The Pi-Rate Ratings

March 27, 2009

A PiRate Look At The NCAA Tournament: The Elite 8–March 28-29, 2009

A PiRate Look At The NCAA Tournament

The Elite 8

 March 28-29, 2009

 

We’ve decided to combine the Saturday and Sunday games into one blog since this is being compiled late Friday night after the games have ended.

 

It’s not quite the Big East Tournament part two, but it looks like there will be two and as many as three Big East teams headed to Detroit.

 

Our Sweet 16 picking brought an end to our chances of hitting the national champion for a fourth consecutive season.  We missed that pick, although we did mention that we thought Missouri should be the true favorite in that game and that they could easily run out to a quick double-digit lead in the game.  We also must admit that our mentor and originator of this blog told us to watch Missouri knock Memphis out, and we didn’t listen as much as we should have.

 

So, which teams left in the tournament still possess all the PiRate Criteria necessary to win it all?  In the East, Pitt easily qualifies.  Villanova now qualifies if you factor in their win over Duke, since their points per game margin reached 10.0 following the easy win.  In the Southeast, North Carolina qualifies, but Oklahoma just misses.  In the Midwest, Louisville qualifies but not Michigan State.  In the West, Connecticut and Missouri both qualify.  Seven of the eight remaining teams qualify, and the one that misses does so by a mere one point. 

 

Of the original 11 teams we listed as super teams possessing the statistical criteria similar to past champions, five have made it to the Elite 8 round. 

 

Our record for the Sweet 16 was just 5-3, bringing the three round total to 43-13.

 

 

(numbers in parentheses are PiRate Criteria scores)

[number in brackets is Strength of Schedule advantage]

 

East Region @ Boston

 

Pittsburgh (14) vs. Villanova (9) [Pittsburgh 2]

Game Time: Saturday, 7:00 PM EDT

These teams played just once during the regular season with Villanova winning by 10 at home.  In that game, Pitt’s Dejuan Blair sat on the bench with foul trouble for much of the night.

 

With Blair staying out of foul trouble this time, we think the Panthers will advance to their first Final Four.

 

Prediction: Pittsburgh 72 Villanova 64

 

South Region @ Memphis

 

North Carolina (17) vs. Oklahoma (9) [Even Strength]

Game Time: Sunday, 5:00 PM EDT

What a great match between two dominant big men we have here!  Tyler Hansbrough and Blake Griffin are two of the top five college players in the game. 

 

Griffin may end up with the better numbers in this game, but Hansbrough has a much better supporting cast.  The Tar Heels will advance yet again to another Final Four.

 

Prediction: North Carolina 85 Oklahoma 73

 

Midwest Region @ Indianapolis

 

Louisville (10) vs. Michigan State (7) [Mich. State 1]

Game Time: Sunday, 2:20 PM EDT

The Two games on this side of the bracket provide us with great studies in contrast.  A quick, full-court team will take on an inside banger team that has some decent outside shooting.

 

Four of Louisville’s five losses came to teams that can bang the ball inside and get plenty of offensive rebounds.  Connecticut, Notre Dame, Minnesota, and UNLV all play a game similar to Michigan State.  The Spartans are capable of holding the Cardinals under 45% shooting and take 55% of the rebounds.  Capable yes, but we don’t think it will happen.  Rick Pitino will guide UL back to the Final Four.

 

Prediction: Louisville 70 Michigan State 63

 

West Region @ Glendale, AZ

 

Connecticut (14) vs. Missouri (12) [Connecticut 1]

Game Time: Saturday, 4:30 PM EDT

We think this will be the best game of the four in this round.  Missouri looked every bit as good as the 1994 Arkansas team that won the NCAA Championship, a team with current Tiger coach Mike Anderson on the bench as an assistant.

 

On the other hand, UConn looks every bit as good if not better than the two Husky teams that won national titles.

 

We don’t think Mizzou will be able to force all that many turnovers in this game, and if they only pick up 8-10 steals, it will not be enough.  They need 12-15 steals to have a chance to win this game.

 

Connecticut’s inside game will be too strong for MU, and we think it will force the Tigers into foul trouble. 

 

Prediction: Connecticut 86 Missouri 74

March 17, 2009

Bracketnomics 505–The Advanced Level Class In Bracket Filling

Bracketnomics 505-The Advanced Level Class In Bracket Filling

This is a graduate level class that will earn you a Masters in Bracketnomics.  So you want a scientific method to guide you as you fill out your brackets?  You say you want a system that will take out most of the human-bias, and allow you to pick your teams in a mechanical fashion.  Well, we’ve got one for you that has been back-tested and holds up fantastically through the years. 

What the inventor of the PiRate system did was to discover the vital information that has worked in the past.  He’s been using this formula since the Internet made statistics-gathering easy, and it has been back-tested as far back as the days when the NCAA Tournament field consisted of just 23, 24, or 25 teams.

This method will not pick every game correctly and make you an instant millionaire.  It is geared toward finding the tendencies that historically have mattered most in picking the teams with the best chances of advancing.  Not all teams will be a perfect fit in this formula; what this formula does is pick the teams that have the best chance of advancing and making a deep run into the tournament. 

How has the formula performed in recent years?  Last year, it picked Kansas to win the NCAA Championship.  In 2006, it tabbed George Mason as a team to watch to sneak into the Elite 8 (they went to the Final 4).   It correctly selected Florida and UCLA for the Final Four in both 2006 and 2007. 

There have been a couple of seasons where the criteria didn’t apply successfully, but over the course of the 50 seasons, it has performed accurately about 43 times.  Without further adieu, here is the PiRate Bracket-Picking System.

1. Scoring Margin

For general bracket picking, look for teams that outscored their opponents by an average of 8 or more points per game.  Over 85% of the Final Four teams since the 1950’s outscored their opponents by an average of 8 or more points per game. 

Make a separate list of teams that outscored their opponents by an average of 10 or more points per game and a third list of teams outscoring opponents by an average of 15 or more points per game.  More than 80% of the final four teams in the last 50 years outscored their opponents by double digit points per game.  When you find a team with an average scoring margin in excess of 15 points per game, and that team is in one of the six power conferences, then you have a team that will advance deep into the tournament.

This is an obvious statistic here.  If team A outscores opponents by an average of 85-70 and their team B opponent outscores their opposition by an average of 75-70, team A figures to be better than team B before you look at any other statistics. 

In the days of the 64/65-team field, this statistic has become even more valuable.  It’s very difficult and close to impossible for a team accustomed to winning games by one to seven points to win four times in a row.  This average gives the same significance and weighting to a team that outscores its opposition 100-90 as it does to a team that outscores its opposition 60-50.

2. Field Goal Percentage Differential

Take each team’s field goal percentage minus their defensive field goal percentage.  Look for teams that have a +7.5% or better showing.  50% to 42% is no better or no worse than 45% to 37%.  A difference of 7.5% or better is all that matters.  Teams that have a large field goal percentage margin are consistently good teams.  Sure, a team can win a game with a negative field goal percentage difference, but in the Big Dance, they aren’t going to win four games much less two.  This statistic holds strong in back-tests of 50 years.  Even when teams won the tournament with less than 7.5% field goal percentage margins, for the most part, these teams just barely missed (usually in the 5.5 to 7.5% range).  In the years of the 64/65-team tournament, this stat has become a more accurate predictor.  Nowadays, the teams with field goal percentage margins in the double digits have dominated the field.  If you see a team shoot better than 48% and allow 38% or less, that team is going to be very hard to beat in large arenas with weird sight lines.

3. Rebound Margin

This statistic holds up all the way back to the early days of basketball, in fact as far back to the days when rebounds were first recorded.  The teams that consistently control the boards are the ones that advance deep into the tournament.  What we’re looking for here are teams that out-rebound their opposition by five or more per game.  In the opening two rounds, a difference of three or more can be used.

The reason this statistic becomes even more important in mid-March is that teams don’t always shoot as well in the NCAA Tournament for a variety of reasons (better defense, abnormal sight lines and unfamiliar gymnasiums, nerves, new rims and nets, more physical play with the refs allowing it, etc.).  The teams that can consistently get offensive putbacks are the teams that go on scoring runs in these games.  The teams that prevent the opposition from getting offensive rebounds, holding them to one shot per possession, have a huge advantage.  Again, there will be some teams that advance that were beaten on the boards, but over the course of four rounds, it is rare for one of these teams to advance.  West Virginia in 2005 made it to the Elite Eight without being able to rebound, but not many other teams have been able to do so.  There have been years where all four Final Four participants were in the top 20 in rebounding margin, and there have been many years where the champion was in the top 5 in rebounding margin.

4. Turnover Margin & Steals Per Game

Turnover margin can give a weaker rebounding team a chance.  Any positive turnover margin is good here.  If a team cannot meet the rebounding margin listed above, they can get by if they have an excellent turnover margin.  Not all turnover margin is the same though.  A team that forces a high number of turnovers by way of steals is better than a team that forces the same amount of turnovers without steals.  A steal is better than a defensive rebound, because most of the time, a steal leads to a fast-break basket or foul.  When a team steals the ball, they are already facing their basket, and the defense must turn around and chase.  Many steals occur on the perimeter where the ball-hawking team has a numbers advantage.  So, this system counts a steal as being worth 1.33 rebounds. 

The criteria to look for here is a positive turnover margin if the team out-rebounds its opposition by three or more; a turnover margin of three or better if the team out-rebounds its opposition by less than three; and a turnover margin of five or more if the team does not out-rebound its opponents.  Give more weight to teams that average 7.5 or more steals per game, and give much more weight to teams that average double figure steals per game.  A team that averages more than 10 steals per game will get a lot of fast-break baskets and foul shots.  In NCAA Tournament play, one quick spurt can be like a three-run homer in the World Series, and teams that either steal the ball or control the boards are the ones who will get that spurt.

The All-Important R+T Margin: Consider this the basketball equivalent of baseball’s OPS (On Base % + Slugging %).  Here is the PiRate R+T stat: R + (.2S * {1.2T}), where R is rebounding margin, S is average steals per game, and T is turnover margin.  When this stat is 5 or more, you have a team that can overcome a few other liabilities to win.  When the result is 10 or more, you have a team that has a great chance of getting enough additional scoring opportunities to make it to the later rounds.  When this stat is negative, you have a team that will be eliminated before the Sweet 16.

5. Power Conference Plus Schedule Strength

I’m sure up to this point you have been thinking that it is much easier for North Dakota State or Siena to own these gaudy statistics than it is for Pittsburgh or Michigan State.  Of course, that’s correct.  We have to adjust this procedure so that the top conferences get extra weight, while the bottom conferences get penalized.  Here is how we do it.  Look at the Strength of schedule for every team in the Field.  You can find SOS on many websites, such as the RPI at cbs.sportsline.com.  Take the decimal difference for each team in the Field and multiply that by 100.  For example if Team A’s SOS is .6044 and Team B’s is .5777, the difference times 100 is 2.67.  So, Team A’s schedule was 2.67 points (or round it to 3) per game tougher than Team B’s.  Use this in head-to-head contests for every game in your bracket.

These are the five basic PiRate criteria used for the last dozen or so years.  You might be shocked to see that there are some key statistics that are not included.  Let’s look at some of these stats not to rely upon.

Assists and Assists to Turnover Ratio

While assists can reveal an excellent passing team, they also can hide a problem.  Let’s say a team gets 28 field goals and has 21 assists.  That may very well indicate this team can pass better than most others.  However, it can also mean two other things.  First, this team may not have players who can create their own offense and must get by on exceptional passing.  That may not work against the best defensive teams in the nation, or the type that get into the Dance.  Second, and even more importantly, it may indicate that this team cannot get offensive putbacks.  As explained earlier, the offensive putback is about as important as any stat can be.  So, consider this stat only if you must decide on a toss-up after looking at the big five stats.

Free Throw Shooting 

Of course, free throw shooting in the clutch decides many ball games.  However, history shows a long line of teams making it deep into the tournament with poor free throw shooting percentages, and teams that overly rely on free throws may find it tough getting to the line with the liberalized officiating in the tournament.

Let’s say a team shoots a paltry 60% at the foul line while their opponent hits a great 75% of their foul shots.  Let’s say each team gets to the foul line 15 times in the game, with five of those chances being 1&1, three being one shot after made baskets, and seven being two shot fouls.  For the 60% shooting team, they can be expected to hit 3 of 5 on the front end of the 1&1 and then 1.8 of the 3 bonus shots; they can be expected to hit 1.8 of 3 on the one foul shot after made baskets; and they can be expected to hit 8.4 of 14 on the two shot fouls for a total of 15 out of 25.  The 75% shooting team can be expected to connect on 3.75 of 5 on the front end of the 1&1 and then 2.8 of 3.75 on the bonus shot; they can be expected to hit 2.3 of 3 on the one foul shot after made baskets; and they can be expected to connect on 10.5 of 14 on the two shot fouls for a total of 19.35 out of 25.75.  So, a team with one of the top FT% only scores nine more points at the foul line than a team with one of the worst.  That looks like a lot of points to make up, but consider that this is about the maximum possible difference.  Also consider that teams that shoot 60% of their foul shots and make the NCAA Tournament are almost always the teams that also have the top R+T ratings.  Teams that make the NCAA Tournament with gaudy free throw percentages frequently got there by winning close games at the line.  In the NCAA Tournament, fouls just don’t get called as frequently as in the regular season.  The referees let the teams play.  So, looking at superior free throw percentage can almost lead you down the wrong path. 

Ponder this:  The 1973 UCLA Bruins are considered to be the best college basketball team ever.  That team connected on just 63% of its free throws.  They had a rebounding margin of 15.2, and they forced many turnovers via steals thanks to their vaunted 2-2-1 zone press.  In the great UCLA dynasty from 1964 through 1973 when the Bruins won nine titles in 10 years, they never once connected on 70% of their free throws and averaged just 66% during that stretch.

3-point shooting

You have to look at this statistic two different ways and consider that it is already part of field goal percentage and defensive field goal percentage.  Contrary to popular belief you do not count the difference in made three-pointers and multiply by three to see the difference.  If Team A hits eight treys, while their Team B opponents hit three, that is not a difference of 15 points; it’s a difference of five points.  Consider made three-pointers as one extra point because they are already figured as made field goals.  A team with 26 made field goals and eight treys has only one more point than a team with 26 made field goals and seven treys.

The only time to give three-point shots any weight in this criteria is when you are looking at a toss-up game, and when you do look at this stat, look for the team that does not rely on them to win, but instead uses a credible percentage that prevents defenses from sagging into the 10-12-foot area around the basket.  If a team cannot throw it in the ocean from behind the arc, defenses can sag inside and take away the inside game.  It doesn’t play much of a role in the NCAA Tournament.  A team that must hit 10 threes per game in order to win isn’t going to be around after the first weekend.

One Big Star or Two Really Good Players

Teams that got to the Dance by riding one big star or a majority of scoring from two players are not solid enough to advance very far.  Now, this does not apply to a team with one big star and four really good players.  I’m referring to a team with one big star and four lemons or two big scorers with three guys who are allergic to the ball.  Many times a team may have one big scorer or two guys who score 85% of the points, but the other three starters are capable of scoring 20 points if they are called on to do so.  If you have a team with five double figure scorers, that will be a harder one to defend and one that will be consistent.  It’s hard for all five players to slump at once.

We hope this primer will help you when you fill out your brackets this week. 

Now, here is a way to put numbers to the criteria.  It isn’t exactly the way our founder did it every year, but it is a close approximation.

1. Scoring Margin

Award 5 points for every team with a scoring margin difference of 10 or more

Award 3 points for every team with a scoring margin difference of 8.0-9.9

Award 1 point for every team with a scoring margin difference of 5.0-7.9

Award 0 points for every team with a scoring margin difference of 0-4.9

Award -3 points for every team with a negative scoring margin

2. Field Goal % Margin

Award 5 points for every team with a FG% margin difference of 10% or more

Award 3 points for every team with a FG% margin difference of 7.5 to 9.9

Award 1 point for every team with a FG% margin difference of 5.0-7.4

Award 0 points for every team with a FG% margin difference of 0.0-4.9

Award -3 points for every team with a FG% margin difference below 0

3. Rebound Margin

Award 3 points for every team with a Rebound margin difference of 5 or more

Award 1 point for every team with a Rebound margin difference of 3.0-4.9

Award 0 points for every team with a Rebound margin difference of 0-2.9

Award -2 points for every team with a Rebound margin difference below 0

4. Turnover Margin

Award 3 points for every team with a Turnover margin difference of 3 or more

Award 1 point for every team with a Turnover margin difference of 1.5-2.9

Award 0 points for every team with a Turnover margin difference of 0-1.4

Award -2 points for every team with a Turnover margin below 0

5. PiRate R+T Formula

Once again, the formula for R+T is [R + ({.2*S}*{1.2*T})], Where R is rebounding margin, S is avg. steals per game, and T is turnover margin

Award 5 points for every team with an R+T of 10 or more

Award 3 points for every team with an R+T of 7.5-9.9

Award 1 point for every team with an R+T of 5-7.4

Award 0 points for every team with an R+T of 0-4.9

Completely eliminate from consideration all teams with a negative R+T

6. Schedule Strength

Use this to compare when looking at team vs. team.  Take the difference in the Strength of Schedule as given by cbs.sportsline.com and multiple it by 100.  For example, Team A with an SOS of .5252 has a schedule 7 points weaker than Team B with an SOS of .5921.  If these two teams face each other, give the Team B an extra 7 criteria points over Team A ([(.5921-.5252)*100]=6.69 rounds to 7).

If you want to compile all this information yourself, the best way is to go to all 65 official athletic websites of the teams in the Big Dance.  You will find up-to-date statistical information.  Some of these stats are available in other places, but many have been found to be riddled with mistakes, or they are not up-to-date.  All 65 school sites are accurate and timely.

Coming tomorrow (Wednesday), we’ll reveal which teams belong in the later rounds by virtue of having the best criteria scores.

March 28, 2008

A PiRate Look At The NCAA Men’s Basketball Regional Finals–March 29, 2008

The Elitist of the Elite

A PiRate Preview of The Regional Final Games-March 29, 2008

Eight teams are left, and only Davidson, a team with a 25-game winning streak can be considered a surprise.  Xavier and Louisville may not have been expected to get this far, but both the Musketeers and Cardinals are no big surprises.

All four number one seeds have advanced to the Elite Eight.  Can all four make it to the Final Four for the first time since the current 64/65-team format has been in effect?  It’s possible, but it’s also possible that two of the four top-seeded teams could lose.

Of the eight Sweet 16 round games, seven of them were dull games.  Only the Xavier-West Virginia game was worth watching from start to finish.  Let’s hope the Regional Final games are a little more exciting.

In the statistics shown below, the records are up to date, but the stats do not include the Regional Semifinal games.  Those will be included in next week’s Final Four Previews.

Note:  In the statistics below, you will see a column marked other.  “B” means the player is an exceptional shot blocker.  “S” means the player is exceptional at stealing the ball.  “A” means the player is an excellent passer for assists.  “F” means the player is foul-prone.

West Regional-Phoenix

Saturday, March 29, 2008

6:40 PM EDT

#3 Xavier vs. #1 UCLA

Xavier Musketeers

Record: 30-6

Head Coach: Sean Miller

No.

Player

Pos

Height

Weight

Cl.

Pts.

Reb.

FG%

3pt%

FT%

Other *

STARTERS

31

Jason Love

F/C

6-09

255

So.

6.1

5.4

57.4

0.0

60.4

B

5

Derrick Brown

F

6-08

225

So.

10.9

6.7

60.2

34.5

72.1

20

C.J. Anderson

F/G

6-06

220

Jr.

10.7

5.9

52.3

0.0

67.3

34

Stanley Burrell

G

6-03

210

Sr.

9.8

2.1

39.1

38.9

83.1

A

24

Drew Lavender

G

5-07

153

Sr.

11.0

2.6

43.6

40.4

86.8

A

KEY RESERVES %

1

Josh Duncan

F

6-09

235

Sr.

12.1

4.7

50.4

41.8

85.4

F

11

B.J. Raymond

G/F

6-06

225

Jr.

10.1

3.1

44.9

41.1

86.1

25

Dante’ Jackson

G

6-05

205

Fr.

2.4

1.2

35.4

38.1

61.5

S/F

Statistical Analysis

XAV

Stat

Opp

Difference

47.8

FG%

40.6

7.2

39.1

3pt%

33.7

5.4

75.5

FT%

67.6

7.9

35.8

Reb

30.2

5.6

13.1

TO

13.0

-0.1

3.4

BK

3.6

-0.2

5.6

STL

6.6

-1.0

15.3

AST

13.1

2.2

R+T  #

5.47

75.5

PPG

62.7

12.8

PiRate Score

8 *

Schedule Strength

.5720

(*) Missed being 10 by very little

(#) For an explanation of R+T, PiRate Score, and Schedule

Strength, see “Bracketnomics 505” posted on 3/17/08

& how point values are assigned posted on 3/18/08

NCAA Tournament Results

Georgia

73-61

Purdue

85-78

West Virginia

79-75 ot

U C L A  Bruins

Record: 34-3

Head Coach: Ben Howland

No.

Player

Pos

Height

Weight

Cl.

Pts.

Reb.

FG%

3pt%

FT%

Other *

STARTERS

42

Kevin Love

C

6-10

271

Fr.

17.3

10.6

55.7

36.5

76.5

B

23

Luc Rich. Mbah a Moute

F

6-08

232

Jr.

8.6

5.5

47.9

20.0

69.4

3

Josh Shipp

F/G

6-05

220

Jr.

12.4

3.2

44.0

32.5

79.2

S

2

Darren Collison

G

6-00

160

Jr.

15.1

2.6

49.4

51.6

87.6

S/A

0

Russell Westbrook

G

6-03

185

So.

12.3

3.8

46.8

31.9

70.5

S/A

KEY RESERVES %

14

Mata-Real, Lorenzo

C

6-09

235

Sr.

3.3

3.7

50.0

0.0

45.2

B/F

12

Alfred Aboya

F/C

6-09

245

Jr.

3.1

2.3

50.0

33.3

52.8

F

41

Dragovic, Nikola

F

6-09

215

So.

2.6

1.4

33.9

23.8

12-12

13

James Keefe

G

6-08

225

So.

2.1

2.4

44.2

28.6

35.7

F

Statistical Analysis

UCLA

Stat

Opp

Difference

47.6

FG%

42.2

5.4

34.6

3pt%

32.5

2.1

73.0

FT%

67.0

6.0

36.3

Reb

27.9

8.4

12.4

TO

14.7

2.3

4.1

BK

2.6

1.5

7.4

STL

4.7

2.7

14.4

AST

11.3

3.1

R+T  #

12.48

73.3

PPG

58.0

15.3

PiRate Score

15

Schedule Strength

.5751

NCAA Tournament Results

Mississippi Valley

70-29

Texas A&M

51-49

Western Kentucky

88-78

UCLA is looking to become the first team since Duke to make it to three consecutive Final Fours.  Of Course the Bruins went to the Final Four every year from 1967 through 1975, so three in a row is now big deal in Westwood.

Xavier is looking to become the first team from the Queen City to make the Final Four since Cincinnati did so in 1992 (The Bearcats also own a five consecutive streak from 1959-1963).

UCLA has a huge intangible in its favor.  The Bruins keep getting the benefit of several officials’ mistakes.  Going back to the end of the regular season when they won back-to-back games over Stanford and California, both ending in controversy, to the Pac-10 Tournament where they won a close game over Southern Cal, to the Texas A&M game in the second round of the Big Dance where the Bruins players were allowed to hold and push with no fouls being called, where the Aggies’ players were whistled for entering the same Zip Code, and it is a pattern that cannot be ignored.  I’m not saying this is a conspiracy.  I’m saying its probably human nature taking its course.  UCLA always got the benefit of the doubt during their great dynasty years.  I remember watching them foul Maryland all over the gym in December of 1973, while Maryland couldn’t get within an arm’s length without being whistled.  Somehow, the Terps had a chance to win at the end that night, but fell short by one basket.

UCLA probably doesn’t need any help to win this game, but I wouldn’t be shocked to see them benefit from a few calls or non-calls by the zebras.  While Xavier has the talent to keep this game close, I’m expecting the sons of Westwood to march to the Final Four with a victory.  The matchup between UCLA’s Kevin Love and Xavier’s Jason Love will be what decides this game, and we can make an educated guess which player will win.

Prediction: UCLA 73  Xavier 64

East Regional-Charlotte

Saturday, March 29, 2008

9:05 PM EDT

#3 Louisville vs. #1 North Carolina

 

Louisville Cardinals

Record: 27-8

Head Coach: Rick Pitino

No.

Player

Pos

Height

Weight

Cl.

Pts.

Reb.

FG%

3pt%

FT%

Other *

STARTERS

4

David Padgett

F/C

6-11

245

Sr.

11.4

4.5

67.7

0.0

65.2

F

1

Terrence Williams

F

6-06

210

Jr.

11.0

7.3

40.5

34.3

56.7

S/A

5

Earl Clark

F/G

6-08

220

So.

10.9

8.0

46.2

23.1

65.5

B

34

Jerry Smith

G

6-01

200

So.

10.5

3.6

44.8

37.7

77.6

S

33

Andre McGee

G

5-10

180

Jr.

6.4

1.6

40.4

40.3

69.8

S/A

KEY RESERVES %

32

Derrick Caracter

F/C

6-09

265

So.

8.5

4.5

55.7

1 of 1

63.1

B/F

10

Edgar Sosa

G

6-01

175

So.

7.6

1.7

38.5

37.4

63.6

3

Juan Palacios

F/C

6-08

250

Sr.

6.4

4.0

44.5

31.3

70.5

S

Statistical Analysis

U of L

Stat

Opp

Difference

46.0

FG%

38.4

7.6

35.2

3pt%

30.6

4.6

64.4

FT%

67.7

-3.3

37.3

Reb

34.5

2.8

13.3

TO

14.6

1.3

4.9

BK

2.7

2.2

8.1

STL

5.7

2.4

15.1

AST

12.2

2.9

R+T  #

5.33

72.3

PPG

60.9

11.4

PiRate Score

9

Schedule Strength

.5852

NCAA Tournament Results

Boise State

79-61

Oklahoma

78-48

Tennessee

79-60

North Carolina Tar Heels

Record: 35-2

Head Coach: Roy Williams

No.

Player

Pos

Height

Weight

Cl.

Pts.

Reb.

FG%

3pt%

FT%

Other *

STARTERS

50

Tyler Hansbrough

F

6-09

250

Jr.

22.8

10.2

54.1

0.0

81.2

S

21

Deon Thompson

F

6-08

240

So.

8.5

4.8

47.7

0.0

58.6

B/F

1

Marcus Ginyard

G-F

6-05

218

Jr.

7.4

4.5

44.6

42.9

66.3

S

22

Wayne Ellington

G

6-04

200

So.

16.8

4.3

47.9

42.1

81.5

5

Ty Lawson

G

5-11

195

So.

12.9

2.7

52.8

36.0

82.5

S/A

KEY RESERVES %

14

Danny Green

G-F

6-05

210

Jr.

11.3

5.0

46.8

37.1

86.3

BSAF

32

Alex Stepheson

F

6-09

235

So.

4.4

4.8

53.2

0.0

43.2

B/F

11

Quentin Thomas

G

6-03

190

Sr.

3.4

1.5

57.3

25.0

78.1

A

4

Bobby Frasor

G

6-03

208

Jr.

3.2

1.8

34.2

30.0

50.0

S/A

Statistical Analysis

UNC

Stat

Opp

Difference

49.1

FG%

42.4

6.7

38.3

3pt%

33.0

5.3

75.4

FT%

66.9

8.5

44.0

Reb

32.4

11.6

14.3

TO

16.1

1.8

4.6

BK

4.9

-0.3

8.3

STL

7.9

0.4

17.3

AST

13.7

3.6

R+T  #

15.19

89.9

PPG

72.9

17.0

PiRate Score

17

Schedule Strength

.5921

NCAA Tournament Results

Mount St. Mary’s

113-74

Arkansas

108-77

Washington State

68-47

Louisville Coach Rick Pitino has his Cardinals playing the best half-court defense of any team he has ever coached, including his 1996 national champs at Kentucky.  What UL did to Tennessee was amazing Thursday night.  However, for the Cards to have any chance of getting to the Final Four, they will have to play even better defensively tonight.

North Carolina is an unstoppable force right now.  Sure, Washington State held them to 67 points, but the Cougars didn’t do it with great defense.  They slowed the game down, making it a low possession game.  UNC still had a fantastic points per possession stat in the game.

I expect the Tar Heels to get their first taste of playing in an NCAA Tournament game that isn’t decided by the under 12 timeout in the first half.  The Heels may even get extended into the second half before they put this one away.

Prediction: North Carolina 78  Louisville 69

South Regional-Houston

Sunday, March 30, 2008

2:20 PM EDT

#2 Texas vs. #1 Memphis

Texas Longhorns

Record: 31-6

Head Coach: Rick Barnes

No.

Player

Pos

Height

Weight

Cl.

Pts.

Reb.

FG%

3pt%

FT%

Other *

STARTERS

32

Connor Atchley

F/C

6-10

225

Jr.

19.2

2.9

44.3

38.0

77.9

B

5

Damion James

F/G

6-07

227

Jr.

13.2

10.7

46.4

44.6

56.3

B

24

Justin Mason

G

6-02

185

So.

7.1

4.3

42.2

34.2

66.2

A

3

A.J. Abrams

G

5-10

155

Jr.

16.6

2.8

42.8

38.1

80.9

14

D.J. Augustin

G

5-11

175

So.

19.2

2.9

44.3

38.0

77.9

A

KEY RESERVES %

1

Gary Johnson

F

6-07

235

Fr.

5.7

4.0

41.6

0.0

55.6

F

34

Dexter Pittman

C

6-10

293

So.

2.7

2.3

54.8

0.0

60.5

B/F

15

Alexis Wangmene

F/C

6-08

240

Fr.

2.2

2.4

42.3

0.0

66.0

B/F

Statistical Analysis

UT

Stat

Opp

Difference

45.3

FG%

38.8

6.5

39.1

3pt%

32.6

6.5

68.2

FT%

67.9

0.3

38.1

Reb

35.1

3.0

9.6

TO

12.1

2.5

5.3

BK

2.8

2.5

6.0

STL

4.6

1.4

13.1

AST

12.4

0.7

R+T  #

6.60

75.5

PPG

64.4

11.1

PiRate Score

9

Schedule Strength

.5950

NCAA Tournament Results

Austin Peay

74-54

Miami (Fla.)

75-72

Stanford

82-62

Memphis Tigers

Record: 36-1

Head Coach: John Calipari

No.

Player

Pos

Height

Weight

Cl.

Pts.

Reb.

FG%

3pt%

FT%

Other *

STARTERS

3

Joey Dorsey

F/C

6-09

265

Jr.

7.0

9.7

64.7

0.0

37.9

B/F

2

Robert Dozier

F

6-09

215

Jr.

9.4

6.7

45.1

29.0

68.5

B

14

Chris Douglas-Roberts

G/F

6-07

200

Jr.

17.3

4.2

54.7

42.7

68.4

5

Antonio Anderson

G

6-06

210

Jr.

8.4

3.7

40.9

32.8

56.6

A

23

Derrick Rose

G

6-03

205

Fr.

14.1

4.3

46.9

35.1

68.4

A

KEY RESERVES %

20

Doneal Mack

G

6-05

175

So.

7.7

1.8

39.7

37.1

66.7

F

0

Shawn Taggart

F/C

6-10

230

So.

5.8

4.2

51.0

37.5

63.9

B/F

1

Willie Kemp

G

6-02

175

So.

5.3

1.1

38.2

36.6

57.1

F

15

Andre Allen

G

5-10

205

Sr.

3.4

1.2

31.5

29.6

40.6

F

Statistical Analysis

Mem

Stat

Opp

Difference

46.6

FG%

38.5

8.1

35.3

3pt%

30.3

5.0

59.2

FT%

66.9

-7.7

40.9

Reb

34.2

6.7

12.0

TO

16.3

4.3

6.2

BK

3.3

2.9

8.5

STL

5.8

2.7

16.2

AST

10.7

5.5

R+T  #

15.47

79.8

PPG

61.1

18.7

PiRate Score

19

Schedule Strength

.5749

NCAA Tournament Results

Texas-Arlington

87-63

Mississippi State

77-74

Michigan State

92-74

Memphis looked every bit as talented as the UNLV 1990-91 team Friday Night against Michigan State.  Sure, they surrendered some easy baskets, but they out-rebounded a Tom Izzo-coached team by nine boards!  That doesn’t happen often, if ever.  When you have a player like Derrick Rose, who can come off the bench and score 27 points and Robert Dozier who can almost record a double double while playing just half the game, and you see how complete this team really is.  Who says the Tigers cannot hit free throws?  26-35 is going to win a lot of close games.

Texas isn’t just horse fodder.  The Longhorns are talented enough to advance to the title game.  Just imagine how great this team would be if Kevin Durant had decided to play just one more season.  D.J. Augustin and A.J. Abrams won’t be intimidated by the Tigers’ defense, and the deadly duo can force Memphis to become lax in the paint.  Then, Connor Atchley and Damion James will take over inside. 

Give Texas some home court advantage for playing in Houston, but give Memphis that little extra to get over the hump and avoid falling in the Elite Eight round for the third consecutive year.  They won’t be denied a third straight time-not with this much talent.

Prediction: Memphis 78  Texas 75

Midwest Regional-Detroit

Sunday, March 30, 2008

5:05 PM EDT

#10 Davidson vs. #1 Kansas

Davidson Wildcats

Record: 29-6

Head Coach: Bob McKillop

No.

Player

Pos

Height

Weight

Cl.

Pts.

Reb.

FG%

3pt%

FT%

Other *

STARTERS

15

Thomas Sander

F

6-08

220

Sr.

7.6

4.9

57.9

23.1

53.3

F

41

Andrew Lovedale

F

6-08

215

Jr.

6.7

5.4

53.6

0.0

66.7

F

14

Max Paulhus Gosselin

G/F

6-06

205

Jr.

3.6

3.5

36.7

12.5

65.5

S

30

Stephen Curry

G

6-03

185

So.

25.7

4.6

48.8

44.4

88.8

S/A

2

Jason Richards

G

6-02

185

Sr.

12.9

3.1

41.8

32.4

74.8

A

KEY RESERVES %

5

Boris Meno

F

6-08

230

Sr.

7.3

5.6

49.5

5.6

66.7

22

Will Archambault

G/F

6-06

210

So.

5.2

1.9

39.1

27.8

69.0

F

24

Bryant Barr

G

6-04

195

So.

5.1

1.0

38.9

40.5

64.7

23

Stephen Rossiter

F

6-07

230

So.

3.1

3.4

60.3

0.0

67.6

S/F

Statistical Analysis

DC

Stat

Opp

Difference

47.1

FG%

42.3

4.8

36.2

3pt%

35.6

0.6

72.3

FT%

63.1

9.2

36.6

Reb

32.7

3.9

12.1

TO

16.9

4.8

3.3

BK

2.4

0.9

8.1

STL

5.6

2.5

17.1

AST

13.5

3.6

R+T  #

13.23

78.6

PPG

63.5

15.1

PiRate Score

14

Schedule Strength

.5252

NCAA Tournament Results

Gonzaga

82-76

Georgetown

74-70

Wisconsin

73-56

Kansas Jayhawks

Record: 34-3

Head Coach: Bill Self

No.

Player

Pos

Height

Weight

Cl.

Pts.

Reb.

FG%

3pt%

FT%

Other *

STARTERS

32

Darnell Jackson

F

6-08

250

Sr.

11.5

6.7

62.3

33.3

69.5

0

Darrell Arthur

F

6-09

225

So.

13.1

6.2

54.0

16.7

70.4

B/F

25

Brandon Rush

G/F

6-06

210

Jr.

13.0

5.0

42.5

43.9

77.6

15

Mario Chalmers

G

6-01

195

Jr.

12.6

3.1

52.5

47.1

73.3

S/A

3

Russell Robinson

G

6-01

205

Sr.

7.4

2.8

42.3

31.3

76.6

S/A

KEY RESERVES %

4

Sherron Collins

G

5-11

205

So.

9.5

2.0

47.9

36.8

76.5

S/A

24

Sasha Kaun

C

6-11

250

Sr.

7.1

3.9

61.1

0.0

54.4

B/F

45

Cole Aldrich

C

6-11

240

Fr.

2.9

3.1

51.9

0.0

64.7

B/F

5

Rodrick Stewart

G

6-04

200

Sr.

2.9

2.3

49.3

31.3

60.7

Statistical Analysis

KU

Stat

Opp

Difference

50.8

FG%

38.0

12.8

40.1

3pt%

33.7

6.4

69.6

FT%

68.4

1.2

38.8

Reb

30.9

7.9

12.8

TO

15.8

3.0

6.0

BK

2.6

3.4

8.9

STL

6.2

2.7

18.4

AST

11.3

7.1

R+T  #

14.31

81.4

PPG

61.4

20.0

PiRate Score

21

Schedule Strength

.5594

NCAA Tournament Results

Portland State

85-61

UNLV

75-56

Villanova

72-57

I have to admit that Stephen Curry and company did something I didn’t think they could do-they blew Wisconsin off the floor Friday night.  I underestimated just how fluid the Wildcats play.  This is actually their third trip to the Elite 8, with the other two coming in 1968 and 1969 (they lost both times to North Carolina by one possession).

Kansas is the team to beat.  The Jayhawks can dominate the game at both ends of the floor and in the stat book,  as they showed against ‘Nova Friday night.  I believe the Jayhawk defense will be able to combat the numerous perimeter screens set and keep Curry from putting up numbers reminiscent of Austin Carr when he played in the NCAA Tournament for Notre Dame.

I’m going with the Jayhawks, because I think they are as good as any National Champion in the last quarter century.  Davidson won’t lose because they are a small school from the Southern Conference.  In my opinion any other team in the field would also lose if they played Kansas in the Elite 8.

Prediction: Kansas 75  Davidson 60

March 17, 2008

Bracketnomics 505–The Advanced Level Class In Bracket Filling

Filed under: College Basketball — Tags: , , , , , , , , , , , , , , , , , , , , , — piratings @ 8:50 am

Bracketnomics 505–The Advanced Level Class In Bracket Filling

This is a graduate level class that will earn you a Masters in Bracketnomics.  So you want a scientific method to guide you as you fill out your brackets?  You say you want a system that will take out most of the human-bias, and allow you to pick your teams in a mechanical fashion.  Well, I’ve got one for you that has been back-tested just like a stock-picking formula. 

What I’ve done is to discover the vital information that has worked in the past.  I’ve been using this formula since the Internet has made statistics-gathering easy, and it has been back-tested as far back as the days when the NCAA Tournament field consisted of 23, 24, or 25 teams.

 This method will not pick every game correctly and make you an instant millionaire.  It is geared toward finding the tendencies that historically have mattered most in picking the teams with the best chances of advancing.  Not all teams will be a perfect fit in this formula; what this formula does is pick the teams that have the best chance of advancing. 

 How has the formula performed in recent years?  Well, in 2006, it tabbed George Mason as a team to watch.  The Patriots fit the criteria.  While I picked GMU to make it to the Sweet 16, I’m not about to admit I selected them for the Final Four.  It did select Florida and UCLA for the Final Four the last two years.  There have been a couple of seasons where the criteria didn’t apply successfully, but over the course of 40 seasons, it has performed well about 34 times.  Without further adieu, here is the PiRate Bracket-Picking System.

1. Scoring Margin

Look for teams that outscored their opponents by an average of 8 or more points per game.  Make a separate list of teams that outscored their opponents by an average of 10 or more points per game and a third list of teams outscoring opponents by an average of 15 or more points per game.

 This is an obvious statistic here.  If team A outscores opponents by an average of 85-70 and their team B opponent outscores their opposition by an average of 75-70, team A figures to be better than team B before you look at any other statistics.  Going back 50 seasons, over 80% of the teams making the Final Four outscored their opponents by double digits, while the number outscoring opponents by eight points makes it a slam dunk.  In the days of the 64/65-team field, this statistic has become even more valuable.  It’s very difficult and close to impossible for a team accustomed to winning games by one to seven points to win four times in a row.  This average gives equal weighting to a team that outscores its opposition 100-90 as it does to a team that outscores its opposition 60-50.

2. Field Goal Percentage Differential

Take each teams’ field goal percentage minus their defensive field goal percentage.  Look for teams that have a +7.5% or better showing.  50% to 42% is no better or no worse than 45% to 37%.  A difference of 7.5% or better is all that matters.  Teams that have a large field goal percentage margin are consistently good teams.  Sure, a team can win a game with a negative field goal percentage, but in the Big Dance, they aren’t going to win four games much less two.  This statistic holds strong in back-tests of 50 years.  Even when teams won the tournament with less than 7.5% field goal percentage margins, for the most part, these teams just barely missed.  In the current field makeup, this stat has become a more accurate predictor.  Nowadays, the teams with field goal percentage margins in the double digits have dominated the field.

 3. Rebound Margin

This statistic holds up all the way back to the early days of basketball.  The teams that consistently control the boards are the ones that advance deep into the tournament.  What we’re looking for here are teams that outrebound their opposition by five or more per game.  In the opening two rounds, a difference of three or more can be used.

The reason this statistic becomes even more important in mid-March is that teams don’t always shoot as well in the NCAA Tournament for a variety of reasons (better defense, abnormal sight lines and unfamiliar gymnasiums, nerves, new rims and nets, etc.).  The teams that can consistently get offensive putbacks are the teams that fire out to the lead in these games.  The teams that prevent the opposition from getting offensive rebounds, holding them to one shot per possession, have a huge advantage.  Again, there will be some teams that advance that were outrebounded, but over the course of four rounds, it is rare for one of these teams to advance.  West Virginia in 2005 made it to the Elite Eight without being able to rebound, but not many other teams have been able to do so.  There have been years where all four Final Four participants were in the top 20 in rebounding margin.

4. Turnover Margin & Steals Per Game

Turnover margin can give a weak rebounding team a chance.  Any positive turnover margin is good here.  If a team cannot meet the rebounding margin listed above, they can get by if they have an excellent turnover margin.  Not all turnover margin is eqaul here.  A team that forces a high number of turnovers by way of steals is better than a team that forces the same amount of turnovers without steals.  A steal is better than a defensive rebound, because most of the time, a steal leads to a fast-break basket or foul.  When a team steals the ball, they are already facing their basket, and the defense must turn around and chase.  Many steals occur on the perimeter where the ball-hawking team has a numbers advantage.  So, I count a steal as being worth 1.33 rebounds. 

The criteria to look for here is a postive turnover margin if the team outrebounds its opposition by three or more; a turnover margin of three or better if the team outrebounds its opposition by less than three; and a turnover margin of five or more if the team does not outrebound its opponents.  Give more weight to teams that average 7.5 or more steals per game, and give much more weight to teams that average double figure steals per game.  A team that averages more than 10 steals per game will get a lot of fast-break baskets and foul shots.  In NCAA Tournament play, one quick spurt can be like a three-run homer in the World Series, and teams that either steal the ball or control the boards are the ones who will get that spurt.

Combining 3 & 4:  R+T margin is what I call this stat.  Consider this the basketball equivalent of baseball’s OPS (Onbase % + Slugging %).  Here is my R+T stat: R + (.2S * {1.2T}), where R is rebounding margin, S is average steals per game, and T is turnover margin.  When this stat is 5 or more, you have a team that can overcome a few other liabilities to win.  When the result is 10 or more, you have a team that has a great chance of getting enough additional scoring opportunities to make it to the later rounds.

5. Power Conference Plus Schedule Strength

I’m sure up to this point you have been thinking that it is much easier for Davidson and Gonzaga to exhibit these statistics than Pittsburgh or Kentucky.  Of course that’s correct.  We have to adjust this procedure so that the top conferences get extra weight, while the bottom conferences get penalized.  Here is how we do it.  Look at the Strength of schedule for every team in the Field.  You can find SOS on many websites, such as the RPI at cbs.sportsline.com.  Take the decimal difference for each team in the Field and multiply that by 100.  For example if Team A has a SOS of .6044 and Team B’s is .5777, the difference times 100 is 2.67.  So, Team A’s schedule was 2.67 points per game tougher than Team B.  Use this in head-to-head matchups for every game in  your bracket.

These are the five basic criteria I have used for the last dozen or so years.  You might be shocked to see that there are some key statistics that I don’t include.  Let’s look at some of these stats that I don’t rely upon.

Assists and Assists to Turnover Ratio

 While assists can reveal an excellent passing team, they also can hide a problem.  Let’s say a team gets 28 field goals and has 21 assists.  That may very well indicate this team can pass better than most others.  However, it can also mean two other things.  One, this team may not have players who can create their own offense and must get by on exceptional passing.  That may not work against the best defensive teams in the nation, or the type that get into the Dance.  Two, and even more importantly, it may indicate that this team cannot get offensive putbacks.  As I explained earlier, the offensive putback is about as important as any stat can be.  So, I only consider this stat if I have to decide on a toss-up after looking at the big five stats.

Free Throw Shooting 

Of course, free throw shooting in the clutch decides many ball games.  However, history shows a long line of teams making it deep into the tournament with poor free throw shooting percentages. 

Let’s say a team shoots a paltry 60% at the foul line while their opponent hits a great 75% of their foul shots.  Let’s say each team gets to the foul line 15 times in the game, with five of those chances being 1&1, three being one shot after made baskets, and seven being two shot fouls.  For the 60% shooting team, they can be expected to hit 3 of 5 on the front end of the 1&1 and then 1.8 of the 3 bonus shots; they can be expected to hit 1.8 of 3 on the one foul shot after made baskets; and they can be expected to hit 8.4 of 14 on the two shot fouls for a total of 15 out of 25.  The 75% shooting team can be expected to connect on 3.75 of 5 on the front end of the 1&1 and then 2.8 of 3.75 on the bonus shot; they can be expected to hit 2.3 of 3 on the one foul shot after made baskets; and they can be expected to connect on 10.5 of 14 on the two shot fouls for a total of 19.35 out of 25.75.  So, a team with one of the top FT% only scores nine more points at the foul line than a team with one of the worst.  That looks like a lot of points to make up, but consider that this is about the maximum possible difference.  Also consider that teams that shoot 60% of their foul shots and make the NCAA Tournament are almost always the teams that also have the top R+T ratings.  Teams that make the NCAA Tournament with gaudy free throw percentages frequently got their by winning close games at the line.  In the NCAA Tournament, fouls just don’t get called as frequently as in the regular season.  The referees let the teams play.  So, looking at superior free throw percentage can almost lead you down the wrong path.  Consider this:  The 1973 UCLA Bruins are considered to be the best college basketball team ever.  That team connected on just 63% of its free throws.  They had a rebounding margin of 15.2, and they forced many turnovers via steals thanks to their vaunted 2-2-1 zone press.  In the great UCLA dynasty from 1964 through 1973 when the Bruins won nine title in 10 years, they never once connected on 70% of their free throws and averaged 66% during that stretch.

3-point shooting

You have to look at this statistic two different ways and consider that it is already part of field goal percentage and defensive field goal percentage.  Contrary to popular belief you do not count the difference in made three-pointers and multiply by three to see the difference.  If Team A hits eight treys, while their Team B opponents hit three, that is not a difference of 15 points; it’s a difference of five in my opinion.  I consider made three-pointers one extra point because they are already figured as made field goals.  A team with 26 made field goals and eight treys has only one more point than a team with 26 made field goals and seven treys.

The only time I give three-point shots any weight in my criteria is when I am looking at a toss-up game, and when I do look at this stat, I am looking for a team that does not rely on them to win, but instead uses a credible percentage that prevents defenses from sagging into the 10-12-foot area around the basket.  If a team cannot throw it in the ocean from behind the arc, defenses can sag inside and take away the inside game.  It doesn’t play much of a role in the NCAA Tournament.  A team that must hit 10 threes per game in order to win isn’t going to be around after the first weekend.

One Big Star or Two Really Good Players

Teams that got to the Dance by riding one big star or a majority of scoring from two players are not solid enough to advance very far.  Now, this does not apply to a team with one big star and four really good players.  I’m referring to a team with one big star and four lemons and two big scorers with three guys who are allergic to the ball.  Many times a team may have one big scorer or two guys who score 85% of the points, but the other three starters are capable of scoring 20 points if they are called on to do so.  If you have a team with five double figure scorers, that will be a harder one to defend and one that will be consistent.  It’s hard for all five players to slump at once.

I hope this primer will help you when you fill out your brackets this week.  I will be previewing the first round games and applying this formula throughout the tournament.  I will preview the Play-in game Tuesday morning, and the rest of the first round some time Wednesday (it may be in the evening before I can get it posted).  

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