’s cupcake opponent will have to be happy with winning their First Four game, because they will be humiliated in this game.

 

Prediction: Pittsburgh 78  UNC-Asheville 54 (or UALR 48)

 

#8 Butler 23-9 (7) vs. #9 Old Dominion 27-6 (10)

This is the second best matchup in this round, and the winner will put a scare into Pittsburgh in the next round and even have a decent shot at the upset.

 

Butler is now the hunted rather than the hunter.  The Bulldogs will not sneak up on anybody this year.  More importantly, they are not as talented as they were last year.  The Bulldogs fared much better on the road last year than this season.  However, down the stretch, Butler started to look like a team proficient enough to get past the first weekend once again.

 

Old Dominion has the talent to advance past the first weekend as well.  The Monarchs are a miniature version of Pittsburgh, the team they would face in the next round should they win this game.

 

ODU is the nation’s number one rebounding team with a +12.2 margin.  The Monarchs’ schedule was not outstanding, but it was on par with several teams from the so-called power conferences, and they finished 6-4 against teams in this tournament.  This is a better ODU team than the one that upset Notre Dame in the first round last year, and this game should be one you do not want to miss.

 

 

Prediction: Old Dominion 72  Butler 70 in overtime

 

#5 Kansas State 22-10 (9) vs. #12 Utah State 30-3 (14)

This is the one game where a number 12 seed winning would not really be all that much of an upset.  Utah State should have been a top eight seed in this tournament.  If we were conspiracy buffs, we would say that the Selection Committee searched for a team that the Aggies do not match up with all that well and placed them in this spot to verify their actions.

 

Kansas State does not take care of the ball well enough to advance very deep into this tournament, but their first game opponent cannot take advantage of that weakness.

 

Utah State has dominated their opponents by forcing them to play a patient half-court game with very little scoring in transition.  They prefer to work the ball patiently for a good shot and then force opponents to take a low-percentage shot.  Thus, the Aggies outrebound their opponents, but they do so by forcing more bad shots than by out-leaping their opponents.

 

Kansas State has the talent to force Utah State to play at a quicker tempo and force them to defend one-on-one.  Jacob Pullen is a poor man’s (and smaller) Derrick Rose.  He can break down most opponents off the dribble, and he should be able to force USU to resort to some type of combination defense to keep him from going wild.

 

What scares us most about Utah State is that they had two opportunities to show they are deserving of their lofty ranking.  They lost to BYU and to Georgetown, and they never really threatened to pull of the upset in either game.

 

This is one game where we are going to go against our own chalk.  Kansas State’s schedule was seven points tougher, and the Wildcats can exploit the Aggies’ weaknesses.

 

Prediction: Kansas State 70  Utah State 63

 

#4 Wisconsin 23-8 (7) vs. #13 Belmont 30-4 (9)

This game has become the most-picked upset special around the nation.  Belmont is being compared with Butler of last year.  The Bruins are lofty of all this attention-gathering admiration, but Wisconsin is not the Washington Generals.

 

Belmont has the highest scoring margin in the nation at 18.4 points per game.  The Bruins outshot their opposition by 5.7% per game, and they took a lot of three-point attempts.  They outrebounded their opponents by 3.9, and they had an eye-popping 5.3 turnover margin.  They share the top steals per game average in this tournament with Missouri at 9.7, and their R+T Rating is the best in the tournament at 16.2 (three better than number two Ohio State).

 

Of course, these statistics were compiled against inferior competition.  Belmont’s schedule strength is nine points below the national average and a dozen below their first round opponent.  Against the opponents that made it to this tournament, they were 1-3.  They beat Alabama State by 13.  The three losses were on the road to in-state rivals Tennessee (twice) and Vanderbilt, but they led in the second half of those games.

 

The last time Belmont was in the Big Dance, the Bruins came within a missed last shot of sending Duke home.   

 

Wisconsin was not expected to be this good in 2011.  This was supposed to be a minor rebuilding season for the Badgers.  The Badgers usually run Coach Bo Ryan’s Swing Offense with great efficiency, rarely turning the ball over.  They outscored their opponents by 9.9 points per game, and they outshot they outrebounded them by 3.8 boards per game. 

 

The Badgers have been a hot and cold team this year.  When they have been hot, they have been nearly unbeatable, because Ryan’s teams always limit possessions.  When they have been cold, they have been easily beatable, because Ryan’s teams always limit possessions.  They finished the season as cold as ice, so the Badgers must be considered a slight underdog in this game.

 

Prediction: Belmont 74  Wisconsin 70

 

#6 St. John’s 21-11 (9) vs. #11 Gonzaga 24-9 (13)

Here is a game where we believe the seedings should be switched.  Gonzaga has been here enough times to be considered a regular in the NCAA Tournament, like Duke, Kansas, Ohio State, and Connecticut.  This makes a baker’s dozen consecutive appearances in the Big Dance for the Bulldogs. 

 

In past years, Gonzaga had a big scorer that could take over games.  Adam Morrison comes to mind.  This year, the Zags are more difficult to prepare for, because they are more team-oriented.  There is not a big star on the roster, but all five starters are capable of taking the team on his shoulders with a hot night.

 

In their nine-game winning streak to close the season, Gonzaga eliminated Saint Mary’s from the Dance party with two victories.  The Bulldogs scoring margin in those nine games was 76-58.  This is a good team playing its best ball of the year, and we expect Coach Mark Few to win yet another NCAA Tournament game.

 

St. John’s comes into the tournament minus one of its stars.  Starting forward D. J. Kennedy went down for the season with a knee injury in the Big East Tournament, and the Red Storm is now suspect in the paint.  Their Criteria Score of nine should be discounted by two to three points.  It is enough to take this contest from tossup status to near-comfortable status for Gonzaga.

 

Prediction: Gonzaga 74  St. John’s 66

 

#3 Brigham Young 30-4 (18) vs. #14 Wofford 21-12 (-1)

So, you didn’t get a chance to see Pete Maravich play at LSU in 1968, 1969, or 1970, eh?  We must admit that nobody will ever be the collegiate equal for Maravich, but Jimmer Fredette may be the closest thing to him.

 

Throw out the floppy socks and floppy Beatles haircut and throw out some of the most unbelievable passes in the history of the game (so unbelievable that Maravich’s teammates frequently could not see them coming), and Fredette is not that far behind Maravich.

 

The sports nation will be turning its eyes to this game just to see if Fredette can make a run at a single game scoring mark.  If we remember correctly, Notre Dame’s Austin Carr set the mark back in 1970 with 61 points against Ohio U in a regional qualifier game.

 

BYU may have been a strong Final Four contender had Brandon Davies not loved his girlfriend so much.  The Cougars averaged 8.7 fewer points per game once Davies was suspended. 

 

Wofford will not be able to take much advantage of Davies’ absence.  The Terriers fared well in all PiRate Criteria categories, but they did not meet even the minimum “numbers to look for” in any category, and their schedule strength was five points below the norm. 

 

Prediction: Brigham Young 75  Wofford 63

 

#7 U C L A 22-10 (-3) vs. #10 Michigan State 19-14 (1)

If only this were a few years ago.  Neither of these historically dominating teams is going to make waves in this year’s tournament, and the winner will be around for just one more game.

 

UCLA would be a national title contender if Kevin Love had stuck around for four years.  Imagine Love as a senior on this team.  Can you say Bill Walton-like numbers?  Alas, the Bruins must get by with a couple of well above-average forwards instead of the best three-man tandem in the nation.

 

The Bruins have the worst turnover margin of any team in this tournament.  At -3.4, UCLA would need to dominate on the boards, and while they usually win that battle, it is anything but dominating.

 

Michigan State’s one asset year in and year out under Coach Tom Izzo has been their rebounding acumen.  For most teams, a +4.3 edge on the boards would be considered outstanding, but in East Lansing, this is considered a down year. 

 

Neither team has done all that well away from their home court this season, and there really is only one stat where one team stands out ahead of the other.  MSU’s schedule was four points tougher than UCLA’s schedule.  That’s our spread for this game.  

 

Prediction: Michigan State 64  UCLA 60

 

#2 Florida 26-7 (15) vs. #15 UC-Santa Barbara 18-13 (-10)

The Gators looked like a potential Final Four team in the last month, at least when they were not playing Kentucky.  UCSB is not Kentucky. 

 

Florida tends to commit too many floor mistakes to win four games in this year’s tournament.  They have enough talent to get through the first weekend, but we do not see the Gators extending their stay after that.

 

UCSB upset Long Beach State to get here, and the Gauchos are one of the weakest teams in the tournament according to our Criteria Score.  With negative rebounding and turnover margins, they just barely escape automatic elimination with a R+T rating of 0.3. 

 

Prediction: Florida 76  U C S B  54

 

 

 

Our Bracket

 

You have seen the 32 teams that we believe will win the second round games.  Here is how we fill out the rest of our bracket.

 

Third Round Winners

Ohio State over George Mason

Kentucky over West Virginia

Syracuse over Xavier

North Carolina over Washington

Duke over Tennessee

Texas over Arizona

Connecticut over Cincinnati

San Diego State over Penn State

Kansas over UNLV

Louisville over Vanderbilt

Purdue over Georgetown

Notre Dame over Texas A&M

Pittsburgh over Old Dominion

Kansas State over Belmont

Gonzaga over Brigham Young

Florida over Michigan State

 

Sweet 16 Winners

Ohio State over Kentucky

Syracuse over North Carolina

Texas over Duke

San Diego State over Connecticut

Kansas over Louisville

Purdue over Notre Dame

Pittsburgh over Kansas State

Florida over Gonzaga

 

Elite 8 Winners

Ohio State over Syracuse

Texas over San Diego State

Kansas over Purdue

Pittsburgh over Florida

 

Semifinal Winners

Ohio State over Texas

Kansas over Pittsburgh

 

National Championship

Kansas over Ohio State

April 1, 2010

A PiRate Look At The Final Four

The PiRate All-Inclusive Look At The Final Four

Rosters, Stats, Results, PiRate Criteria Scores, and Analysis

National Semifinals

Date: Saturday, April 3, 2010

Place: Lucas Oil Stadium, Indianapolis

Our PiRate NCAA Tournament Criteria correctly picked half the field this year, getting it right with Duke and West Virginia.  We just missed getting three as Butler edged our pick from the West Regional, Kansas State, in the Elite 8.

Our overall number one pick and selection to win the Big Dance back when the field was announced is still going strong, and if the Blue Devils win it all Monday night, the PiRate picking formula will have succeeded in picking the National Champion for the fourth time in five years.

If the NCAA Tournament expands to 96 teams as it looks like might happen, we aren’t sure we will be able to handle the extra work to get this published.  33 extra teams might just be too much to get ready in a couple days.  To tell you the truth, 96 teams would be too much to keep our attention.  We would forget the first three rounds and do something else.  Heck, we might forget the tournament altogether.

Okay, let’s get down to the meat of this edition—The National Semifinal Round.

Game One: 6:07 PM EDT

 

Butler Bulldogs (32-4) vs. Michigan State Spartans (28-8)

 

Butler

 

Roster

No. Name Pos Ht Wt Yr Status
1 Shelvin Mack G 6-3 215 So Starter
2 Shawn Vanzant G 6-0 172 Jr Key Reserve
3 Zach Hahn G 6-1 176 Jr Plays In Every Game
5 Ronald Nored G 6-0 174 So Starter
11 Alex Anglin G/F 6-5 177 Jr Seldom Plays
14 Nick Rodgers G 6-2 168 Sr Seldom Plays
20 Gordon Hayward G/F 6-9 207 So Starter
21 Willie Veasley G/F 6-3 206 Sr Starter
22 Grant Leiendecker G 6-5 182 Jr Seldom Plays
24 Avery Jukes F 6-8 215 Sr Plays In Every Game
30 Emerson Kampen C 6-9 189 Fr Seldom Plays
32 Garrett Butcher F 6-7 209 So Seldom Plays
33 Chase Stigall G 6-4 195 Fr Seldom Plays
44 Andrew Smith C 6-11 239 Fr Plays Considerable Time
54 Matt Howard F 6-8 230 Jr Starter
HC Brad Stevens          
Ast Matthew Graves          
Ast Terry Johnson          
Ast Micah Shrewsbury          

 

Record:32-4, 18-0 Horizon      
Colors: Blue & White      
       
Opponent But Opp  
Davidson 73 62  
at Northwestern 67 54  
at Evansville 64 60  
Minnesota (Anaheim) 73 82  
UCLA (Anaheim) 69 67  
Clemson (Anaheim) 69 70  
at Ball State 59 38  
Valparaiso  84 67  
Georgetown (at NYC) 65 72  
Ohio State 74 66  
Xavier 69 68  
at Alabama-Birmingham 57 67  
UW-Green Bay 72 49  
UW-Milwaukee 80 67  
at Wright State 77 65  
at Detroit 64 62 ot
Cleveland State 64 55  
Youngstown State 91 61  
at Loyola of Chicago 48 47  
at Illinois-Chicago 84 55  
at UW-Green Bay 75 57  
at UW-Milwaukee 73 66  
Detroit 63 58  
Wright State 74 62  
Loyola of Chicago 62 47  
at Youngstown State 68 57  
at Cleveland State 70 59  
Illinois-Chicago 73 55  
Siena (Bracketbuster) 70 53  
at Valparaiso 74 69  
UW-Milwaukee (Horizon Trn) 68 59  
Wright State (Horizon Trn) 70 45  
UTEP (NCAA) 77 59  
Murray State (NCAA) 54 52  
Syracuse (NCAA) 63 59  
Kansas State (NCAA) 63 56  

 

Stats

 

Player Min/G Pts Reb FG% 3pt % FT% Ast Bk Stl
Gordon Hayward 33.1 15.5 8.2 47.4 29.5 82.7 61 28 37
Shelvin Mack 31.0 14.2 3.8 45.5 38.6 73.6 112 5 49
Matt Howard 25.7 11.8 5.3 49.4 27.3 79.2 30 23 21
Willie Veasley 31.1 10.1 4.3 49.8 36.9 64.7 33 9 39
Ronald Nored 29.9 6.0 2.9 41.8 18.2 61.2 133 4 63
Zach Hahn 15.8 5.1 0.9 43.9 42.0 92.9 24 0 13
Shawn Vanzant 14.5 2.8 1.7 32.1 30.4 73.5 43 6 15
Avery Jukes 10.1 2.7 1.2 39.2 37.9 69.4 5 5 5
Garrett Butcher 5.6 0.5 1.0 19.4 11.1 33.3 1 1 2
                   
                   
Team Stats But Opp              
Points 69.4 59.6              
FG% 44.9 41.5              
3PT % 34.5 31.7              
FT% 73.9 68.3              
Rebounds 32.6 29.7              
Turnovers 12.2 13.9              
Steals 7.0 5.3              
Blocks 2.3 3.0              
Off. Rebound % 27.5                
Possessions/G * 65.1                
                   
* Possessions/G estimated and based on this formula        
FG attempts + (.5* FT attempts) + Turnovers – Offensive Rebounds      

 

PiRate Criteria Score

 

Stat Butler
Scoring Margin 9.8
Points 3
FG% Margin 3.40%
Points 0
Rebound Margin 3.2
Points 1
Turnover Margin 1.7
Points 1
R+T * 6.06
Road W-L 15-4
Points 3
Schedule Strength 6.65
   
Sub-total 20.71
   
Butler Gets an extra 2 points for quasi-home court advantage
Total 22.71

 

* R+T is a formula that combines rebounding margin and turnover margin.  It is weighted
to give turnover margin a little more clout and steals even more clout based on the fact that
turnovers, especially steals, produce a higher percentage of easy fast break points than do most rebounds.
         
R+T Formula: R+T= (.2S * 1.2T)+ R
R = Rebounding Margin, T = Turnover Margin, S = Avg. Steals per Game
If Turnover Margin is a negative number, then Steals are dropped from the formula

 

 

 

 

Michigan State

 

Roster

No. Name Pos Ht Wt Yr Status
1 Kalin Lucas G 6-0 190 Jr Injured–Out For Season
2 Raymar Morgan F 6-8 230 Sr Starter
3 Chris Allen G 6-3 205 Jr Key Reserve
10 Delvon Roe F 6-8 230 So Starter
13 Austin Thornton G 6-5 220 So Plays Some in Every Game
15 Durrell Summers G 6-4 205 Jr Starter
20 Mike Kebler G 6-4 205 Jr Plays Infrequently
22 Isaiah Dahlman G 6-6 195 Sr Plays Infrequently
23 Draymond Green F 6-6 235 So Plays as Much as a Starter
25 Jon Crandell F 6-8 230 Sr Seldom Plays
34 Korie Lucious G 5-11 170 So Starter–replaced Lucas
40 Tom Herzog C 7-0 250 Jr Seldom Plays
41 Garrick Sherman C 6-10 235 Fr Plays Some in Every Game
44 Anthony Ianni C 6-9 260 Jr Does Not Play
50 Derrick Nix C 6-8 280 Fr Starter
HC Tom Izzo          
Ast Mark Montgomery          
Ast Dwayne Stephens          
Ast Mike Garland          

 

Record:28-8, 14-4 Big Ten      
Colors: Green & White      
       
Opponent MSU Opp  
Florida Gulf Coast 97 58  
Gonzaga 75 71  
Toledo (Legends Classic) 75 62  
Valparaiso (Legends Classic) 90 60  
Florida (Legends Classic) 74 77  
U Mass (Legends Classic) 106 68  
at North Carolina (ACC/Big Ten) 82 89  
Wofford 72 60  
at Citadel 69 56  
Oakland 88 57  
I P F W 80 58  
at Texas 68 79  
Texas-Arlington 87 68  
at Northwestern 91 70  
Wisconsin 54 47  
at Iowa 71 53  
Minnesota 60 53  
Illinois 73 63  
Iowa 70 63  
at Minnesota 65 64  
at Michigan 57 56  
Northwestern 79 70  
at Wisconsin 49 67  
at Illinois 73 78  
Purdue 64 76  
at Penn State 65 54  
at Indiana 72 58  
Ohio State 67 74  
Penn State 67 65  
Michigan 64 48  
Minnesota (Big Ten Trn) 67 72  
New Mexico State (NCAA) 70 67  
Maryland (NCAA) 85 83  
Northern Iowa (NCAA) 59 52  
Tennessee (NCAA) 70 69  

 

Stats

Player Min/G Pts Reb FG% 3pt % FT% Ast Bk Stl
Kalin Lucas-Inj. 31.1 14.8 1.9 45.3 35.4 77.2 131 2 40
Morgan Raymar 27.3 11.5 6.2 53.5 31.3 68.1 62 24 37
Durrell Summers 25.9 11.2 4.6 45.3 35.9 80.3 31 3 25
Draymond Green 25.4 9.8 7.8 52.7 13.3 68.3 111 32 44
Chris Allen 25.7 8.5 2.9 43.0 39.8 73.3 73 3 16
Delvon Roe 20.6 6.5 5.0 55.9 0.0 66.1 41 34 31
Korie Lucious 22.5 5.4 1.7 33.7 30.8 73.7 114 5 26
Derrick Nix 7.8 2.4 2.1 50.7 0.0 27.1 8 6 7
Garrick Sherman 7.2 1.9 1.6 58.8 0.0 55.6 3 5 4
Austin Thornton 5.7 1.1 1.1 35.0 20.0 100.0 9 0 3
                   
                   
Team Stats MSU Opp              
Points 72.4 64.1              
FG% 47.2 40.8              
3PT % 34.3 33.1              
FT% 68.8 70.9              
Rebounds 38.6 29.9              
Turnovers 13.8 12.5              
Steals 6.6 6.4              
Blocks 3.3 2.6              
Off. Rebound % 39.9                
Possessions/G * 67.2                
                   
* Avg Possessions estimated and based on this formula        
FG attempts + (.5* FT attempts) + Turnovers – Offensive Rebounds      

 

PiRate Criteria Score

 

Stat Michigan St.
Scoring Margin 8.3
Points 3
FG% Margin 6.40%
Points 1
Rebound Margin 8.1
Points 3
Turnover Margin -1.3
Points -2
R+T * 6.54
Road W-L 13-6
Points 2
Schedule Strength 8.74
   
Total 22.28

 

 

Analysis: First things first.  Butler is not a surprise team in the Final Four, or at least not a surprise in that they come from a smaller conference.  UNLV was once a small team from a small conference that made four trips to the Final Four and won the most lopsided Championship Game ever.  Marquette was a small Midwestern school that became a national power in the late 1950’s through the late 1970’s.

Butler is no different than UNLV or Marquette.  The Bulldogs have been as powerful as a Villanova, Ohio State, or Tennessee in recent years.  They have been a regular fixture, like Gonzaga.

Throw in some home-town advantage, and it’s easy to see why the Bulldogs are actually favored in this game.  There is one problem.  They have very little inside depth to match up with the Spartans’ inside game.

Michigan State won’t have their all-star playmaker Kalin Lucas on hand, but the Spartans will be able to cover that weakness up against Butlers’ gamble-free defense.  Lucious has been more than adequate as a play-maker in Lucas’s place, and Green, Allen, and Morgan have become competent runners of the offense as point forwards.

Most Final Four games are decided by guard play, but we see this game being the exception.  We believe the outcome hinges on the performances of the teams’ frontcourts.  Butler has Howard and Hayward and little else, so neither player can afford to get into foul trouble. 

The Spartans, as usual, dominate on the glass in most games.  In addition to Morgan, Green, and Roe, guards Summers and Allen can rebound like forwards.  Izzo has more options in reserve inside. 

The Criteria show this game to be a tossup, and thus a clear-cut favorite cannot be established.  However, all five of us lean toward the Spartans to win based on their superiority inside.

Prediction: Michigan State 63  Butler 56

 

Game Two: 8:47 PM EDT

 

Duke Blue Devils (33-5) vs. West Virginia Mountaineers (31-6)

 

Duke

 

Roster

No. Name Pos Ht Wt Yr Status
2 Nolan Smith G 6-2 185 Jr Starter
3 Seth Curry G 6-1 175 So Does Not Play
5 Mason Plumlee F 6-10 230 Fr Key Reserve
12 Kyle Singler F 6-8 230 Jr Starter
13 Olek Czyz F       Seldom Plays
20 Andre Dawkins G 6-4 190 Fr Key Reserve
21 Miles Plumlee F 6-10 240 So Key Reserve
30 Jon Scheyer G 6-5 190 Sr Starter
34 Ryan Kelly F 6-10 220 Fr Key Reserve
41 Jordan Davidson G 6-1 180 Sr Seldom Plays
42 Lance Thomas F 6-8 225 Sr Starter
51 Steve Johnson F 6-5 210 Jr Seldom Plays
52 Todd Zafirovski F 6-8 240 Fr Does Not Play
53 Casey Peters G 6-4 185 Jr Seldom Plays
55 Brian Zoubek C 7-1 260 Sr Starter
HC Mike Krzyzewski          
Ast Steve Wojciechowski          
Ast Chris Collins          
Ast Nate James          
 Record: 33-5, 13-3 ACC      
Colors: Royal Blue & White      
       
Opponent Duke Opp  
UNC Greensboro 96 62  
Coastal Carolina (Pre NIT) 74 49  
Charlotte (Pre NIT) 101 59  
Radford 104 67  
Arizona State (Pre NIT @NYC) 64 53  
Connecticut (Pre NIT @ NYC) 68 59  
at Wisconsin (ACC/B10) 69 73  
St. John’s 80 71  
Gardner-Webb 113 68  
Gonzaga (at NYC) 76 41  
Long Beach State 84 63  
Penn 114 55  
Clemson 74 53  
Iowa State (at Chicago) 86 65  
at Georgia Tech 67 71  
Boston College 79 59  
Wake Forest 90 70  
at N. C. State 74 88  
at Clemson 60 47  
Florida State 70 56  
at Georgetown 77 89  
Georgia Tech 86 67  
at Boston College 66 63  
at North Carolina 64 54  
Maryland 77 56  
at Miami (FL) 81 74  
Virginia Tech 67 55  
Tulsa 70 52  
At Virginia 67 49  
at Maryland 72 79  
North Carolina 82 50  
Virginia (ACC Tournament) 57 46  
Miami (FL) (ACC Tournament) 77 74  
Georgia Tech (ACC Tournament) 65 61  
Ark. Pine Bluff (NCAA) 73 44  
California (NCAA) 68 53  
Purdue (NCAA) 70 57  
Baylor (NCAA) 78 71  
                   

 

 

Stats

Player Min/G Pts Reb FG% 3pt % FT% Ast Bk Stl
Jon Scheyer 36.7 18.2 3.6 39.5 38.1 88.2 183 8 62
Kyle Singler 35.7 17.6 6.9 40.9 39.1 79.4 89 30 40
Nolan Smith 35.4 17.4 2.8 44.4 39.6 78.3 104 9 45
Brian Zoubek 18.1 5.5 7.6 63.2 0.0 55.4 35 29 27
Miles Plumlee 16.6 5.4 5.1 56.6 100.0 66.1 12 25 18
Lance Thomas 24.9 4.8 4.9 43.2 0.0 74.3 36 8 21
Andre Dawkins 12.9 4.7 1.2 40.0 38.3 73.5 13 2 11
Mason Plumlee 14.7 3.8 3.3 46.2 28.6 54.3 30 29 17
Ryan Kelly 6.6 1.2 1.1 35.6 26.3 66.7 13 14 8
                   
                   
Team Stats Duke Opp              
Points 77.4 61.1              
FG% 43.9 40.2              
3PT % 38.2 27.8              
FT% 76.1 68.5              
Rebounds 39.3 32.8              
Turnovers 11.1 14.4              
Steals 6.7 5.4              
Blocks 4.1 4.0              
Off. Rebound % ^ 40.3                
Possessions/G * 67.5                
                   
^ Offensive Rebound % is based on this formula          
Offensive Rebounds/(Opponents’ Defensive Rebounds + Defensive Dead Ball Rebounds)  
                   
* Avg Possessions estimated and based on this formula        
FG attempts + (.5* FT attempts) + Turnovers – Offensive Rebounds 

 

     

PiRate Criteria Score

Stat Duke
Scoring Margin 16.3
Points 5
FG% Margin 3.70%
Points 0
Rebound Margin 5.9
Points 3
Turnover Margin 3.3
Points 3
R+T * 11.21
Road W-L 16-5
Points 3
Schedule Strength 10.39
   
Total 35.6

 

 
   

West Virginia

 

Roster

No. Name Pos Ht Wt Yr Status
1 Da’Sean Butler F 6-7 230 Sr Starter
2 Cam Thoroughman F 6-7 240 Jr Plays Some in Every Game
3 Devin Ebanks F 6-9 215 So Starter
4 Jonnie West G 6-3 195 Jr Seldom Plays–Son of Jerry West
5 Kevin Jones F 6-8 250 So Starter
12 Kenny Ross G 6-0 175 Fr Does Not Play
15 Bryan Lowther G 6-6 215 Fr Does Not Play
20 Cam Payne G 6-4 225 So Seldom Plays
21 Joe Mazzulla G 6-2 200 Jr Starter in Replace of Bryant
25 Darryl Bryant G 6-2 200 So Broken Bone in Foot Will Try To Play
30 Danny Jennings F 6-8 260 Fr Plays Infrequently
32 Dalton Pepper G 6-5 215 Fr Plays Infrequently
33 Casey Mitchell G 6-4 225 Jr Key Reserve
35 Wellington Smith F 6-7 245 Sr Starter
41 John Flowers F 6-7 215 Jr Key Reserve
42 Deniz Kilicli F 6-9 260 Fr Plays Infrequently

 

Record: 31-6, 13-5 Big East      
Colors: Old Gold & Blue      
       
Opponent WVU Opp  
Loyola of Md 83 60  
Citadel (at Charleston, WV) 69 50  
Long Beach State (Anaheim) 85 62  
Texas A&M (Anaheim) 73 66  
Portland (Anaheim) 84 66  
Duquesne 68 39  
Coppin State 69 43  
at Cleveland State 80 78  
Ole Miss 76 66  
at Seton Hall 90 84 ot
Marquette 63 62  
at Purdue 62 77  
Rutgers 86 52  
at Notre Dame 68 70  
at South Florida 69 50  
Syracuse 71 72  
Marshall (at Charleston, WV) 68 60  
Ohio State 71 65  
at Depaul 62 46  
Louisville 77 74  
Pittsburgh 70 51  
at St. John’s 79 60  
Villanova 75 82  
at Pittsburgh 95 98 3ot
at Providence 88 74  
Seton Hall 75 63  
at Connecticut 62 73  
Cincinnati 74 68  
Georgetown 81 68  
at Villanova 68 66 ot
Cincinnati (Big East Trn) 74 68  
Notre Dame (Big East Trn) 53 51  
Georgetown (Big East Trn) 60 58  
Morgan State (NCAA) 77 50  
Missouri (NCAA) 68 59  
Washington (NCAA) 69 56  
Kentucky (NCAA) 73 66  

 

Stats

Player Min/G Pts Reb FG% 3pt % FT% Ast Bk Stl
Da’Sean Butler 36.0 17.4 6.3 41.6 35.7 78.3 117 15 36
Kevin Jones 32.9 13.7 7.2 52.4 40.6 67.6 40 33 22
Devin Ebanks 34.1 12.0 8.2 45.3 10.0 76.8 82 23 36
Darryl Bryant 24.3 9.3 2.2 34.6 31.5 75.7 108 1 25
Wellington Smith 23.0 6.5 4.1 46.0 35.3 59.5 46 36 27
Casey Mitchell 8.3 3.8 0.9 32.1 30.2 84.2 13 0 10
Deniz Kilicli 6.6 3.4 0.9 50.0 0.0 55.6 1 0 0
Dalton Pepper 7.8 3.2 0.6 37.1 33.3 72.7 16 1 4
John Flowers 14.4 3.0 2.4 43.6 31.8 46.8 45 28 21
Joe Mazzulla 15.6 2.6 1.8 36.7 12.5 57.1 85 1 24
                   
Team Stats WVU Opp              
Points 72.8 63.1              
FG% 43.1 41.3              
3PT % 33.6 31.6              
FT% 70.3 67.8              
Rebounds 38.9 32.3              
Turnovers 11.9 13.6              
Steals 5.7 6.2              
Blocks 4.1 3.0              
Off. Rebound % 38.8                
Possessions/G * 65.8                
                   
* Avg Possessions estimated and based on this formula        
FG attempts + (.5* FT attempts) + Turnovers – Offensive Rebounds      

 

PiRate Criteria Score

Stat WVU
Scoring Margin 9.7
Points 3
FG% Margin 0.18%
Points 0
Rebound Margin 6.9
Points 3
Turnover Margin 2.7
Points 1
R+T * 7.45
Road W-L 19-4
Points 3
Schedule Strength 10.96
   
Total 28.41

 

Analysis: Most fans, prognosticators, and pundits believe this is the real championship game between the two best teams left in the tournament.  We cannot disagree, as the criteria scores show both to be better than the other two teams.  What it should be is a more interesting game.  West Virginia’s 1-3-1 zone defense is a throwback to an earlier time when there was no three-point line.  Its natural weakness is on deep sides, where really good outside shooters can load up on three-point shots against it.  WVU rebounds exceptionally well out of this zone defense, thanks to the size and quickness of the three big men—Butler, Jones, and Ebanks.

Duke’s inside game isn’t as quick as the Mountaineers, but it could be even stronger.  Zoubek, Singler, and the Plumlee brothers know how to throw around their muscle.  This should make the inside game a wash.

We believe the Blue Devils will win this game because of their exceptional backcourt.  Scheyer and Smith will find the seams in the Mountaineer zone and hit crucial three-pointers throughout the game.  Singler will get into the act as well.

West Virginia’s only hope is that Butler (Da’Sean and not the school from Indianapolis) will have one of those terrific games.  He can keep WVU in it, but in the end we believe the Blue Devils will have just a little too many weapons.

Prediction: Duke 73  West Virginia 65

 

Coming Sunday—A look at the big game for all the marbles.

March 28, 2010

Sunday’s Regional Final Games

Sunday’s Regional Finals

Advanced Level Bracketnomics

 

The PiRate NCAA Tournament Criteria Formula worked like a charm in Friday night’s regional semifinal games.  Let’s see how it applies to Sunday’s regional final games.

South Regional

 

#1 Duke (30.48) vs. #3 Baylor (26.04)

We have been split whether to issue Baylor a partial home court advantage for this game, but we have decided to leave it as a 100% neutral game.  Baylor will have more fans for sure, but it won’t be like it would be if Duke were playing Kentucky in Nashville or Indianapolis.  The advantage for Baylor will be negligible.

Both teams in this game have crucial assets that prove to be winning tickets in games of this magnitude.  For Baylor, the Bears hit over 48% of their field goal attempts and give up less than 38%.  They have a scoring margin in double digits, and they control the boards by more than five per game.

For Duke, the Blue Devils outscore their opposition by 16 points per game and outrebound them by almost six per game.  The Dukies enjoy one of the best R+T* ratings in the nation, coming in at 11.64.  This number is so high because not only is their rebounding margin great, their turnover margin is also terrific at +3.7.  When a team consistently wins the battle of the boards and the turnover margin by healthy amounts, they have to really throw up bricks and give up easy layups to lose.

The two teams’ strengths of schedule are a wash—there isn’t even a half-point’s difference.  This game should be a see-saw affair with neither team pulling away until maybe the final minutes.  We’re going to stick with our pre-tournament favorite to win it all and take Coach K and company to earn the trip to Indianapolis.

Prediction: Duke 70  Baylor 63

 

Midwest Regional

 

#5 Michigan State (20.92) vs. #6 Tennessee (21.16)

Tennessee head coach Bruce Pearl faced a serious dilemma when he dismissed star forward Tyler Smith from the squad at the end of December.  His team also played a couple weeks without the services of three other players.  Yet, the Volunteers upset undefeated and number one Kansas in their next game.  While fans and media were expecting the orange and white to crumble to a losing SEC record, Pearl changed their style of play to a more conservative approach and guided the Vols to double-digit wins in the conference.  This marks the farthest Tennessee has ever advanced in the Big Dance.

Michigan State under Coach Tom Izzo has made a habit of making it this far and farther.  The Spartans made it to the Championship Game last year.  Now, Izzo is facing the same dilemma Pearl faced in December.  He must get by without the services of his top player—Kalin Lucas.

The Spartans edged Northern Iowa in their first game without Lucas, but they face a team in the regional finals that will definitely exploit Lucas’s loss.  Tennessee can pressure the perimeter in the frontcourt and force MSU to work the shot clock to its final seconds.  The Spartans will have to force up some shots against the Volunteers’ defense.

Michigan State can still win this game if the Spartans shoot 38%.  They will definitely win the rebounding battle in this game.  However, Tennessee will force more turnovers and pick up a couple of cheapie baskets.  It is more likely that the Vols will enjoy some type of scoring spurt in this game.  Since it is most likely to be a limited possession game, just one spurt of eight to 10 points will be enough to advance Pearl’s club to the school’s first Final Four bid in history.

Prediction: Tennessee 64  Michigan State 59

 

* For an explanation of R+T as well as the rest of the PiRate Criteria, go to: https://piratings.wordpress.com/2010/03/14/bracketnomics-505-how-to-pick-your-ncaa-tournament-brackets/

 

 

Coming Thursday: An in-depth look at the Final Four with expanded coverage.  We will have a one-stop look at the four teams, including rosters, statistics, schedules, the entire PiRate formulas, and of course, our predictions.

April 5, 2009

A PiRate Look At The 2009 NCAA Basketball Championship Game

A PiRate Look At The NCAA Final Four

The National Championship Game

 April 6, 2009

Ford Field: Detroit

Tip Time: 9:21 PM EDT

 

Michigan State (31-6) vs. North Carolina (33-4)

 

Note: Team info courtesy of the two schools’ official athletic websites

 

Michigan State Spartans

 

No. Name Ht. Wt. Pos. Year Hometown/High School

00

Ibok, Idong 6-11 260 C RS SR Lagos, Nigeria/Montverde (Fla.) Academy

1

Lucas, Kalin 6-0 180 G SO Sterling Heights, Mich./Orchard Lake St. Mary’s

2

Morgan, Raymar 6-8 225 F JR Canton, Ohio/McKinley

3

Allen, Chris 6-3 205 G SO Lawrenceville, Ga./Meadowcreek

5

Walton, Travis 6-2 190 G SR Lima, Ohio/Lima Senior

10

Roe, Delvon 6-8 225 F FR Lakewood, Ohio/St. Edward

13

Thornton, Austin 6-5 210 G RS FR Sand Lake, Mich./Cedar Springs

14

Suton, Goran 6-10 245 C RS SR Lansing, Mich./Everett

15

Summers, Durrell 6-4 195 G SO Detroit, Mich./Redford Covenant Christian

20

Kebler, Mike 6-4 200 G SO Okemos, Mich./Okemos

22

Dahlman, Isaiah 6-6 200 G JR Braham, Minn./Braham Area

23

Green, Draymond 6-6 235 F FR Saginaw, Mich./Saginaw

25

Crandell, Jon 6-8 225 F JR Rochester, Mich./Rochester Adams

34

Lucious, Korie 5-11 170 G FR Milwaukee, Wis./Pius XI

40

Herzog, Tom 7-0 240 C RS SO Flint, Mich./Powers

41

Gray, Marquise 6-8 235 F RS SR Flint, Mich./Beecher

 

   
Coaches  
   
Tom Izzo – Head Coach
Mark Montgomery – Associate Head Coach
Dwayne Stephens – Assistant Coach
Mike Garland – Assistant Coach
Jordan Ott – Video Coordinator
Richard Bader – Director of Basketball Operations

 

 
                                     

                               2008-09 Michigan State Basketball

                  Michigan State Combined Team Statistics (as of Apr 05, 2009)

                                           All games

 

 

 RECORD:                OVERALL      HOME        AWAY       NEUTRAL

 ALL GAMES………..   (31-6)      (12-2)      (9-1)       (10-3)

 CONFERENCE……….   (15-3)      (7-2)       (8-1)       (0-0)

 NON-CONFERENCE……   (16-3)      (5-0)       (1-0)       (10-3)

 

 

   DATE            OPPONENT                       W/L    SCORE  ATTEND

   ————    ——————–           —    —–  ——

   11/16/08        IDAHO                          W     100-62   14759

   11/19/08     at IPFW                           W      70-59    6704

   11/27/08     vs Maryland                         L    62-80    4464

   11/28/08     vs Oklahoma State                 W      94-79    4658

   11/30/08     vs Wichita State                  W      65-57    3768

   12/03/08     vs North Carolina                   L    63-98   25267

   12/07/08        BRADLEY                        W      75-59   14759

   12/13/08        ALCORN STATE                   W     118-60   14759

   12/17/08        THE CITADEL                    W      79-65   14759

   12/20/08     vs Texas                          W      67-63   17074

  @12/27/08     vs Oakland University             W      82-66   15361

  *12/31/08     at Minnesota                      W      70-58   14625

  *1/3/09       at Northwestern                   W      77-66    8117

  *01/06/09        OHIO STATE                     W      67-58   14759

   01/10/09        KANSAS                         W      75-62   14759

  *1/14/09      at Penn State                     W      78-73   10270

  *1/17/09         ILLINOIS                       W      63-57   14759

  *1/21/09         NORTHWESTERN                     L    63-70   14759

  *01/25/09     at Ohio State                     W      78-67   18767

  *01/29/09     at Iowa Hawkeyes                  W      71-56   13640

  *02/01/09        PENN STATE                       L    68-72   14759

  *2/4/09          MINNESOTA                      W      76-47   14759

  *2/7/09          INDIANA                        W      75-47   14759

  *02/10/09     at Michigan                       W      54-42   13751

  *02/17/09     at Purdue                           L    54-72   14123

  *02/22/09        WISCONSIN                      W      61-50   14759

  *02/25/09        IOWA HAWKEYES                  W      62-54   14759

  *03/01/09     at Illinois                       W      74-66   16618

  *3-3-09       at Indiana                        W      64-59   15006

  *03/08/09        PURDUE                         W      62-51   14759

   3-13-09      vs Minnesota                      W      64-56   13023

   3-14-09      vs Ohio State                       L    70-82   15728

   03/20/09     vs Robert Morris                  W      77-62   12814

   03/22/09     vs Southern Cal                   W      74-69   14279

   3/27/09      vs Kansas                         W      67-62   33780

   3/29/09      vs Louisville                     W      64-52   36084

   4/4/09       vs Connecticut                    W      82-73   72456

 * = Conference game

 

 

 

 ## SUMMARY              GP-GS   Min   FG%  3PT%   FT%  R/G  A/G STL BLK PTS/G

 —————————————————————————–

 01 Lucas, Kalin…….. 37-36  31.8  .397  .394  .810  2.2  4.6  39   6  14.7

 02 Morgan, Raymar…… 34-25  22.6  .526  .238  .654  5.4  1.2  23   7  10.4

 14 Suton, Goran…….. 31-28  26.6  .513  .409  .848  8.3  1.6  36  14  10.2

 03 Allen, Chris…….. 37-5   19.1  .371  .325  .800  2.3  1.3  14   0   8.5

 15 Summers, Durrell…. 37-13  21.4  .436  .387  .719  3.4  0.8  25  12   8.5

 10 Roe, Delvon……… 37-30  18.0  .563  .000  .459  5.1  0.9  16  28   5.7

 05 Walton, Travis…… 37-36  27.9  .415  .600  .578  2.3  3.4  56   1   5.2

 41 Gray, Marquise…… 37-5    9.7  .584  .000  .674  2.9  0.3   4  12   3.2

 23 Green, Draymond….. 36-0   11.4  .544  .000  .617  3.2  0.9  20   9   3.2

 34 Lucious, Korie…… 37-1    8.9  .376  .351  .667  0.9  1.3  10   2   3.1

 13 Thornton, Austin…. 26-0    3.7  .375  .235  .750  0.7  0.3   4   0   1.2

 00 Ibok, Idong……… 27-5    6.1  .375  .000  .667  0.9  0.2   0   7   0.4

 40 Herzog, Tom……… 15-1    2.1  .600  .000  .571  0.7  0.1   0   4   0.7

 22 Dahlman, Isaiah….. 15-0    1.8  .500  .333  .250  0.6  0.0   0   0   0.7

 25 Crandell, Jon…….  9-0    1.1 1.000  .000 1.000  0.0  0.0   0   0   0.4

 20 Kebler, Mike……..  8-0    1.3  .500  .000 1.000  0.3  0.1   0   0   0.5

 TM Team……………. 37-0    0.0  .000  .000  .000  3.2  0.0   0   0   0.0

    Total…………… 37           .452  .357  .697 38.9 16.2 247 102  72.0

    Opponents……….. 37           .414  .316  .696 29.5 11.5 220 131  63.0

 

 SCORING              GP   FG-FGA   FG%  3FG-FGA  3PT%   FT-FTA   FT%   PTS PTS/G

 ——————————————————————————–

 Lucas, Kalin…….. 37  169-426  .397   41-104  .394  166-205  .810   545 14.7

 Morgan, Raymar…… 34  131-249  .526    5-21   .238   87-133  .654   354 10.4

 Suton, Goran…….. 31  116-226  .513   18-44   .409   67-79   .848   317 10.2

 Allen, Chris…….. 37  104-280  .371   52-160  .325   56-70   .800   316  8.5

 Summers, Durrell…. 37  112-257  .436   43-111  .387   46-64   .719   313  8.5

 Roe, Delvon……… 37   80-142  .563    0-0    .000   51-111  .459   211  5.7

 Walton, Travis…… 37   81-195  .415    3-5    .600   26-45   .578   191  5.2

 Gray, Marquise…… 37   45-77   .584    0-0    .000   29-43   .674   119  3.2

 Green, Draymond….. 36   43-79   .544    0-1    .000   29-47   .617   115  3.2

 Lucious, Korie…… 37   38-101  .376   27-77   .351   12-18   .667   115  3.1

 Thornton, Austin…. 26    9-24   .375    4-17   .235    9-12   .750    31  1.2

 Ibok, Idong……… 27    3-8    .375    0-0    .000    4-6    .667    10  0.4

 Herzog, Tom……… 15    3-5    .600    0-0    .000    4-7    .571    10  0.7

 Dahlman, Isaiah….. 15    4-8    .500    1-3    .333    1-4    .250    10  0.7

 Crandell, Jon…….  9    1-1   1.000    0-0    .000    2-2   1.000     4  0.4

 Kebler, Mike……..  8    1-2    .500    0-1    .000    2-2   1.000     4  0.5

 Total…………… 37  940-2080 .452  194-544  .357  591-848  .697  2665 72.0

 Opponents……….. 37  811-1957 .414  224-708  .316  485-697  .696  2331 63.0

 

                                   REBOUNDS

 TOTALS               GP   MIN  OFF  DEF  TOT   PF  FO    A   TO  A/TO  HI

 ————————————————————————-

 Lucas, Kalin…….. 37  1178   26   54   80   47   0  169   78   2.2  24

 Morgan, Raymar…… 34   768   62  121  183   85   2   41   61   0.7  29

 Suton, Goran…….. 31   824   91  167  258   78   1   50   55   0.9  20

 Allen, Chris…….. 37   706   27   57   84   62   0   47   50   0.9  21

 Summers, Durrell…. 37   791   49   75  124   57   0   28   53   0.5  26

 Roe, Delvon……… 37   665   76  113  189   80   1   35   41   0.9  16

 Walton, Travis…… 37  1031   24   60   84   94   1  124   48   2.6  18

 Gray, Marquise…… 37   358   38   69  107   57   0   12   35   0.3  12

 Green, Draymond….. 36   410   37   78  115   63   2   31   22   1.4  16

 Lucious, Korie…… 37   330    4   28   32   36   1   47   40   1.2  16

 Thornton, Austin…. 26    97    4   14   18   14   0    7    6   1.2   9

 Ibok, Idong……… 27   164    9   15   24   28   0    5   13   0.4   2

 Herzog, Tom……… 15    31    3    8   11    3   0    1    0  99.0   5

 Dahlman, Isaiah….. 15    27    3    6    9    1   0    0    0   0.0   6

 Crandell, Jon…….  9    10    0    0    0    0   0    0    0   0.0   2

 Kebler, Mike……..  8    10    1    1    2    0   0    1    0  99.0   2

 Total…………… 37  7400  520  920 1440  706   8  598  511   1.2 118

 Opponents……….. 37  7400  342  751 1093  734   –  427  508   0.8  98

 

 

 TEAM STATISTICS                   MSU          OPP

 ————————————————–

 SCORING……………..         2665         2331

   Points per game…….         72.0         63.0

   Scoring margin……..         +9.0            –

 FIELD GOALS-ATT………     940-2080     811-1957

   Field goal pct……..         .452         .414

 3 POINT FG-ATT……….      194-544      224-708

   3-point FG pct……..         .357         .316

   3-pt FG made per game.          5.2          6.1

 FREE THROWS-ATT………      591-848      485-697

   Free throw pct……..         .697         .696

   F-Throws made per game         16.0         13.1

 REBOUNDS…………….         1440         1093

   Rebounds per game…..         38.9         29.5

   Rebounding margin…..         +9.4            –

 ASSISTS……………..          598          427

   Assists per game……         16.2         11.5

 TURNOVERS……………          511          508

   Turnovers per game….         13.8         13.7

   Turnover margin…….         -0.1            –

   Assist/turnover ratio.          1.2          0.8

 STEALS………………          247          220

   Steals per game…….          6.7          5.9

 BLOCKS………………          102          131

   Blocks per game…….          2.8          3.5

 ATTENDANCE…………..       206626       400377

   Home games-Avg/Game…     14-14759     10-13162

   Neutral site-Avg/Game.            –     13-20674

 

 SCORE BY PERIODS:           1st  2nd    Total

 ————————-  —- —-     —-

 Michigan State………..  1290 1375  –  2665

 Opponents…………….  1096 1235  –  2331

 

 

 

North Carolina Tar Heels

 

No. Name Ht. Wt. Pos. Yr. Hometown (High School)

1

Marcus Ginyard 6-5 220 G/F SR Alexandria, Va. (Bishop O’Connell)

2

Marc Campbell 5-11 175 G JR Wilmington, N.C. (Ravenscroft)

4

Bobby Frasor 6-3 210 G SR Blue Island, Ill. (Brother Rice)

5

Ty Lawson 5-11 195 G JR Clinton, Md. (Oak Hill Academy (Va.))

11

Larry Drew II 6-1 180 G FR Encino, Calif. (Woodland Hills Taft)

13

Will Graves 6-6 245 F/G SO Greensboro, N.C. (Dudley)

14

Danny Green 6-6 210 F/G SR North Babylon, N.Y. (St. Mary’s)

15

J.B. Tanner 6-0 185 G SR Hendersonville, N.C. (West Henderson)

21

Deon Thompson 6-8 245 F JR Torrance, Calif. (Torrance)

22

Wayne Ellington 6-4 200 G JR Wynnewood, Pa. (The Episcopal Academy)

24

Justin Watts 6-4 205 G FR Durham, N.C. (Jordan)

30

Jack Wooten 6-2 190 G SR Burlington, N.C. (Williams)

32

Ed Davis 6-10 215 F FR Richmond, Va. (Benedictine)

35

Patrick Moody 6-4 195 F SR Asheville, N.C. (T.C. Roberson)

40

Mike Copeland 6-7 235 F SR Winston-Salem, N.C. (R.J. Reynolds)

44

Tyler Zeller 7-0 220 F FR Washington, Ind. (Washington)

50

Tyler Hansbrough 6-9 250 F SR Poplar Bluff, Mo. (Poplar Bluff)

 

 
Coaching Staff
 
Roy Williams – Head Coach
Joe Holladay – Assistant Coach
Steve Robinson – Assistant Coach
C.B. McGrath – Assistant Coach
Jerod Haase – Director of Basketball Operations
Chris Hirth – Head Athletic Trainer
Eric Hoots – Video Coordinator
Jonas Sahratian – Strength & Conditioning Coordinator

 

 

North Carolina Season Schedule/Results & Leaders (as of Apr 05, 2009)

 

North Carolina Combined Team Statistics (as of Apr 05, 2009)

                                           All games

 

 

 RECORD:                OVERALL      HOME        AWAY       NEUTRAL

 ALL GAMES………..   (33-4)      (14-1)      (8-2)       (11-1)

 CONFERENCE……….   (13-3)      (7-1)       (6-2)       (0-0)

 NON-CONFERENCE……   (20-1)      (7-0)       (2-0)       (11-1)

 

 

   DATE            OPPONENT                       W/L    SCORE  ATTEND

   ————    ——————–           —    —–  ——

   11/15/08        PENN                           W      86-71   19623

   11/18/08        KENTUCKY                       W      77-58   21538

   11/21/08     at UC Santa Barbara               W      84-67    6000

   11-24-08     vs CHAMINADE                      W     115-70    2500

   11-25-08     vs Oregon                         W      98-69    2500

   11-26-08     vs Notre Dame                     W     102-87    2500

   11/30/08        UNC ASHEVILLE                  W     116-48   18054

   12/03/08     vs Michigan State                 W      98-63   25267

   12/13/08        ORAL ROBERTS                   W     100-84   21269

   12/18/08        EVANSVILLE                     W      91-73   21291

   12/20/08     vs VALPO                          W      85-63   10645

   12/28/08        RUTGERS                        W      97-75   21750

   12-31-08     at Nevada                         W      84-61   10526

  *01/04/09        BOSTON COLLEGE                   L    78-85   21750

   01/07/09        COLLEGE OF CHARLESTON          W     108-70   20543

  *01/11/09     at Wake Forest                      L    89-92   14714

  *01/15/09     at Virginia                       W      83-61   13811

  *01/17/09        MIAMI                          W      82-65   21750

  *01/21/09        CLEMSON                        W      94-70   21750

  *01/28/09     at Florida State                  W      80-77   11333

  *01/31/09     at NC State                       W      93-76   19700

  *02/03/09        MARYLAND                       W     108-91   20863

  *02/07/09        VIRGINIA                       W      76-61   20879

  *2/11/09      at Duke                           W     101-87    9314

  *2/15/09      at Miami                          W      69-65    7200

  *02/18/09        NC STATE                       W      89-80   21750

  *02/21/09     at Maryland                         LOT  85-88   17950

  *02/28/09        GEORGIA TECH                   W     104-74   20959

  *03/04/09     at Virginia Tech                  W      86-78    9847

  *03/08/09        DUKE                           W      79-71   21750

   3/13/09      vs Virginia Tech                  W      79-76   26352

   3/14/09      vs Florida State                    L    70-73   26352

   03/19/09     vs Radford                        W     101-58   20226

   03/21/09     vs LSU                            W      84-70   22479

   3/27/09      vs Gonzaga                        W      98-77   17103

   3/29/09      vs Oklahoma                       W      72-60   17025

   4/4/09       vs Villanova                      W      83-69   72456

 

 

 

 ## SUMMARY              GP-GS   Min   FG%  3PT%   FT%  R/G  A/G STL BLK PTS/G

 —————————————————————————–

 50 Tyler Hansbrough…. 33-33  30.2  .517  .429  .850  8.2  1.0  42  12  20.8

 05 Lawson, Ty………. 34-34  29.7  .539  .486  .795  2.9  6.6  67   5  16.5

 22 Wayne Ellington….. 37-36  30.3  .480  .408  .773  4.9  2.7  36   6  15.8

 14 Danny Green……… 37-37  27.5  .470  .414  .852  4.7  2.7  66  51  13.3

 21 Deon Thompson……. 37-36  24.9  .495  .000  .642  5.8  0.7  35  40  10.6

 32 Ed Davis………… 37-2   19.0  .511  .000  .587  6.5  0.6  14  65   6.5

 13 Will Graves……… 20-0   11.2  .437  .278  .889  2.6  0.8   7   2   4.0

 44 Tyler Zeller…….. 14-2    8.3  .472  .000  .800  2.1  0.2   3   3   3.3

 04 Frasor, Bobby……. 37-4   17.3  .330  .278  .462  2.0  1.4  22   5   2.6

 11 Larry Drew II……. 37-0    9.7  .357  .231  .412  1.1  2.0  15   1   1.4

 01 Ginyard, Marcus…..  3-0   12.3  .250  .000  .500  2.7  1.3   2   0   1.3

 15 J.B. Tanner……… 20-0    2.2  .421  .357  .333  0.4  0.1   1   0   1.2

 35 Patrick Moody……. 20-0    2.2  .583  .000  .615  0.8  0.0   2   3   1.1

 40 Mike Copeland……. 16-1    2.6  .250  .000 1.000  0.8  0.1   0   0   0.8

 24 Justin Watts…….. 26-0    3.2  .226  .000  .429  0.7  0.2   2   3   0.7

 30 Jack Wooten……… 19-0    1.9  .364  .200  .250  0.3  0.1   0   0   0.5

 02 Campbell, Marc…… 19-0    1.9  .500  .000 1.000  0.2  0.5   2   0   0.2

 TM TEAM……………. 37-0    0.0  .000  .000  .000  3.1  0.0   0   0   0.0

    Total…………… 37           .481  .387  .754 42.2 18.2 316 196  89.8

    Opponents……….. 37           .411  .338  .692 35.5 13.6 265 162  72.0

 

 SCORING              GP   FG-FGA   FG%  3FG-FGA  3PT%   FT-FTA   FT%   PTS PTS/G

 ——————————————————————————–

 Tyler Hansbrough…. 33  217-420  .517    9-21   .429  243-286  .850   686 20.8

 Lawson, Ty………. 34  179-332  .539   51-105  .486  151-190  .795   560 16.5

 Wayne Ellington….. 37  208-433  .480   82-201  .408   85-110  .773   583 15.8

 Danny Green……… 37  182-387  .470   75-181  .414   52-61   .852   491 13.3

 Deon Thompson……. 37  161-325  .495    0-0    .000   70-109  .642   392 10.6

 Ed Davis………… 37   94-184  .511    0-0    .000   54-92   .587   242  6.5

 Will Graves……… 20   31-71   .437   10-36   .278    8-9    .889    80  4.0

 Tyler Zeller…….. 14   17-36   .472    0-0    .000   12-15   .800    46  3.3

 Frasor, Bobby……. 37   36-109  .330   20-72   .278    6-13   .462    98  2.6

 Larry Drew II……. 37   20-56   .357    6-26   .231    7-17   .412    53  1.4

 Ginyard, Marcus…..  3    1-4    .250    0-0    .000    2-4    .500     4  1.3

 J.B. Tanner……… 20    8-19   .421    5-14   .357    2-6    .333    23  1.2

 Patrick Moody……. 20    7-12   .583    0-0    .000    8-13   .615    22  1.1

 Mike Copeland……. 16    4-16   .250    0-2    .000    5-5   1.000    13  0.8

 Justin Watts…….. 26    7-31   .226    0-6    .000    3-7    .429    17  0.7

 Jack Wooten……… 19    4-11   .364    1-5    .200    1-4    .250    10  0.5

 Campbell, Marc…… 19    1-2    .500    0-1    .000    2-2   1.000     4  0.2

 Total…………… 37 1177-2448 .481  259-670  .387  711-943  .754  3324 89.8

 Opponents……….. 37  991-2413 .411  267-791  .338  414-598  .692  2663 72.0

 

                                   REBOUNDS

 TOTALS               GP   MIN  OFF  DEF  TOT   PF  FO    A   TO  A/TO  HI

 ————————————————————————-

 Tyler Hansbrough…. 33   995  102  167  269   74   1   32   61   0.5  34

 Lawson, Ty………. 34  1011   23   77  100   59   0  224   65   3.4  25

 Wayne Ellington….. 37  1120   55  127  182   55   0  101   62   1.6  34

 Danny Green……… 37  1016   68  107  175   79   2  100   61   1.6  26

 Deon Thompson……. 37   920   70  143  213   81   1   26   46   0.6  22

 Ed Davis………… 37   702   81  161  242   70   1   22   40   0.6  15

 Will Graves……… 20   224   22   29   51   32   0   15   23   0.7  10

 Tyler Zeller…….. 14   116   11   18   29   19   0    3    8   0.4  18

 Frasor, Bobby……. 37   639   22   52   74   49   0   53   26   2.0   9

 Larry Drew II……. 37   360    5   36   41   36   0   74   45   1.6   5

 Ginyard, Marcus…..  3    37    6    2    8    5   0    4    3   1.3   3

 J.B. Tanner……… 20    44    2    5    7    4   0    1    1   1.0   9

 Patrick Moody……. 20    43    4   11   15    7   0    0    3   0.0   6

 Mike Copeland……. 16    41    4    9   13    8   0    1    2   0.5   5

 Justin Watts…….. 26    84    6   13   19    6   0    5    9   0.6   9

 Jack Wooten……… 19    37    0    5    5    1   0    2    2   1.0   4

 Campbell, Marc…… 19    36    1    3    4    2   0    9    7   1.3   2

 Total…………… 37  7425  545 1017 1562  587   5  672  465   1.4 116

 Opponents……….. 37  7425  481  834 1315  757   –  505  584   0.9  92

 

 

 TEAM STATISTICS                    NC          OPP

 ————————————————–

 SCORING……………..         3324         2663

   Points per game…….         89.8         72.0

   Scoring margin……..        +17.9            –

 FIELD GOALS-ATT………    1177-2448     991-2413

   Field goal pct……..         .481         .411

 3 POINT FG-ATT……….      259-670      267-791

   3-point FG pct……..         .387         .338

   3-pt FG made per game.          7.0          7.2

 FREE THROWS-ATT………      711-943      414-598

   Free throw pct……..         .754         .692

   F-Throws made per game         19.2         11.2

 REBOUNDS…………….         1562         1315

   Rebounds per game…..         42.2         35.5

   Rebounding margin…..         +6.7            –

 ASSISTS……………..          672          505

   Assists per game……         18.2         13.6

 TURNOVERS……………          465          584

   Turnovers per game….         12.6         15.8

   Turnover margin…….         +3.2            –

   Assist/turnover ratio.          1.4          0.9

 STEALS………………          316          265

   Steals per game…….          8.5          7.2

 BLOCKS………………          196          162

   Blocks per game…….          5.3          4.4

 ATTENDANCE…………..       315519       365800

   Home games-Avg/Game…     15-21035     10-12040

   Neutral site-Avg/Game.            –     12-20450

 

 SCORE BY PERIODS:           1st  2nd   OT    Total

 ————————-  —- —- —-     —-

 North Carolina………..  1646 1669    9  –  3324

 Opponents…………….  1259 1392   12  –  2663

 

 

Player Matchups

Point Guard

Michigan State: Kalin Lucas

North Carolina: Ty Lawson

 

Lawson is the best point guard in the nation, but Lucas isn’t totally outmanned in this matchup.  Lucas is probably one of the top five point guards in the nation.

 

Lawson’s advantage here is small.  Expect a great matchup at this most important position.

 

Shooting Guard

Michigan State: Travis Walton

North Carolina: Wayne Ellington

 

Walton is the best defensive player from the Big 10, but stopping Ellington will not beat North Carolina.  Ellington may be held under 10 points, but North Carolina can win nine times out of ten when he scores in single digits.

 

We’ll give another slight advantage to North Carolina

 

Small Forward

Michigan State: Raymar Morgan

North Carolina: Danny Green

 

If Morgan plays as well as he did Saturday, then he should outpace Green.  Green is at a size disadvantage against Morgan, and Morgan has the speed and quickness to stay with Green all night.

 

We give Michigan State the advantage.

 

Power Forward

Michigan State: Delvin Roe

North Carolina: Deon Thompson

 

This will be an interesting matchup.  Thompson has the better moves around the basket, but Roe has the better power game.  It will be a study in contrasts. 

 

If North Carolina gets their offense running and gunning, Roe will have a tough time contributing on the defensive board.

 

An ever so slight advantage goes to Michigan State here.

 

Center

Michigan State: Goran Suton

North Carolina: Tyler Hansbrough

 

There haven’t been many classic matchups between two future NBA centers and major contributors in the NCAA Championship Game’s last 30 years (such as Rick Robey vs. Mike Gmisnki in 1978, Sam Perkins vs. Patrick Ewing in 1982, and Ewing vs. Akeem Olajuwon in 1984).  This one looks like one of those few exceptions.

 

We believe that Suton will slow Hansbrough inside and force him to take several shots from outside his comfort zone.  Meanwhile, Suton will try to force Hansbrough to guard some from outside the low post area.

 

Hansbrough’s advantage is not that large.  Suton missed the first game between these two teams, so his presence will mean a major turnaround from the earlier game.

 

Bench Play

Michigan State

Chris Allen

Durrell Summers

Marquise Gray

Draymond Green

 

North Carolina

Ed Davis

Bobby Frasor

Larry Drew, Jr.

 

If Davis and Frasor have good games, this could be enough to throw the game in North Carolina’s favor.  It’s not that these two guys will have to dominate to tilt the game, it’s that they will allow the Tar Heels to either make a run or play more consistently

 

Michigan State has a numbers’ advantage, but with the extra length of TV timeouts, this game will not require subs entering games.

 

A small advantage goes to North Carolina

 

PiRate Criteria see articles from the week of March 16-18 for explanation of this statistical formula

 

North Carolina had the second best criteria score of the 65 teams in the field, so the Tar Heels were selected to make it all the way to the last game.

 

Michigan State did not qualify as a superior team, but the Spartans have home court advantage of about three points.  Combined with a criteria score of seven, it gives them an opportunity to be there at the end with a chance to win.

 

The strengths of schedule are nearly equal, as Michigan State gets one additional point here.

 

Prediction

We believe this game will be close and the lead will never be all that large for either team.  Michigan State will desire to make this a lower possession game, while North Carolina will try to make it a game of race horse basketball.  The Spartans will crash the offensive glass, and that will limit the Tar Heels’ fast breaking opportunities.

 

When all is said and done, North Carolina has too many weapons to ever pick against them. 

 

North Carolina 74 Michigan State 69

April 4, 2009

A PiRate Look At The NCAA Final Four: Semifinal Round–April 4, 2009

A PiRate Look At The NCAA Final Four

The Semifinals

 April 4, 2009

 

Ford Field: Detroit

 

Many basketball purists believe that the NCAA Tournament Semifinal is the top ticket in all of sports.  While we would argue that any ticket to a Green Bay Packers game would top it, this is the only time the top four teams in any sport meet on the same court back-to-back.

 

At Detroit’s Ford Field Saturday, there’s a good chance that the teams in the home uniforms will win more games in four hours than the regular tenant of the building won all season.  We know that’s a stab at the division rival Lions, but we had to do it.

 

For what it’s worth, our record through the first four rounds is 45-15.

 

Here is a guide for the two semifinal games.  We hope you have fun.

 

Note: Team info courtesy of the four schools’ official athletic websites

 

Game 1

Connecticut Huskies (31-4) vs. Michigan State Spartans (30-6)

Tip Time: 6:07 PM EDT

 

Rosters

 

Connecticut Huskies

 

NO NAME HT/WT POSITION YR/CLASS HOMETOWN

4

Adrien, Jeff 6-7/243 Forward SR Brookline, Mass.

24

Austrie, Craig 6-3/176 Guard SR Stamford, Conn.

55

Bailey, Kyle 6-3/170 Guard SO Lancaster, N.H.

2

Beverly, Donnell 6-4/190 Guard SO Hawthorne, Calif.

10

Bird, Johnnie 6-0/165 Guard SR Fort Bragg, N.C.

11

Dyson, Jerome 6-3/180 Guard JR Rockville, Md.

33

Edwards, Gavin 6-9/230 Forward/Center JR Gilbert, Ariz.

30

Haralson, Scottie 6-4/215 Guard FR Jackson, Miss.

13

Hornat, Alex 6-5/205 Forward JR South Windsor, Conn.

45

Lindner, John 6-5/265 Forward SR Cheshire, Conn.

32

Mandeldove, Jonathan 6-11/220 Center JR Stone Mountain, Ga.

35

Okwandu, Charles 7-1/255 Center SO Lagos, Nigeria

12

Price, A.J. 6-2/190 Guard SR Amityville, N.Y.

21

Robinson, Stanley 6-9/220 Forward SO Birmingham, Ala.

34

Thabeet, Hasheem 7-3/265 Center JR Dar Es Salaam, Tanzania

40

Veronick, Jim 6-8/200 Forward SR Durham, Conn.

15

Walker, Kemba 6-1/172 Guard FR Bronx, N.Y.

 

 
Coaches
 
Jim Calhoun – Head Coach
George Blaney – Assistant Coach
Andre LaFleur – Assistant Coach
Patrick Sellers – Assistant Coach
Beau Archibald – Director of Operations

 

 

 

Michigan State Spartans

 

No. Name Ht. Wt. Pos. Year Hometown/High School

00

Ibok, Idong 6-11 260 C RS SR Lagos, Nigeria/Montverde (Fla.) Academy

1

Lucas, Kalin 6-0 180 G SO Sterling Heights, Mich./Orchard Lake St. Mary’s

2

Morgan, Raymar 6-8 225 F JR Canton, Ohio/McKinley

3

Allen, Chris 6-3 205 G SO Lawrenceville, Ga./Meadowcreek

5

Walton, Travis 6-2 190 G SR Lima, Ohio/Lima Senior

10

Roe, Delvon 6-8 225 F FR Lakewood, Ohio/St. Edward

13

Thornton, Austin 6-5 210 G RS FR Sand Lake, Mich./Cedar Springs

14

Suton, Goran 6-10 245 C RS SR Lansing, Mich./Everett

15

Summers, Durrell 6-4 195 G SO Detroit, Mich./Redford Covenant Christian

20

Kebler, Mike 6-4 200 G SO Okemos, Mich./Okemos

22

Dahlman, Isaiah 6-6 200 G JR Braham, Minn./Braham Area

23

Green, Draymond 6-6 235 F FR Saginaw, Mich./Saginaw

25

Crandell, Jon 6-8 225 F JR Rochester, Mich./Rochester Adams

34

Lucious, Korie 5-11 170 G FR Milwaukee, Wis./Pius XI

40

Herzog, Tom 7-0 240 C RS SO Flint, Mich./Powers

41

Gray, Marquise 6-8 235 F RS SR Flint, Mich./Beecher

 

 
Coaches
 
Tom Izzo – Head Coach
Mark Montgomery – Associate Head Coach
Dwayne Stephens – Assistant Coach
Mike Garland – Assistant Coach
Jordan Ott – Video Coordinator
Richard Bader – Director of Basketball Operations
 

 

 

 

 

Player Matchups

 

Ppg=points per game, rpg=rebounds per game, bpg=blocks per game, apg=assists per game, spg=steals per game, fg%=field goal percentage, 3pt= 3-point percentage, ft%=free throw percentage, mpg=minutes per game

 

Point Guard

Connecticut: A.J. Price (6-2, 190 Sr.)-14.7 ppg/3.4 rpg/40.3% 3pt/71.2% ft/4.8 apg

 

Michigan State: Kalin Lucas (6-0, 180 So.)-14.6 ppg/2.2 rpg/38.8% 3pt/81.4% ft/4.6 apg

 

This position is the reason why both teams made it this far.  Both players are 4-star leaders.  Their stats are similar, but the differences are Price’s experience and the fact that he compiled these stats in addition to leading the Huskies while Lucas is more of the go-to guy.

 

We give a slight advantage to UConn here.

 

Shooting Guard

Connecticut: Craig Austrie (6-3, 176 Sr.)-7.3 ppg, 1.8 rpg, 80.5% ft, 2.3 apg

 

Michigan State: Travis Walton (6-2, 190 Sr.)-5.3 ppg, 2.3 rpg, 3.2 apg, 1.5 spg

 

While Walton is one of the top defensive guards in the nation, stopping Austrie won’t shut the Huskie offense down.  He should be able to supply extra help defense though, and that should make up for his inability to shoot from outside or at the foul line.

 

Austrie has had some hot nights, but that isn’t required of him for his team to make it to Monday night.

                                                                 

We’ll give an ever so slight advantage to MSU.

 

Small Forward

Connecticut: Stanley Robinson (6-9, 220 So.)-8.2 ppg/5.7 rpg/49.5% fg

 

Michigan State: Delvin Roe (6-8, 225 Fr.)-5.8 ppg/5.0 rpg/56.5% fg

 

This is a tough one to figure out.  Neither player plays consistently.  If both play a good game, it will be close to a wash.  Roe cannot hit the broad side of a barn from the foul line, but Robinson is basically an in-close shooter with no real range.

 

We’re going to call this one a stand-off but with high deviation.  Either player could have a big game or disappear.

 

Power Forward

Connecticut: Jeff Adrien (6-7, 243 Sr.)-13.7 ppg/10.0 rpg/50.5% fg/1.1 bpg

 

Michigan State: Raymar Morgan (6-8, 225 Jr.)-10.2 ppg/5.3 rpg/52.5% fg/1.2 apg

 

Morgan has not had a great game in March.  He is not a great defender nor a dominant rebounder for his position.

 

Adrien plays much like Wes Unseld used to play.  He stops the opponent in the hot shooting area, and he punishes any opponent who dares try to rebound the ball in his area. 

 

We’ll give UConn a hefty advantage here.

 

Center

Connecticut: Hasheem Thabeet (7-3, 265 Jr.)-13.5 ppg/10.9 rpg/4.3 bpg/64.9% fg

 

Michigan State: Goran Suton (6-10, 245 Sr.)-10.4 ppg/8.4 rpg/51.6% fg/

 

Both players are prone to getting into foul trouble, but Thabeet is the more likely to foul out of a game.  Thabeet is a Bill Russell type player.  Unless another Wilt Chamberlain is opposing him, he is going to dominate the inside-as long as he is in the game and not sitting on the bench with foul concerns.

 

Suton doesn’t have the flashy numbers of his adversary, but he is a workhorse inside and won’t back down to Thabeet even though he is giving away five inches.  Suton plays strong defense.

 

In a surprise, we’re going to call this one a wash.

 

Bench Play

Connecticut

Kemba Walker (6-1, 172 Fr. G)-9.0 ppg/3.5 rpg/74.6% ft/1.1 spg/2.9 apg/25 mpg

 

Gavin Edwards (6-9, 230 Jr. F/C)-3.9 ppg/2.9 rpg/63.3% fg/74.5% ft/12 mpg

 

Michigan State

Chris Allen (6-3, 205 So. G)-8.7 ppg/2.3 rpg/80.0% ft/19 mpg

 

Durrell Summers (6-4, 195 So. G)-8.4 ppg/3.3 rpg/21 mpg

 

Marquise Gray (6-8, 235 Sr. F)-3.3 ppg/2.9 rpg/58.7% fg/10 mpg

 

Draymond Green (6-6, 235 Fr. F)-3.1 ppg/3.2 rpg/53.3% fg/11 mpg

 

Connecticut basically goes just seven deep since Jerome Dyson was lost 24 games into the season.  The two bench players are better than any two bench players for the Spartans.  However, MSU has great depth.  The Spartans can wear down the best opponents and still have something in the tank at the end of games. 

 

Edwards may have to play serious minutes in the paint if Thabeet picks up too many early fouls.

 

We’ll call this a win-win comparison.  UConn has the better seven deep bench, but MSU has the better depth by far.  Overall, give a slight edge to the Spartans.

 

PiRate Criteria see articles from the week of March 16-18 for explanation of this statistical formula

 

Connecticut qualifies as one of the elite team with statistical data similar to many previous title holders.  Michigan State just barely fails to qualify with 7 total criteria points.  Of course, we must look at both strength of schedule and implied home court advantage.  MSU’s schedule was about two points per game stronger than UConn’s.  You can also add about three points home court advantage for the Spartans playing just over an hour away from campus.

 

Prediction

We are supposed to go with the criteria in virtually every game, and it would be hard to pick against Connecticut.  We think this is going to be a whale of a ball game.  Connecticut gives up just 37.6% shooting to opponents and blocks eight shots per game.

 

Michigan State gives up just 63 points per game and 41.4% shooting to opponents.  The Spartans are the dominant rebounding team in the land with an advantage of almost 10 per contest.  That advantage will be neutralized because UConn is just a hair behind at +9.2 per game. 

 

We expect the Huskies to stake themselves to the early lead and pad it a bit to the halfway point of the final period.  Then, the fatigue factor will begin to creep in.  At this point, Michigan State will mount a rally.  Connecticut will gain a second wind at the end and hold the Spartans at bay in the crucial time of this game.  Then, it will be up to the Huskies to hit their foul shots at the end of the game.  UConn hits 68% from the charity stripe.  It’s not great, but we believe Coach Jim Calhoun’s squad will advance to their third ever national title game.

 

Connecticut 67 Michigan State 63

 

 

Game 2

North Carolina Tar Heels (32-4) vs. Villanova Wildcats (30-7)

Tip Time: 30 minutes following the end of the

Connecticut-Michigan State Game

Approximately 8:47 PM EDT

 

Rosters

 

North Carolina Tar Heels

No. Name Ht. Wt. Pos. Yr. Hometown (High School)
1 Marcus Ginyard 6-5 220 G/F SR Alexandria, Va. (Bishop O’Connell)
2 Marc Campbell 5-11 175 G JR Wilmington, N.C. (Ravenscroft)
4 Bobby Frasor 6-3 210 G SR Blue Island, Ill. (Brother Rice)
5 Ty Lawson 5-11 195 G JR Clinton, Md. (Oak Hill Academy (Va.))
11 Larry Drew II 6-1 180 G FR Encino, Calif. (Woodland Hills Taft)
13 Will Graves 6-6 245 F/G SO Greensboro, N.C. (Dudley)
14 Danny Green 6-6 210 F/G SR North Babylon, N.Y. (St. Mary’s)
15 J.B. Tanner 6-0 185 G SR Hendersonville, N.C. (West Henderson)
21 Deon Thompson 6-8 245 F JR Torrance, Calif. (Torrance)
22 Wayne Ellington 6-4 200 G JR Wynnewood, Pa. (The Episcopal Academy)
24 Justin Watts 6-4 205 G FR Durham, N.C. (Jordan)
30 Jack Wooten 6-2 190 G SR Burlington, N.C. (Williams)
32 Ed Davis 6-10 215 F FR Richmond, Va. (Benedictine)
35 Patrick Moody 6-4 195 F SR Asheville, N.C. (T.C. Roberson)
40 Mike Copeland 6-7 235 F SR Winston-Salem, N.C. (R.J. Reynolds)
44 Tyler Zeller 7-0 220 F FR Washington, Ind. (Washington)
50 Tyler Hansbrough 6-9 250 F SR Poplar Bluff, Mo. (Poplar Bluff)

 

 
Coaching Staff
 
Roy Williams – Head Coach
Joe Holladay – Assistant Coach
Steve Robinson – Assistant Coach
C.B. McGrath – Assistant Coach
Jerod Haase – Director of Basketball Operations
Chris Hirth – Head Athletic Trainer
Eric Hoots – Video Coordinator
Jonas Sahratian – Strength & Conditioning Coordinator

 

 

Villanova Wildcats

 

No. Name Pos. Cl. (EXP) Ht. Wt. Hometown High School

0

Antonio Pena Forward RS SO (2L) 6-8 235 Brooklyn, N.Y. St. Thomas More

1

Scottie Reynolds Guard JR (2L) 6-2 190 Herndon, Va. Herndon

4

Jason Colenda Guard JR (1L)   205 Fairfax, Va. Bishop O’Connell

10

Corey Fisher Guard SO (1L) 6-1 200 Bronx, N.Y. St. Patrick’s (N.J.)

15

Reggie Redding Guard JR (2L) 6-5 205 Philadelphia, Pa. St. Joseph’s Prep

20

Shane Clark Forward SR (3L) 6-7 205 Philadelphia, Pa. Hargrave Military Academy

21

Maurice Sutton Forward/Center FR 6-11 215 Upper Marlboro, Md. Largo

22

Dwayne Anderson Guard/Forward SR (3L) 6-6 215 Silver Spring, Md. St. Thomas More

23

Russell Wooten Forward JR 6-4 210 Chula Vista, Calif. St. Augustine

24

Corey Stokes Guard SO (1L) 6-5 220 Bayonne, N.J. St. Benedict’s

31

Taylor King Forward RS FR 6-6 230 Huntington Beach, Cal. Santa Ana Mater Dei

33

Dante Cunningham Forward SR (3L) 6-8 230 Silver Spring, Md. Potomac

42

Frank Tchuisi Forward SR (3L) 6-8 215 Douala, Cameroon St. Benedict’s

 

 
Coaches

Jay Wright-Head Coach

Patrick Chambers-Associate Head Coach

Doug West-Assistant Coach

Jason Donnelly-Assistant Coach

Keith Urgo-Manager of Basketball Operations

Kyle Neptune-Administrative Intern

Jeff Pierce-Head Athletic Trainer

Lon Record-Strength Coach

 

Player Matchups

 

Point Guard

North Carolina: Ty Lawson (5-11, 195 Jr.)-16.3 ppg/2.8 rpg/54.2% fg/48.5% 3pt/81.5% ft/6.5 apg/2.0 spg

 

Villanova: Scottie Reynolds (6-2, 190 Jr.)-15.2 ppg/2.8 rpg/35.3% 3pt/81.7% ft/3.3 apg/1.6spg

 

What can’t Ty Lawson do?  He is the best outside shooter in the Final Four.  He can penetrate and either take it to the hoop or dish the rock for an easy shot.  He can play defense better than any other guard.  He can also shoot craps better than anybody on the Canadian-American border.

 

Reynolds is the reason VU made it this far.  It was his buzzer beater that knocked Pittsburgh out of the Dance.  He has a good offensive game, but he cannot handle Lawson.

 

North Carolina receives a huge advantage here.

 

Shooting Guard

North Carolina: Wayne Ellington (6-4, 200 Jr.)-15.6 ppg/4.8 rpg/48.0% fg/39.7% 3pt/77.8% ft/2.7 apg

 

Villanova: Reggie Redding (6-5, 205 Jr.)-6.9 ppg/5.0 rpg/70% ft/3.1 apg/1.2 spg

 

Ellington is a streaky outside shooter.  When his shot is falling, North Carolina cannot be defeated. 

 

Redding is VU’s defensive sparkplug who gives the Wildcats a fourth inside presence.  He had yet to meet an opponent as talented as Ellington though.

 

We give North Carolina the advantage here, but it is not strong.

 

Small Forward

North Carolina: Danny Green (6-6, 210 Sr.)-13.3 ppg/4.8 rpg/47.3% fg/41.5% 3pt/85.2% ft/2.8 apg/1.3 bpg/1.8 spg

 

Villanova: Dwayne Anderson (6-6, 215 Sr.)-9.1 ppg/2.8 rpg/46.0% fg/83.9% ft/1.4 apg/1.6 spg

 

Green can do a little of everything, but he isn’t a go-to player.  Anderson is similar to Green, just not as talented.

 

North Carolina has a small advantage here as well.

 

Power Forward

North Carolina: Deon Thompson (6-8, 245 Jr.)-10.7 ppg/5.8 rpg/49.8% fg/1.1 bpg/1.0 spg

 

Villanova: Dante Cunningham (6-8, 230 Sr.)-16.2 ppg/7.4 rpg/52.9% fg/1.2 apg/1.3 bpg/1.2 spg

 

Thompson is North Carolina’s least talented starter, but that is not a slap in his face.  He’s just not the star that the other four starters are.  There have been times when Thompson has come up with big plays.

 

Cunningham is Villanova’s key weapon.  As he goes, so go the Wildcats.  VU’s only chance at getting to Monday night’s game is for him to have a Danny Manning/Jack Givens moment.  We doubt that will happen, but he should have a good, if not great game.

 

Villanova has a decided edge here.

 

Center

North Carolina: Tyler Hansbrough (6-9, 250 Sr.)-20.9 ppg/8.1 rpg/52.1% fg/85.8% ft/1.2 spg

 

Villanova: Shane Clark (6-7, 205 Jr.)-5.6 ppg/3.8 rpg/48.0% fg

 

Clark is a hard-nosed defensive stopper, but he cannot stop his opponent.  The top relief pitcher in baseball couldn’t consistently keep Babe Ruth from hitting one into the seats, and that’s why it will take two or two and a half defenders to keep Hansbrough from beating Villanova.

 

Hansbrough is like a loyal employee who always shows up for work on time, always does his job as well as helping others, and never complains when he doesn’t get a raise.  He may not be the most naturally talented big man in Tar Heel lore (James Worthy-Sam Perkins-Tom Lagarde-Bob McAdoo, etc.)

 

North Carolina has a major advantage here.

 

Bench Play

North Carolina

Ed Davis (6-10, 215 Fr. F)-6.6 ppg/6.6 rpg/51.4% fg/1.8 bpg/19 mpg

 

Bobby Frasor (6-3, 210 Sr. G)-2.7 ppg/1.9 rpg/1.4 apg/17 mpg

 

Villanova

Corey Fisher (6-1, 200 So. G)-10.7 ppg/2.2 rpg/78.8% ft/2.8 apg/1.3 spg/24 mpg

 

Corey Stokes (6-5, 220 So. G)-9.5 ppg/3.4 rpg/84.8% ft/1.0 apg/23 mpg

 

Antonio Pena (6-8, 235 So. F)-5.3 ppg/4.2 rpg/48.5% fg/18 mpg

 

While neither team can go 10-deep, the reserves that do play are good enough to start for most teams.  In Villanova’s case, the two Coreys are really starters and not reserves.  They enter the game after the opening tip, but they play the bulk of the minutes at their positions.

 

North Carolina’s Davis is a future NBA player as soon as he can add some bulk.  Frasor is the type of pesty player who can stick the dagger in the opposing team with a well-timed trey after the defense has played competently for 25-30 seconds.

 

We’ll call this a wash.

 

PiRate Criteria

North Carolina had the second best criteria score of the 65 teams in the field, so the Tar Heels were selected to make it all the way to the last game.

 

Villanova has teetered on the brink of qualifying as a superior team.  After the regional semifinal and final rounds, the Wildcats statistical gains have elevated their criteria score to 11, which now gives them superior status.  Still, they trail UNC by six in this category.

 

The strengths of schedule are nearly equal, as UNC gets one additional point here.

 

Prediction

North Carolina is clearly the better team.  It doesn’t mean Villanova has no chance, because a really good team can defeat a great team under certain conditions.

 

We believe this game will remain close throughout the first half, and Villanova could go to the locker room with a small lead.  The Tar Heels have too many quality options for the entire roster to have an off game.  Coach Roy Williams will figure out how to get his hot players the ball in the second half, and UNC will go on a run and put this game away by taking a double digit lead in the final 12 minutes. 

 

North Carolina 78 Villanova 66

 

Tune in here Sunday Night for a preview of the Championship Game.

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