Comparison of Old & New R+T Ratings

We hope you read our piece earlier this week describing our updated R+T Rating for 2020.  If you didn’t, and if you are a new reader to the PiRate Ratings, after thanking you for stopping buy and remembering you are getting exactly what you paid for here, the following is a quick tutorial on what R+T Rating means.

1. The R+T Rating is a metric that applies only to the NCAA Tournament.

2. The R+T Rating attempts to estimate extra scoring opportunities by teams in NCAA Tournament games.

3. Over the last two decades when the needed statistics to calculate R+T Ratings, the National Champions and most of the Final Four teams rated near the top of the field in R+T Rating.  

4. The reason the R+T Rating is so important in the NCAA Tournament only is because the other metrics are better applied in an environment where half of the teams in Division 1 are below average offensively, while a separate half of the teams in Division 1 are below average defensively.  In the NCAA Tournament, almost all teams are above average offensively and defensively, so these extra scoring opportunities frequently are the difference.   It only takes one nice scoring spurt to win a tightly contested game in the Big Dance.

We used the same R+T Rating for almost two decades, only slightly tweaking the weighting for these stats.  The old R+T Rating, which we will continue to publish this year, is:

(R * 2) + (S * .5) + (6 – Opp S) + T

R = Rebounding Margin
S = Average Steals Per Game
T = Turnover Margin

This metric shows that rebounding margin is more important than turnover margin, but steals are more important than other types of turnovers.  The reason is that steals lead to the most potential points per possession.  When a team steals the ball, they are usually facing their own basket (whereas on a rebound, their backs are to their own basket).  The team committing the turnover by steal must do a 180° turn to defend, and the stealing team takes off on a fast break.

This R+T Rating helped us pick some big upsets for many years.  Teams with high R+T Ratings and adequate strengths of schedule advanced in the tournaments at the expense of teams with low R+T Ratings.  In multiple years, teams with negative R+T Ratings lost quickly in the Big Dance, even teams that were #2, 3, and 4 seeds.  We correctly picked two different Georgetown teams to be upset as heavy favorites, because those Hoya teams had negative or very low positive R+T Ratings.  For three years, we picked Vanderbilt to lose in the first game against underdogs because Vanderbilt also had negative or very low R+T Ratings.  At the other end of the spectrum, the team with the highest R+T Rating and a significantly strong schedule has cut down the nets multiple times.

If the R+T Rating has been an accurate predictor of potential NCAA Tournament success, why did we need to create a new version?  We did so, because the old version simply counted actual margins without concerning itself with possessions.  Rate stats are more accurate than counting stats.  As we have used as an example many times, a team that outrebounds its opponents 35-30 has done a better job than a team that outrebounded its opponents 43-37.  Strictly counting 43-37 is +6 and 35-30 is only +5, but 35-30 is 53.85% while 43-37 is 53.75%, so 35-30 is a tad better.  We want our stats to be as accurate as possible, so we switched to rate stats over counting stats.

But, we have an issue.  The variables now must change as well, because percentages are totally different from standard numbers.  We have tried to back-test the new variables and include a constant to try to make the outcome look the same but more accurate.

Here is the explanation for the new R+T Rating.

1. Use 4-Factors Rate Stats
A. Offensive Rebound %
B. Opponents’ Offensive Rebound %
C. Steal %
D. Opponents’ Steal %
E. Turnover %
F. Opponents’ Turnover %

2. Take the difference in each stat from the national average for each stat. There will be discrepancies in the offensive and defensive averages due to D1 vs. D2 games, so we set the national average from the mean of the offensive and defensive norms.
For example: O Reb% = 28.43 & D Reb% = 27.79, then the mean Reb% for Division 1 in 2020 is 28.1.

3. For Rebounding Rate Margin & Turnover Rate Margin take the sum of offensive and defensive rates and divide by 2.
Example: A team’s OReb Margin is +6.4% and DReb Margin is -1.2%. Reb Rate Margin would be +2.6%

4. We Keep Steal Rate Margins Separate as in original R+T.

5. The New Formula Now Becomes:

((R*8)+(S*2+((5-Opp S)*2)+(T*4)))/2.75

 

Here’s how we calculate a sample new R+T Rate.

The Big State University Pumas have these stats

Offensive Rebounding % = 34.8.  With a national Rebound % mean of 28.1, Big State’s offensive rebound rate margin is +6.7% (34.8-28.1)

Opponents’ Offensive Rebounding % = 28.6.  With a national Rebound % mean of 28.1, The defensive margin or Big State’s opponents offensive rebound margin is -0.5 (28.1-28.6)

Now we add the two margins and divide by 2  (+6.7 – 0.5) / 2 = 3.1

3.1 would be the new R number in the equation.

Big State has a steal rate of 10.6% and a defensive steal rate of 9.6%.  The national average steal rate is 9.2%.  

So, Big State’s S Rating would be +1.4 (10.6-9.2).  Their opponents’ S would be +.4% (in this case the higher the number, the worse off it is for the team).

Big State has a turnover rate of 16.8% and a defensive turnover rate of 18.2%.  The national average for turnovers is 16.9%, so Big State’s turnover rate margin would be 0.1%, and their defensive turnover rate margin would be 1.3%.

So Big State’s T Rating would be 0.7,  (.1+1.3)/2

Now we have all the numbers we need to plug into the calculation.

((R*8)+(S*2+((5-Opp S)*2)+(T*4)))/2.75

For Big State, the equation becomes:

((3.1 * 8) + (1.4 * 2 + ((5 – .4) *2) + (0.7 * 4)))/2.75 = 14.4

Big State’s R+T Rating would be 14.4, which is about average for an NCAA Tournament Team.  We must at this point look at their schedule strength to see if it merits worthiness against teams most likely to advance into additional NCAA Tournament rounds.

So, by now you are maybe wanting to see some real R+T Ratings?  We are going to show you both the old and new R+T Ratings for the current top 20 teams in the nation.

Here is the old R+T list with the schedule strength.  For schedule strength, 50.0 is average.  55.0 and higher means the team has played a tough schedule.  Below 45.0 means the team has played a weak schedule.  Usually national champions have a strength of schedule between 56 and 62, and most Final Four Teams have strengths of schedule between 52 and 62.

Old R+T

Team	R+T No.	SOS
Gonzaga	24.6	53.9
Houston	23.0	55.8
West Virginia	20.6	60.4
Kansas	17.0	62.3
Baylor	17.0	59.4
Duke	16.5	58.6
San Diego St.	15.9	53.6
Louisville	15.3	57.6
Colorado	14.4	57.6
Maryland	13.1	59.9
Florida St.	12.8	57.9
Butler	11.9	59.7
Kentucky	11.9	56.7
Penn St.	10.3	59.8
Dayton	9.4	54.4
Iowa	9.4	60.8
Marquette	8.1	59.8
Villanova	7.5	60.0
Seton Hall	4.9	60.4
Creighton	2.2	60.3

 

Looking at the old R+T, the Big East appears to be a bit overrated this year.  The four Top 20 teams with the lowest R+T Ratings are all Big East teams.

Until last night, Duke had a much more impressive R+T than they do today, but losing by 22 to North Carolina State, and getting outrebounded and committing more turnovers and having the ball stolen more against the Wolf Pack led to the Blue Devils dropping down to sixth.

Gonzaga’s R+T is about where it was when the Bulldogs advanced to the National Championship Game against North Carolina a few years back.  At the moment, their schedule strength is a tad too low, but GU has games remaining against Saint Mary’s and BYU and likely another game against one of the two in the WCC Championship Game.  The Zags’ SOS could move up a little.

 

 

New R+T Rating

 

Team	R+T Rate	SOS
West Virginia	26.5	60.4
Gonzaga	21.5	53.9
Houston	20.9	55.8
Baylor	18.7	59.4
Duke	18.3	58.6
Colorado	15.3	57.6
Kansas	14.4	62.3
Florida St.	12.7	57.9
San Diego St.	12.7	53.6
Louisville	11.9	57.6
Maryland	10.7	59.9
Iowa	9.6	60.8
Penn St.	8.6	59.8
Butler	7.6	59.7
Villanova	5.7	60.0
Marquette	4.1	59.8
Kentucky	3.8	56.7
Seton Hall	3.1	60.4
Dayton	1.6	54.4
Creighton	-5.5	60.3

 

The new R+T gives a little more credit to three of the Big East teams.  Obviously, lower possessions per game in the Big East are partly to blame for lower counting stats, but on the whole, this does not look like a great potential year for the Big East.

Look at the top four teams here.  All four are teams that are west of the Mississippi River.  There hasn’t been an NCAA Champion from west of the Mississippi River since Kansas in 2008.  There hasn’t been an NCAA Champion from west of the Rockies since Arizona in 1997.  Did you know that the last 11 NCAA Champions came from the Eastern Time Zone?  And, did you know that the last NCAA Champion from the Pacific Time Zone was UCLA in 1995?

PiRate Ratings College Basketball For February 19, 2020

Wednesday’s Games

 

Home	Visitor	Spread
Alabama	Texas A&M	13.1
American	Navy	4.9
Arkansas St.	UL Monroe	7.0
Bradley	Missouri St.	4.9
Cincinnati	Central Florida	11.2
Citadel	Chattanooga	-8.4
Colgate	Lehigh	15.3
DePaul	Villanova	-3.4
Drake	Valparaiso	2.4
Duquesne	George Washington	11.4
East Tennessee St.	Furman	4.6
Fresno St.	Air Force	6.2
Georgetown	Providence	4.8
Georgia	Auburn	-3.4
Houston	Tulsa	10.0
Houston Baptist	Abilene Christian	-10.7
Incarnate Word	McNeese	-7.3
La Salle	Fordham	7.6
Lafayette	Boston U	-0.3
Louisville	Syracuse	10.0
Loyola (Chi.)	Illinois St.	11.4
Loyola (MD)	Army	2.6
Memphis	East Carolina	15.8
Mercer	Samford	7.5
Minnesota	Indiana	4.9
Mississippi St.	South Carolina	5.5
North Carolina St.	Duke	-8.4
North Dakota	South Dakota St.	-4.1
Northwestern St.	Nicholls St.	-4.3
Richmond	George Mason	11.8
Rutgers	Michigan	1.2
Sam Houston St.	Lamar	8.8
San Jose St.	Boise St.	-11.5
Seton Hall	Butler	5.7
Siena	Iona	7.0
South Dakota	North Dakota St.	0.3
Stephen F. Austin	Central Arkansas	14.0
Texas	TCU	4.1
Texas Tech	Kansas St.	12.0
Tulane	SMU	-6.1
UC Irvine	Long Beach St.	15.7
UMKC	California Baptist	-0.2
UNC Greensboro	Wofford	10.1
Utah St.	Wyoming	21.1
Virginia	Boston College	11.6
Virginia Tech	Miami	4.9
Wake Forest	Georgia Tech	1.3
Washington St.	California	6.6
Western Carolina	VMI	9.5

 

Wednesday’s Key TV Games

 

Time (EST)	Network	Home	Visitor
6:30 PM	FS1	Seton Hall	Butler
7:00 PM	ESPN	Louisville	Syracuse
7:00 PM	BTN	Rutgers	Michigan
7:00 PM	ESPN+	East Tennessee St.	Furman
8:00 PM	ESPN3	South Dakota	North Dakota St.
8:30 PM	FS1	Georgetown	Providence
9:00 PM	ESPN	North Carolina St.	Duke
9:00 PM	ESPNU	Houston	Tulsa
9:00 PM	BTN	Minnesota	Indiana
9:00 PM	SECN	Mississippi St.	South Carolina

In Order To Perform A More Perfect Metric

 

If you follow this website on a semi-regular basis, you know that our R+T Rating has been the one unique metric used by us when predicting NCAA Tournament favorites.

For those of you that are new to this site, our R+T Rating was created two decades ago to estimate the extra scoring opportunities (by points) each team might be better than average in the NCAA Tournament.  We realized long ago that just like the “Money Ball” type of baseball strategies did not work well in the Major League Playoffs, the NCAA Tournament presented its own unique differences and required more than the Four Factors to determine winners when only the good to great teams remain.

The current formula for R+T consists of counting stats, but we have realized for some time that rate stats are much more accurate.  Using baseball as an example, a counting stat would be Johnny Horsehide hitting 43 home runs and driving in 118 runs.  These two stats might lead the Majors, but these stats may not reveal what we want them to reveal.  Gary Goodeye might hit just 34 home runs and drive in 95 runs, but Good Ole Gary might be a better home run hitter than Johnny.  How many times did Horsehide come to the plate?  What if Horsehide walked 34 times in 702 plate appearances while playing for a team that had three all-stars hitting in front of him, all of whom have on-base percentages of .400 or better?

What if Goodeye had 650 plate appearances playing on a team that was quite weak offensively?  Let’s say his teammates that batted in front of him had one-base percentages between .320 and .335.  Let’s say that Goodeye didn’t always get good pitches when he appeared in the batter’s box, and he walked 125 times.

Now, if we look at the number of home runs hit per at bat or plate appearances that did not end in a walk (or hit by pitch or sacrifice), we will see that Goodeye actually hit home runs at a slightly better rate than Horsehide.  As for runs batted in, that statistic is close to meaningless, because in order to drive runs in, runners must be on base.  So, the RBI stat is more reliant on the other players on the team.  It could be that Goodeye drove in runners better than Horsehide, because when we look at how many runners were on base and what base they were on, Goodeye might have had a better percentage at driving those runners in.

Back to basketball.  A team with a rebounding advantage of 43-37 has a +6 margin.  A team with a rebounding advantage of 35-30 has a +5 margin.  Using counting stats, the 43-37 team is one better than the 35-30 team.  But, the 35-30 team rebounded 53.85% of the missed shots, while the 43-37 team only rebounded 53.75% of the shots.  So, the 35-30 team is a little better than the 43-37 team on the surface.

However, it is harder to get offensive rebounds than it is to get defensive rebounds.  In fact, data throughout the calculated history of college basketball shows that an offensive rebound is worth better than 2 1/2 defensive rebounds.  The Four Factors breaks rebounding rate down into offensive and defensive rates.  

Let’s say that in a game,  Team A shot 25 of 60 for 41.7% while shooting 16-22 at the foul line for 72.7%.  Team B shot 28 of 58 for 48.3% while shooting 10-17 at the foul line for 58.8%.  Team A hit one more three point basket than Team B and one by a point.  

Now, let’s look at the rebounding for this game.  First, there were five dead ball rebounds, which we do not count as actual rebounds.  The statistical rules in basketball is that for every missed shot, there must be a rebound.  When a player is at the foul line for two shots, and he misses the first shot, there is not a real rebound.  The foul shooting team gets credited with a dead ball rebound.

To the contrary, team rebounds do count, because these are rebounds in which possession is determined.  When a missed shot ends up out of bounds before possession can be guaranteed, the team that gets possession out of bounds receives an offensive rebound.

In this game after removing the five dead ball rebounds, there were 73 rebounds to be had.  When Team A shot, there were 39 potential rebounds following misses, while when Team B shot, there were 34 potential rebounds following misses.

Looking at the stats, Team A finished with 13 offensive rebounds and 23 defensive rebounds for 36 total rebounds.  Team B finished with 11 offensive rebounds and 26 defensive rebounds for 37 total rebounds.

Team B had a counting rebounding margin of +1, while Team A had a margin of -1.  However, let’s now look at the percentage of offensive rebounds each team enjoyed.  Team A had 13 offensive rebounds out of 39 missed shots, which is 33.3% of the missed shots at their offensive end.  Team B had 11 offensive rebounds out of 34 missed shots for 32.4% of the missed shots at their offensive end. 

Looking at the rate stats, Team A may have retrieved fewer total rebounds than Team B, but they were actually the better rebounding team in this game by almost 1%.

The rate data is obviously more telling than counting data, but how can we determine a point value to substitute rate data for counting data in our R+T Rating, which in the past has picked a lot of surprise NCAA Tournament winners?

We’ve been back-testing values daily for two months.  We had to include a constant in our formulas to smooth out the results to make the numbers mean something.  Without the constant, the results were too far apart to mean something.  Tiny differences led to major spreads, and that did not tell us what we wanted.  

After about 150 to 175 different attempts, we believe (HOPE) that we have finally had a breakthrough.  The following formula will be explained after we reveal it:

((R*8)+(S*2+((5-Opp S)*2)+(T*4)))/2.75

 

This formula now refers to Rate Stats.  The “R” in the formula now stands for Rebounding Rate.  This is a combination of both offensive and defensive rebounding rate and it is a deviation from the norm and not just a percentage.  The norm in our experiment is 28.1%.  If a team has an offensive rebounding rate above this number, it is above average, and if it is below this number, it is below average.  Thus, the norm for defensive rebounding rate is the opposite of the above number, or 71.9%.  We then calculate our R part of the formula by taking each team’s offensive rate minus 28.1 plus their defensive rate minus 71.9 and then add the two results and divide by 2.

Example: Today, Houston has an offensive rebounding rate of 38.5%, which is 10.4% higher than average (we experimented with using the actual percentage better which would have been 37% better than average, but we never arrived at a usable final number doing so.)  Houston’s defensive rebounding rate is 74.5%, which is 2.6% better than average. 

We then take both numbers (+10.4 & +2.6), sum the numbers, and divide by 2 to get +6.5.  That would be the R number for Houston in the new formula.

Let’s now update our formula:

((6.5*8)+(S*2+((5-Opp S)*2)+(T*4)))/2.75

 

The rest of this formula uses the same system as above.  The norm for steals (S) is 9.2% for both offense and defense.

Houston has a 7.4% steal rate, which is 1.8% below average.  Houston’s opponents have a 7.5% steal rate against them, which is 1.7% above average for Houston.  Once again, we update the formula.

 

((6.5*8)+(-1.8*2+((5- [-1.7])*2)+(T*4)))/2.75

 

Now, we need Turnover rates, both offensive and defensive.  The norm for turnover rate is 16.9%.  Obviously, the lower the offensive turnover rate is, the better, and the higher the defensive turnover rate is, the better.  Houston’s offensive turnover rate is 14.9%, which is 2.0% better than average.  The Cougars’ defensive turnover rate is 15.8%, which is 1.1% below average.  We sum the two numbers and divide by 2:  2.0 + (-1.1) = 0.9 and divided by 2 = 0.45.  The 0.45 is now our T in the equation and we are ready to solve the equation.  The 2.75 by the way is our constant that when used brings the results into what we hope is a usable formula.

 

((6.5*8)+(-1.8*2+((5- [-1.7])*2)+(.45*4)))/2.75

 

We will simplify the formula in case you have math anxiety like one of our PiRate lasses.

 

((52)+(-3.6+(6.7*2)+(1.8)))/2.75

 

(52+9.8+1.8)/2.75

 

63.6/2.75 = 23.13

 

We will have some growing pains with this new formula, and there’s a good chance that the numbers will be tweaked in the future, but this is the Rate Version of the R+T Rating that we will use in the NCAA Tournament.  Because it is an experiment, we will also use the original R+T formula when we issue our Bracketnomics 2020 edition.

 

Here are the two formulas together for you to compare.

 

Original R+T using actual counting margins and averages

 

(R * 2) + (S * .5) + (6 – Opp S) + T

R = Rebounding Margin
S = Average Steals Per Game
T = Turnover Margin

 

New Experimental R+T using rate the percentage number difference from the norm

 

((R*8)+(S*2+((5-Opp S)*2)+(T*4)))/2.75

The 2020 Norms

Offensive Rebounding:        28.1%

Defensive Rebounding:       71.9%

Steals (O&D):                         9.2%

Turnovers (O&D)                16.9%

 

 

 

 

 

Bracketnomics 2019: Picking The Bracket

Here it is!

I’ve always wanted to post those words.  As a fanatic of the old Mother Road, Route 66, those three words have a special meaning.  In the “good ole days,”  The Jack Rabbit Trading Post near Joseph City, Arizona, used those three words to advertise that after miles of driving and seeing numerous signs for this tourist stop, they had finally arrived.

Like those Mother Road drivers, it is my hope that I have finally arrived at a successful system, one that will pick a large percentage of winners in the Big Dance.

The PiRate Ratings Bracketnomics System has been successful in the past–very successful.  Then, again, there have been major bust years, where throwing a dart at a dartboard with team names would have been just as reliable.

Numerous revisions to the system have brought me to settle on what you might have read yesterday, the Bracketnomics Tutorial, which you can read here:

https://piratings.wordpress.com/2019/03/18/bracketnomics-2019-picking-your-brackets/

Today, I will attempt to interpret that data from the tutorial and select a bracket based on the statistics.  This is a 100% mechanical process with no objectivity.  If you believe in 100% mechanical stock investing, then this publication is totally for you.  If you are more of a hunch player, then you will need to alter this information to better fit your beliefs, but at least let our data be a dissenting view when you consider your choices.

This post will pick all 67 games, including the games in Dayton that 99% of the bracket pools do not include.  I will pick each round today.

After the conclusion of each round, I will then post an updated bracket to assist all of you that play in a pool that allows you to pick new winners after each round.

Remember, this is still a system in its infancy with growing pains.  What I have tried to do is isolate through back-tested methods similar statistical data that past Final Four and National Championship teams possessed.

For instance, almost every national champion has possessed a scoring margin of 8 points  or better, and a large majority had double-digit scoring margins.  Almost all national champions have come from one of the “Power Conferences” or in the past were one of the top 10 Independents when there were more than 30 teams not in a conference.

Very few teams have ever made the Final Four with a negative rebounding margin, but considerably more had negative turnover margins.  At the same time, a lot of these teams had high steals per game averages, even if their turnover margin was negative.

One final factor I like to look at is style of play.  Most National Champions have been up-tempo teams that run the fast break, play some form of pressure defense (not necessarily full-court), and moves the ball quicker than average in the scoring zone.  This is not 100% exclusive.  Some patient teams that play a non-gambling style of defense have made the Final Four and a couple even won the tournament, but the trend is to go with the team that has the better chance of going on a scoring run with a 10-point or better spurt.  History shows that teams that play like North Carolina and Duke tend to get these spurts more frequently than teams like Virginia and Kansas St.

Let’s take a look at the data, starting with the First Four games in Dayton.

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Prairie View A&M	43.07	-2.7	30.0	66.1	15.2	21.7	-3.8
Fairleigh-Dickinson	43.31	5.2	28.9	68.1	17.1	18.1	-2.4

This is an excellent example for the first game of the tournament.  SOS (Strength of Schedule) is dead even, so the rest of the stats are 100% comparable.  FDU will more than likely have the better shooting night.  Rebounding should be about even, and Prairie View will more than likely force FDU into a few more mistakes than they normally commit.  Because both teams possess R+T ratings below zero, these are two 16-seeds that are going nowhere for sure.  The winner will be a blowout victim Thursday.  This is about as tossup as you can get.  I’ll go with the team with the better, but terrible R+T Rating and select

Fairleigh-Dickinson

 

Team

SOS

TS Marg

OReb%

DReb%

TOV%

DTOV%

R+T

Temple	54.13	0.5	26.0	71.1	13.8	18.1	-3.1
Belmont	48.60	9.7	25.6	76.4	13.8	14.8	6.0

Temple has the stronger schedule by about 5.7 points per game.  Thus, the system calls for Temple’s stats to carry stronger weight than Belmont’s stats.  Temple faced better defensive teams on average than Belmont, but not enough to counter a difference of 9.2%.  Temple will have marginal rebounding advantages on both sides of the floor, but the Owls have a negative R+T.  Belmont’s R+T rating is good enough to win early, and even though the Bruins are 0-7 in past NCAA Tournaments, their mechanical data show that they are the better team.  It could be one little spurt in the second half that wins this game.

Belmont

 

Team

SOS

TS Marg

OReb%

DReb%

TOV%

DTOV%

R+T

North Carolina Central	39.47	3.5	35.1	73.7	19.0	17.3	8.2
North Dakota St.	47.57	3.4	20.9	75.7	14.3	13.2	-6.1

UNC Central has the weakest SOS in the entire field, and there isn’t another one even close.  North Dakota State has an R+T rating that is near the bottom of the field, one that in the past has never won more than one game in a Dance.  Once again, these are two 16-seeds that have no chance against a 1-seed.  I’m not sure they could beat any of the 15-seeds.  This one is a difficult choice–the weakest schedule or the worst R+T score.  Because I expect very low shooting percentages in this game, I will take the team likely to get the most second chance points.

North Carolina Central

 

Team

SOS

TS Marg

OReb%

DReb%

TOV%

DTOV%

R+T

St. John’s	55.79	-0.2	21.3	70.3	12.8	18.3	-8.0
Arizona St.	55.20	2.3	32.4	73.6	15.9	16.7	6.8

Once again, we have teams with identical SOS, which makes the selection a lot easier.  St. John’s has the second worst R+T rating in the entire field.  Case closed right away.  Arizona State will enjoy at least one big run in this game, and the Sun Devils will put this game away at that point.  This has the looks of a potential blowout win.

Arizona State

 

Team

SOS

TS Marg

OReb%

DReb%

TOV%

DTOV%

R+T

Louisville	61.61	6.1	29.2	74.2	15.5	14.3	2.9
Minnesota	59.44	1.8	31.7	72.2	15.0	14.5	1.1

Louisville’s schedule is marginally tougher, so they will get a slight upward adjustment  in their data.  The Cardinals have a clear advantage in true shooting margin and an ever so slight R+T advantage.  This makes it 3 for 3 in Louisville’s favor, but it’s three slim advantages.  The Cards are the slim favorite according to the data.

Louisville

 

Team

SOS

TS Marg

OReb%

DReb%

TOV%

DTOV%

R+T

LSU	58.56	3.2	37.3	69.6	15.3	18.0	10.1
Yale	49.95	8.8	26.0	75.9	16.1	13.5	3.6

Note:   Unless something changes, LSU Coach Will Wade is still suspended and will not coach this game.  My system has no contingency to adjust LSU’s stats.

LSU’s SOS is almost nine points stronger, so their numbers must be improved.  Thus, the Tigers have a slightly better TS%, a much better rebounding advantage, and a considerably better R+T rating.  Yale might keep it close for some time, but LSU will enjoy a killer scoring spurt to put this game away.

LSU

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Auburn	59.71	1.8	33.0	68.0	14.7	22.0	3.9
New Mexico St.	48.05	4.8	36.8	79.0	14.5	17.6	18.7

This is going to be a game you will want to watch, even if you have no dog in this fight.  I expect the teams to top 75 possessions in this game.  Two of the top 20 coaches in college basketball will face off, and Aggie head coach Chris Jans should be on the radar of some power conference teams looking for a new coach.

Auburn has a large SOS advantage of 11.66 points per game, which is prohibitive.  The TS margin, offensive rebounding advantage, and R+T numbers heavily favor NMSU, and the Aggies have the top R+T rating in the tournament.  However, with a SOS advantage of almost a dozen points, Auburn will win the turnover battle, and NMSU’s rebounding advantage will be heavily tempered.  Score one for the SEC, but it would not be a shock if New Mexico State makes this a close game and even has a chance to win.  The Aggies should be considered as one of your potential upset teams, but I think there are better upset chances in this round.

Auburn

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Vermont	46.62	6.5	27.8	78.8	14.4	17.8	8.8
Florida St.	59.87	3.5	33.1	73.1	16.5	18	8.3

It is rare to see a Round of 64 game where the SOS difference is 13+ points and it isn’t a 1 vs. 16 or 2 vs. 15 game.  Florida State’s superior schedule makes the relatively equal numbers in the other data inconsequential.  If you are into horse racing, you know doubt know how often a non-winner of two lifetime races enters a graded handicap and beats a classic champion horse.  Vermont is the three year old that won a race against other non-winners and then entered a Graded stakes race against four and five year old horses, some of which were contenders in the Derby when they were three.  Class wins horse races, and it wins NCAA Tournament games when the upstart isn’t the next Justify.  Vermont isn’t a Justify.

Florida State

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Michigan St.	61.44	13.8	33.9	73.4	16.2	12.8	11.7
Bradley	48.52	1.7	27.4	73.8	16.8	16.5	-0.5

This game has the same issue that the previous game has, but the data is even more biased in favor of the better team.  Michigan State could start its second five in this game and probably win.  Bradley will have to settle for being glad they got to Dance.  If Tom Izzo wanted to do so, he could run up the score to a 40-point victory.  Sparty has a chance to go deep into this Tournament with their superior numbers.  Only an inability to force turnovers might eventually end their run.

Michigan State

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Maryland	59.76	7.4	33.9	75.3	17.0	12.5	8.6

Temple	54.13	0.5	26.0	71.1	13.8	18.1	-3.1
Belmont	48.60	9.7	25.6	76.4	13.8	14.8	6.0

In most of your pools, you get a free pass on the play-in games, but some of you might actually have to select these games.  Thus, I am showing you both of the teams Maryland could face.

Against Temple, the Terps have a slight SOS advantage and a humongous R+T advantage.  This system’s rule of thumb is to play against teams with a negative R+T rating.

Against Belmont, the Terps have a large SOS advantage, while the remaining stats are rather close.  This system’s other rule of thumb is to play the team with the superior SOS in this case.  So, the outcome should be the same no matter which team Maryland plays.

Maryland

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Kansas	62.55	5.5	29.7	71.6	16.1	15.7	1.9
Northeastern	51.11	6.7	22.7	75.7	15.1	14.9	-1.9

Kansas is not destined for a long stay at this cotillion.  The Jayhawks do not have the spurtability needed to win in the later rounds, but for this round, KU will feast on second chance points and take advantage of a Northeastern defense incapable of stopping a Big 12 offense.  This has the makings of a 20-point win.

Kansas

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Marquette	57.57	8.9	29.1	73.7	17.0	14.5	2.4
Murray St.	47.53	10.6	32.0	70.7	14.7	17.2	7.8

The old system had an assumption that a team with one star and average teammates rarely advanced far in the tournaments.  Remember, Michael Jordan and Stephan Curry played for teams with very good talent.  Jordan had Sam Perkins and James Worthy for teammates.

Ja Morant qualifies as one fantastic star, while the rest of his team is slightly above average but not in the Davidson mold when Curry and crew went to the Elite 8.

Marquette’s stats are not great.  The Big East was a bit weaker than normal this season, so MU is not a team to advance very far in your bracket, and in Markus Howard, you have one big star.  The difference is that the Golden Eagles have four well-above average players rounding out their starting lineup and a very good sub.

Murray State has an upset chance in this game, but when you break it down closely, Marquette should have a little more in the tank in the final minutes.  If you are looking for upset possibilities, this could definitely be put in that category, but it looks like Marquette is just good enough to avoid an upset.

Marquette

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Nevada	52.55	9.0	26.5	75.4	12.7	17.1	7.0
Florida	59.80	1.2	31.1	68.3	15.5	19.4	-0.5

This is your first big upset possibility in the games previewed so far.  Florida has a seven-point SOS advantage, but is is not enough to overcome their deficiencies in the other statistics.  Nevada coach Eric Musselman is, in my opinion, the best college basketball coach in the nation today, better than Mike Krzyzewski, Roy Williams, and Jay Wright.  If UCLA is not seriously looking at him for their vacancy, they are making a monumental mistake.

Let’s look at the data.  Nevada will take more intelligent shots than Florida, other than when the Gators get a couple of cheap baskets on offensive rebounds.  The Gators’s pressure defense will not be all that effective, and Florida has shown a propensity to make crucial mistakes in the final minutes of games.  This isn’t part of the criteria per se, but it shows in their turnover percentage, and their negative R+T rating,  and the criteria does say to play against a negative R+T.

Nevada

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Kentucky	60.54	9.5	36.5	74.2	15.9	16.1	15.4
Abilene Christian	42.42	4.3	29.4	73.3	15.5	21.7	5.9

Under John Calipari, Kentucky has shown a tendency to emulate their 1958 National Champions.  Adolph Rupp’s “Fiddlin’ Five” frequently allowed an opponent to enjoy a small lead, and then like a lightning flash make a big run to decide the outcome.  The Wildcats of 2019 have displayed this characteristic more times than not.

Abilene Christian isn’t a terrible team.  They earned their invitation by sweeping the regular season and conference tournament in the Southland Conference.  However, their data is not comparable when past Southland power Stephen F. Austin won in the Dance.  This game is a mismatch, and once the Wildcats stop fiddlin’, they will run away from the other Wildcats.

Kentucky

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Villanova	58.16	5.0	31.1	72.6	14.2	15.4	3.5
Saint Mary’s	55.33	5.1	31.2	76.8	14.1	14.7	9.6

In my opinion, this should be a great game to watch.  The teams are fairly evenly matched.  Villanova’s SOS is marginally better, while SMC has the better R+T Rating.  Both teams rely on offensive rebounding to score a good bit of their baskets, and Saint Mary’s has the ability to limit Villanova’s offensive rebounding.  It comes down to R+T rating.  The Gaels have a slight advantage over the defending national champions.  I consider this a 50-50 game, but the data says to take the Gaels.

Saint Mary’s

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Gonzaga	56.14	17.7	30.6	72.9	12.8	16.5	14.3

Prairie View A&M	43.07	-2.7	30.0	66.1	15.2	21.7	-3.8
Fairleigh-Dickinson	43.31	5.2	28.9	68.1	17.1	18.1	-2.4

There is no need to preview this.  Maybe, if the game was just five minutes long, Gonzaga would have a 2% chance of being upset.  However, over 40 minutes, the only upset will be if the Bulldogs fail to win this game by more than 30 points, no matter which of the two 16-seeds wins in Dayton.

Gonzaga

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Michigan	60.07	8.4	24.0	75.0	12.0	16.1	3.2
Montana	46.25	5.4	27.0	75.3	15.5	17.5	4.7

A lot of fans and so-called pundits believe Montana has a serious upset chance in this game.  The data here disagrees.  Michigan’s SOS is so much stronger, almost 14 points per game.  The Wolverines’ TS Margin is much better thanks to a superior defense, and the Maize and Blue limit mistakes.  I believe this game has more chance to be a blowout than to approach tossup status and look for the Wolverines to win by double digits.

Michigan

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Wofford	52.24	7.9	33.1	76.6	13.6	18.2	14.3
Seton Hall	58.56	0.5	29.5	70.6	15.2	17.4	-0.6

It’s always a bit scary to look at a Mid-major favorite and go with the chalk.  Is Wofford as good as advertised?  I have seen them play about five times this year, and they have an incredible inside-outside offensive game combined with an above-average defense.

Seton Hall’s advantage rests in their SOS superiority, but the Big East was not a beast this year.  The Hall only has a minor advantage here.  In every other data point, the Terriers look like pit bulls in this game, and Seton Hall has a negative R+T rating.

Wofford

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Purdue	60.84	2.3	34.9	73.5	13.5	17.2	11.4
Old Dominion	48.87	1.3	32.3	75.2	15.1	16.3	8.4

Purdue has been one of the biggest disappointments in NCAA Tournament history ever since Joe Barry Carroll led the Boilermakers to the 1980 Final Four.  Purdue has been upset numerous times in nearly 40 years.  This system doesn’t consider that to be a factor.  However, many of those Purdue teams lacked the R+T Rating advantage.  This one does.  Purdue has a strong SOS and a double-digit R+T.  Ironically, where the Boilermakers have been historically strong, TS% margin, they are rather mediocre there this year.

Old Dominion is a solid team from an average conference.  Their only liability is an equally mediocre TS% margin, and their SOS is a tad below average.  Look for the Big Ten to pick up a win, but at some point PU will stink in a game and fail once again to reach the Elysian Fields otherwise known as Minneapolis.

Purdue

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Syracuse	59.55	1.6	30.1	66.6	15.8	19.7	-3.7
Baylor	58.27	1.3	38.0	71.3	16.5	16.1	9.1

This should be another interesting game to watch, and it should be close.  Syracuse’s 2-3 matchup zone can be hard to attack without a lot of experience facing it, so the Orangemen frequently outperform their statistics in the Big Dance.  Baylor frequently plays better in the tournament than they do in the regular season with athletes that have free reign to shine.

The numbers show one glaring liability.  The ‘Cuse have a negative R+T rating, something rarely seen in a Jim Boeheim team.  Syracuse usually rebounds quite well out of their zone, but not so this year.  Baylor has one of the best offensive rebounding numbers in the field, so the Bears have the best chance to exploit a weakness in this game.

Baylor

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Cincinnati	55.48	2.9	37.2	70.9	13.4	18.2	12.9
Iowa	58.09	4.5	30.0	70.9	15.0	16.1	-0.4

In recent years, Cincinnati has owned criteria that yell Elite 8, even Final Four worthy, but the Bearcats never come through.  This isn’t their best team in recent years, so it figures that Cinti is prone for an early exit, even though the Bearcats are playing close to home.

Iowa peaked in the middle of the season and hasn’t been the same since January.  The Hawkeyes have a slight edge in SOS and TS% margin.  Cincinnati has such an incredible edge in R+T, and Iowa’s R+T is negative.  This is enough to advance the Bearcats to the Round of 32.  I expect Cinti to get double-digit offensive rebounds and force about 15 turnovers on the Hawkeyes.  That should lead to at least one big scoring spurt.

Cincinnati

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Ole Miss	58.28	3.2	30.4	70.5	16.0	18.2	2.8
Oklahoma	60.26	4.6	26.1	72.3	15.4	15.1	-2.5

What we have here are two swooning schools.  Both teams looked like sure Sweet 16 teams into mid-January.  Since then, both teams have struggled.  The winner is almost assuredly going home after the next round.  As far as this game goes, Oklahoma has that nasty negative R+T rating, and I just cannot pick a team with a negative R+T to win unless their SOS is far superior.  Two points is not that far.

Ole Miss

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Texas Tech	58.01	9.8	28.5	71.4	16.1	20.0	4.6
Northern Kentucky	46.39	6.6	31.0	74.1	15.4	16.8	7.1

This is Northern Kentucky’s second ever NCAA appearance.  Their original appearance resulted in a single-digit loss to big brother Kentucky.  This team is about as good as that team, while this Texas Tech teams is not as good as that Kentucky team.  Of course, the Norse were super fired up to face the Wildcats, and they got their moral victory.

This time, I expect the data to mean much more.  Texas Tech has a whopping SOS advantage of almost 12 points per game.  They have a much better TS% margin when the SOS is handicapped, and even though NKU has a higher R+T number, when you handicap it to SOS, the Red Raiders actually have the advantage here, and I expect TTU to force NKU into up to five more turnovers than they average.

Texas Tech

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Kansas St.	58.91	1.4	27.9	74.5	15.1	20.3	3.5
UC-Irvine	47.26	6.6	34.3	73.6	14.9	14.7	12.2

Kansas State is one of those teams on my radar to be a potential upset victim.  Having watched UC-Irvine’s Big West Conference Tournament games, I think they have a shot in this game.

The issue is the SOS numbers.  The Wildcats’ schedule was more than 11 1/2 points stronger per game.  UCI’s toughest opposition the entire season was at home against Utah State, and the Aggies slaughtered the Anteaters by 24 points.  UCI did win at Saint Mary’s.

Kansas State has one big asset–their ability to force turnovers.  The Wildcats are not particularly strong on offense.  There Wildcats play a very patient offense and try to limit possessions, but there are nights where this strategy plays into the oppositions’ hands.  Irvine plays patient, smart basketball and will feel right at home in a 60-65 possession game with less than 120 total points.  Kansas State might have the overall better athletes, but UC-Irvine has a hot coach in Russ Turner, a man tutored by Mike Montgomery with a little Don Nelson in his background.  Here’s a 13-seed that I believe can win an opening game.  It’s a tossup.  Go with the team you believe in your mind and heart should win, because I debated this one for 30 minutes before deciding and to be quite honest, I am not sure I can really determine the superior team according to my system.

UC-Irvine

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Tennessee	59.65	9.7	31.3	70.0	13.9	15.8	5.3
Colgate	47.05	5.7	29.6	73.9	16.7	15.6	3.2

There isn’t much need to discuss much in this game–it’s a mismatch.  Tennessee has slightly better criteria stats than Colgate, and when you add a better than 12 1/2 point superiority per game in SOS, you are looking at a potential 20-30 point win.

Tennessee

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Gardner-Webb	45.44	8.8	24.8	70.2	14.7	16.4	-1.8
Virginia	60.36	13.2	29.9	74.1	12.8	15.6	9.6

Gardner-Webb is not in Baltimore County.  Additionally, the Bulldogs do not have the criteria that UMBC had at this time last year.  GWU has a negative R+T rating, and against the Pack Line defense, they will not get the crucial second chance points on offensive rebounds.  Virginia will control the boards and commit few turnovers.  How do you beat the Cavaliers without winning the rebounding and/or the turnover margin?  UVA will wash that bad taste of 2018 out of their mouths with an ugly final score in the neighborhood of 75 to 50.

Virginia

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Buffalo	53.41	6.0	31.8	73.8	13.5	18.2	10.3

St. John’s	55.79	-0.2	21.3	70.3	12.8	18.3	-8.0
Arizona St.	55.20	2.3	32.4	73.6	15.9	16.7	6.8

Bully for Coach Nate Oats.  He signed a lengthy contract extension to stay in Buffalo, when a lot of other schools were ready to pound on his door.  It makes me wonder if Buffalo has designs on maybe campaigning for a spot in a future expanded American Athletic Conference, with excellent football and basketball programs more than ready to move up.

I expect the Bulls to be facing Arizona State in this game, but let’s for a moment look at the possibility that St. John’s wins in Dayton.  With an R+T rating of -8.0, the rules of this system is to continue to play against this team unless the opponent has an incredibly low SOS, well below 45.00.  Buffalo’s SOS is about where previous Mid-Major Final Four teams George Mason, Wichita State, and Virginia Commonwealth were.  So, if St. John’s advances out of Dayton, go with Buffalo to beat their in-state rival by double digits.

Against Arizona State, this is a much more even game.  Buffalo enjoys only a very slight advantage, making this basically a 50-50 game.  The Bulls have been a little more consistent all season, while ASU has been up and down.  The data says that Buffalo is maybe a 51% chance to be the winner.

There is one other factor in this potential game, and it is not part of the criteria, but the fabulous Buffalo senior class that put this team in the top 20 were recruited by current Sun Devil Coach Bobby Hurley.

Buffalo

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Wisconsin	60.91	6.5	24.0	73.5	12.8	15.0	-1.2
Oregon	55.13	3.8	29.6	71.9	15.5	18.3	4.6

When McDonald’s All-American Bol Bol went out for the season after nine games, it looked like it was Duck Season, and the Pac-12 was full of Elmer J. Fudd hunters on the hardwoods.  Give Coach Dana Altman the utmost respect for making the necessary adjustments when he lost his 5-star stud.  His number two 5-star player, Louis King, was not ready to star when the season began.  As the season progressed, King got better and better.

Wisconsin has a slightly better SOS and TS% Margin.  Rebounding is about equal.  However, The Badgers have a negative R+T rating.  Thus, we go against UW more than in favor of Oregon.

Oregon

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Utah St.	52.13	8.7	32.0	77.8	15.5	15.5	14.8
Washington	55.60	4.4	29.5	65.7	17.4	20.5	-3.6

Utah State might be a dangerous dark horse this year!  They have the criteria resume of a Gonzaga in previous years before Mark Few took the Bulldogs to the Championship Game.  I am not predicting USU to make the Final Four this year, but they might make the second weekend.

In this game, Washington is another one of those teams with a negative R+T rating.  While, I am a bit worried that so many teams made the field this year with sub-zero R+T ratings, until one of these non-spurtable teams get to the Elite 8, they will not have my support.

Utah State

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Duke	63.09	10.3	36.1	70.4	15.0	17.1	12.1

North Carolina Central	39.47	3.5	35.1	73.7	19.0	17.3	8.2
North Dakota St.	47.57	3.4	20.9	75.7	14.3	13.2	-6.1

Don’t even think for a second that Duke coach Mike Krzyzewski will lose a minute’s sleep thinking about this game, no matter which 16-seed wins in Dayton.  Duke could play this game without Zion Williamson, R.J. Barrett, or Cam Reddish suiting up.  Heck, Coach K could take his Gary Winton-led team from Army in the 1970’s and win this game.

Duke

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Houston	55.02	8.0	34.4	74.1	14.2	15.8	13.6
Georgia St.	51.14	5.1	23.5	66.2	14.7	18	-9.6

Here is another mismatch game.  Georgia State’s -9.6 R+T rating is dead last in this field, and Houston’s 13.6 R+T rating is seventh best in the field.  Add a better SOS and better TS% margin, and this leads to a major slaughter.  Houston has won some NCAA Tournament games by very large margins in the past.  There was a 35-point pasting of TCU in the Midwest Regional Final in 1968.  The Cougars have an outside chance to top that in this game.  Kelvin Sampson will unload the bench quicker than the way Guy Lewis did, so expect the margin to be in the 20’s.

Houston

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Mississippi St.	59.59	4.3	34.8	70.2	16.5	17.1	6.2
Liberty	46.27	9.2	25.9	74.9	15.0	18.5	5.2

I expect this game to stay somewhat close, at least for most of the game.  Mississippi State has good but not great criteria data.  Liberty’s data is slightly more impressive, but the Bulldogs’ SOS is much stronger, which will probably lead to the Maroon and White prevailing by wearing down and eventually extinguishing the Flames.

Mississippi State

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
North Carolina	62.61	5.5	34.4	76.9	14.6	16.5	17.4
Iona	45.43	3.1	25	70.6	15.4	16.1	-5.4

Roy Williams knows how to get his teams ready to play in the Big Dance, and the Tar Heels are heavy favorites to advance deep into this tournament.  Their R+T rating is second best in the field.  Their SOS is also number two.

Iona is fun to watch, as they like to run and gun.  However, this plays right into UNC’s hands.  The Gaels cannot possibly win this game, and it will be hard to keep it within 20 points.  Their -5.4 R+T rating would exclude them from being picked against 50 other teams in this tournament.

North Carolina

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Virginia Commonwealth	53.22	6.8	31.3	69.3	17.4	20.0	2.9
Central Florida	54.86	9.5	29.3	70.7	15.4	15.5	2.2

This will be another potentially close and exciting game, one worth watching.  The two teams are fairly evenly matched, but only if star Rams’ star guard Marcus Evans is playing at 100% after injuring his knee in an Atlantic 10 Tournament loss to Rhode Island.  When Evans went out, VCU was dominating the Rams.  Without him, they looked like a team that might not have beaten UMass that day.

Central Florida has the unique 7 foot 6 giant, Tacko Fall.  If you haven’t seen him play, do not mistake him for past titans that could barely walk and chew gum at the same time.  Fall is not a gentle giant.  He plays with an attitude, and he is coordinated.  He can play a one-man zone under the basket and change the opponents’ field goal percentage by 10%.  On offense, he is nearly unstoppable when the Knights can get him the ball within arms’ reach of the basket, where he can dunk flat-footed.

With a healthy Evans, VCU can still press full-court and take a lot of Fall’s ability to dominate out of the game.  Make no mistake though; this is not the same Havoc defense run by former coach Shaka Smart.  VCU won’t gamble and go full out for the steal or to force a turnover.  If I had to pick which game might have the best shot at going to overtime, this one might be the one.

Central Florida

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Iowa St.	59.42	7.6	28.7	70.0	13.9	15.9	1.7
Ohio St.	59.18	2.5	27.8	73.9	16.3	16.3	-0.4

Because the SOS’s are close to equal, the remaining stats are easy to compare.  Iowa State has a clear TS% margin, and even though the Cyclones’ R+T is weak, at least it is not negative, like the Buckeyes.

Iowa State

 

Team	SOS	TS Marg	OReb%	DReb%	TOV%	DTOV%	R+T
Virginia Tech	58.33	8.6	29.7	72.6	15.4	19.0	6.4
Saint Louis	51.40	-0.8	35.8	75.2	15.8	17.2	11.2

Only three teams enter this tournament with negative TS% margins, and it makes sense.  The object of the game is to put the ball into the hoop, while preventing the other team from doing so.  Add a healthy SOS advantage, and the Billiken’s R+T rating is neutralized.  SLU’s biggest asset is the ability to force their opponents into committing turnovers, but in this game, Virginia Tech is even better at that game.  While I have heard some people  on sports talk radio express the belief that Travis Ford’s team has a legitimate upset chance in this game, I tend to believe that chances are much stronger that the Hokies win by double-digits.

Virginia Tech

 

Here is how I fill out the remainder of the bracket

For the first time ever, the number one seeds have the top four criteria.  Could it be that the Selection Committee Members all have Bachelor of Madness Degrees in Bracketnomics?

Round of 32

Duke over Central Florida

Virginia Tech over Mississippi St.

Maryland over LSU

Michigan St. over Louisville

Gonzaga over Baylor

Florida St. over Marquette

Texas Tech over Buffalo

Michigan over Nevada

Virginia over Ole Miss

UC-Irvine over Oregon

Purdue over Saint Mary’s

Tennessee over Cincinnati

North Carolina over Utah St.

Auburn over Kansas

Houston over Iowa St.

Kentucky over Wofford

 

Sweet 16

Duke over Virginia Tech

Michigan St. over Maryland

Gonzaga over Florida St.

Texas Tech over Michigan

Virginia over UC-Irvine

Tennessee over Purdue

North Carolina over Auburn

Kentucky over Houston

 

Elite 8

Duke over Michigan St.

Gonzaga over Texas Tech

Virginia over Tennessee

North Carolina over Kentucky

 

Final Four

Gonzaga over Duke

North Carolina over Virginia

 

 

Championship Game

Gonzaga over North Carolina

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Bracketnomics 2019

How We Select Our Bracket

Welcome to PiRate Ratings Bracketnomics 2019.

This tutorial will help you earn your Bachelor of Madness Degree. Just remember that  it is not be a BS degree; it is a BM degree, so you may want to think twice before telling others you received it from PiRate U.

Most universities have some type of history that potential enrollees can examine before deciding to matriculate. That’s to make the school look worthy of consideration (and receive financial patronage). Our PiRate School of Bracketnomics has been a bit up and down throughout our history. When we first debuted as an online course, our selections and predictions put us into Ivy League/Cal Tech/MIT league. We isolated some key points from back-tested data that worked. Some of the early pointers that helped us pick brackets were things that would appear obvious to most people–scoring margin, rebounding margin, field goal percentage margin, turnover margin, schedule strength, and the ability to win away from one’s home court.

Our big breakthrough that helped us devise our first advanced metric came about when CBS’s Clark Kellogg mentioned that teams with “spurtability” tended to do best in the NCAA Tournament. What is spurtability? It is exactly what it sounds like, the ability for a team to go on a scoring spurt.

In the 1964 Final Four, tiny UCLA with no starter over 6 foot 5, went on an 11-0 scoring spurt to put away Kansas State in the semifinals, and then the following evening, put a much taller and favored Duke team away with an incredible 16-0 spurt in 2 1/2 minutes just before halftime.

How did a much smaller UCLA team put a taller, favored Duke team away with that 16-0 run? It didn’t happen because the Bruins scored baskets on eight half-court possessions, while Duke missed shots on eight half-court possessions. No, it happened because UCLA pressed Duke out of the gym that night, forcing 29 turnovers, many by steals, and then scoring easy fast-break points.

Similarly, the 1968 UCLA team put away North Carolina in the Championship Game with a couple of smaller spurts. It wasn’t the press that did the trick this time. This North Carolina team could handle the ball and break the press, and this UCLA team did not rely as much on forcing turnovers to beat opponents. With the great Kareem Abdul-Jabbar in the middle, Coach Wooden relied on muscle and speed to destroy the enemy. On this night, North Carolina tried to slow the game down by using the four-corners offense, but the plan was no more successful than 28 other opponents’ plans against the Bruins.

It was a different dominating statistic that gave the Bruins the edge that night. North Carolina rarely received a second chance to score when they missed a shot, and UCLA had numerous put back baskets on offensive rebounds. The Bruins dominated on the glass with an almost 2 to 1 rebounding advantage, and their transition game was still the best in the business with Lucius Allen running the point on the fast break.

Our captain perused all the boxscores of past NCAA Tournament games. He read microfilms of archived newspaper reports of games over the course of 30 years of NCAA Tournaments, and he combined the eyewitness reports with the statistics of the teams to locate the factors that predicted which teams were more likely to enjoy a big scoring spurt. He discovered that half-court offenses and half-court defenses that led to one team connecting on a very high percentage of shots while the other team missed a high percentage of shots seldom led to these spurts by themselves and very rarely allowed a team to win six, or even just four NCAA Tournament games.

It was rare for Team A to hit eight out of 10 shots, while Team B hit only one out of ten shot, leading to a 16-2 run. So, what caused the great spurtabilities of the teams? The Captain discovered that in a large majority of the cases where a team went on a big scoring run in the NCAA Tournament, it was due to these factors:
1. Dominating rebounding at both ends of the court
2. Forcing turnovers (especially steals)
3. Getting easy fast break baskets or forcing the opponent to foul to stop the fast break

From this point, the Captain devised what has come to be the most important factor in picking NCAA Tournament winners. He called it “The R+T Rating.” After trial and error using different data points, the Captain created a formula that doubled rebounding margin, added turnover margin, and then gave additional weight to steals and the prevention of steals. The result was an approximation for how many extra scoring chances (and predicted points) a team might be expected to receive versus the average college team. If Team A had an R+T rating of 20, and Team B had an R+T rating of 10, then Team A would be expected to have the ability to score an average of 10 extra points against Team B just from these extra scoring opportunities. Team B could still win if they were a lot more accurate on their shots, thus neutralizing Team A’s spurtability advantage.

Immediately, in the first year publishing this data online, the PiRates successfully picked Florida to win its first national championship, and the Gators came through with a surprise title. In all six of their tournament wins in 2006, they enjoyed spurts that broke close games open. In their big upset win over top-seeded Villanova, the Gators’ pressure man-to-man defense made it difficult for the Villanova perimeter to get an open look, and when the Wildcats drove by into the lane, Joakim Noah and Al Horford were there waiting to stop the offense. The two Gator big men totally controlled the boards that afternoon, and Florida advanced with a couple of spurts that put the game safely in the win column.

Early on in the history of our Bracketnomics, our success continued and brought us a tiny bit of national notoriety. A little success swelled the heads of all the PiRates. We became too big for our tiny ship. We began to try to perfect our system by adding additional information. We thought for a few years that teams that relied on the three-point shot were at a disadvantage against teams that pounded the ball inside, because so many of the tournament games were held in giant stadiums, even domes, and it affected depth perception and made it hard to aim on outside shots. There was a time when we discounted teams that won games by shooting a lot of foul shots, because the officials did not call as many fouls in the tournament.

The success of the PiRate Ratings Bracketnomics led to some mainstream media sources linking to us, and we saw our readership increase by large multiples, especially between the second week of March and the first week of April. And, then what happened? After correctly picking the national champion during Bracket Picking day for three consecutive years; and after picking tiny George Mason to contend for a Final Four spot when Jim Larranaga guided the Patriots to the Final Four; and after picking Duke, Connecticut, and Kentucky to win and hit on another three in a row, the bottom fell out.

Just like the Dosage Index for the Kentucky Derby, the criteria began to lose its effectiveness. Too many basketball equivalents of Strike The Gold and Real Quiet began winning when the profile predicted they had little or no chance. While R+T ratings still remained effective, other criteria not used by us began to be more predictive of reality.

The better three-point shooting teams started to win more and more. Watching the Golden State Warriors dominate the NBA and then seeing how almost every NBA team tried to copy them in some way, it became apparent that advanced metrics were changing the game, just like Sabermetrics changed the way general managers built their baseball teams. The name of the game became three-point shooting and very high percentage two-point shooting. Defenses that forced opponents to take lower percentage two-point shots became the new basis for determining effectiveness.

There was one other change that greatly affected the college game. When the shot clock moved from 35 to 30 seconds, it appeared on the surface that it would minimally affect the game by maybe two or three possessions per game. This was not the case. Defenses discovered that they could pressure the offense more and more in hopes that they would force a turnover or force the offense to escape the pressure to find a good shot. Many times, the pressure defense led to a hurried shot by the offense. Thus, teams that were patient all of a sudden saw their shooting percentages fall when good pressure defenses forced too many hurried shots. There was also the case where a defense that could keep the ball out of the close two-point range and force three-point shots to be taken a few feet farther back, could stop the patient offenses. What was the solution to these defenses? It was the return of Up-tempo basketball. Offenses began to try to hurry up their tempo to beat these gambling defenses or to get the preferred close in two-pointer or open looks an inch behind the line three-point line before defenses could organize. The newer up-tempo style of play brought back basketball from 40 years ago.

Once again, the teams that can get up and down the court in a hurry and do so without becoming sloppy in execution have begun to dominate the game. The patient offenses and non-pressuring defenses have found out that it is really hard to win consistently when the opponent is now finding a way to score 10 more points per game due to their new style of play.

On the other end of the spectrum, teams began to play more like the high schools in the Midwest. Players not equipped for the running and pressure defense games began to concentrate on playing incredible help defense, cramming the paint with defenders to stop dribble penetration. While some teams did this with man-to-man defense, otherwise known as the Pack-Line defense, some teams also accomplished this with zone defenses. Either way, the goal was to prevent easy inside shots while not gambling for steals or pressuring opponents into mistakes. Usually these teams paired this style of defense with a patient offense that valued each possession like gold and when they took a shot, two or more players retreated to stop any opponent transition. A lot of teams have done quite well during the regular season, but they have not been the best at winning four tournament games and getting to the Final Four. Loyola of Chicago beat the odds last year playing this way. Butler made it to the Championship Game twice with a semi-patient offense and non-gambling defense.

What did we do at the PiRate Ratings to combat our decline in effectiveness? The PiRates stripped our criteria down back to the basics. We felt like we were missing the obvious. In 2019, here are the Big Three stats that matter most when the NCAA Tournament begins play.

1. True Shooting Percentage Margin

2. R+T Rating

3. Schedule Strength

These three basic principles make up an overwhelming majority of how we will select our brackets when we release them Monday evening.

1. True Shooting Percentage Margin: this is the difference between a team’s offensive true shooting percentage and defensive true shooting percentage. For college basketball, true shooting percentage is:   (100*Pts)/[2*(fga+{.475*fta})].

2. R+T Rating: We hope most of you reading this today have some familiarity with our R+T Rating.

The formula for R+T is: (R * 2) + (S * .5) + (6 – Opp. S) + T
where, R = rebounding margin; S = Steals per game; and T= Turnover margin

3. Schedule Strength: It is obvious that a team could compile some very lofty True Shooting Percentages and R+T ratings playing the weakest 30 teams in the nation, while another team could compile some really awful stats playing the top 30 teams in the nation.

Don’t let these stats look intimidating. We would never force you, our patron, that we love so much to have to figure the offensive and defensive percentages for 68 teams. Do you know how long it takes to go to 68 different official athletic sites to get this information? We sure do! We will calculate this information for you and show you the stats for all 68 teams.

The first two data points must be weighted with the strength of schedule, and there is the rub. How much do we adjust the data from True Shooting Percentage Margin and R+T Rating to factor in schedule strength? We think we have the answer. Based on the fact that a certain schedule strength number has held consistent as the floor among past Final Four teams, we believe we know the cut-off points that will allow us to interpolate the winners of each round.

Obviously, it is not an exact science, but hey, nobody has ever picked a perfect bracket, and we hear that the chances of doing so are less than one person winning both the Power Ball and Mega Millions jackpots in the same week, while being struck two times by lightning on the way to collect from both the lottery offices.

The PiRates will reveal our entire bracket selections Monday evening.   And, after each round, we will then post an updated bracket selection for those people that play in contests where you can pick the winners round-by-round. Our goal is to try to pick the four Final Four participants and National Champion, so those of you in contests where you receive points for your accuracy, with more points awarded for each succeeding round, might have a somewhat unfair advantage over others in your pool.

We hope you return to this site after 7PM EDT on Monday night, March 18, to see what we believe will be an exciting and informative Bracketnomics 2019 exam. Yes, you too can earn your BM degree!

And, don’t forget to check our site out Sunday as our Bracket Gurus attempt to continue a history of incredible accuracy predicting the 68 teams to be selected for the NCAA Tournament.

We will publish one or two updates Sunday.  The first will be on this site before 10:00 AM EDT.  The final one will be published after all Sunday games but the Big Ten Tournament go final, or later if there is a chance this game will affect the bracket.

There will be an additional late Saturday night bracket update to include new automatic bid winners.

Bracketnomics 505 for 2018: First Class

NOTE:  DO NOT REFER TO PAST YEARS’ BRACKETNOMICS REPORTS–THEY ARE OBSOLETE!!!!!

Welcome to the 2018 edition of the PiRate Ratings Bracketnomics 505 Course.  Our course is accredited, and when you complete it, you will earn your Bachelor of Madness Degree.  Just remember that it may not be a BS degree, but it is a BM degree, so you may want to think twice before telling others you received it from PiRate U.

Most universities have some type of history that potential enrollees can examine.  That’s to make the school look worthy of consideration.  Our PiRate School of Bracketnomics has been a bit up and down throughout our history.  When we first debuted as an online course, our selections and predictions put us into Ivy League/Cal Tech/MIT status.  We isolated some key points from back-tested data that worked.  Some of the early pointers that helped us pick brackets were things that would appear obvious to most people–scoring margin, rebounding margin, field goal percetage margin, turnover margin, schedule strength, and the ability to win away from one’s home court.

Our big breakthrough that helped us devise our first advanced metric came about when CBS’s Clark Kellogg mentioned that teams with “spurtability” tended to do best in the NCAA Tournament.  What is spurtability?  It is exactly what it sounds like, the ability for a team to go on a scoring spurt.  What we are talking about here is something like 10-0 or 15-4 or 20-8 run.  Next, in the evolution of PiRate Bracketnomics, our Captain began to research what factors contributed the most to big scoring spurts.  He discovered that half-court offenses and half-court defenses that led to one team connecting on a very high percentage of shots while the other team missed a high percentage of shots seldom led to these spurts by themselves.  It was rare for Team A to hit eight out of 10 shots, while Team B hit only one out of ten shots and led to a 16-2 run.  So, what caused the great spurtabilities of the teams?  The Captain discovered that in a large majority of the cases where a team went on a big scoring run in the NCAA Tournament, it was due to dominating rebounding at both ends of the court, forcing turnovers (especially steals) and then getting easy fast break baskets or forcing the opponent to foul.

From this point, the Captain devised what has come to be the most important factor in picking NCAA Tournament winners–the R+T Rating.  After trial and error using different data points, the Captain created a formula that doubled rebounding margin, added turnover margin, and then gave additional weight to steals and the prevention of steals.  The result was an approximation for how many extra scoring chances and points a team might be expected to receive versus the average college team.  If Team A had a R+T rating of 20, and Team B had a R+T rating of 10, then Team A would be expected to score 10 extra points against Team B just from extra scoring opportunities.  Team B could still win if they outshot Team A by a high enough percentage to make up for those 10 points.

A little success swelled the heads of all the PiRates.  We became too big for our tiny ship.  We began to try to perfect our rating by adding additional information.  We thought for a few years that teams that relied on the three-point shot were at a disadvantage against teams that pounded the ball inside, because so many of the tournament games were held in giant stadiums, even domes, and it affected depth perception and made it hard to aim on outside shots.

There was a time when we discounted teams that won games by shooting a lot of foul shots, because the officials did not call as many fouls in the tournament.

The success of the PiRate Ratings Bracketnomics led to some mainstream media sources linking to us, and we saw our readership go up by large multiples, especially between the second week of March and the first week of April.  And, then what happened?  After correctly picking the national champion during Bracket Picking day for three consecutive years; and after picking tiny George Mason to contend for a Final Four spot when Jim Larranaga guided the Patriots to the Final Four; and after picking Duke, Connecticut, and Kentucky to win and hit on another three in a row, the bottom fell out.

Just like the Dosage Index for the Kentucky Derby, the criteria began to lose its effectiveness.  Too many basketball equivalents of Strike The Gold and Real Quiet began winning when the profile predicted they had little or no chance.    While R+T ratings still remained effective, other criteria not used by us began to be more predictive.

The better three-point shooting teams started to win more and more. Watching the Golden State Warriors dominate the NBA and then seeing how almost every NBA team tried to copy them in some way, it became apparent that advanced metrics were changing the game, just like Sabermetrics changed the way general managers built their baseball teams.  The name of the game became three-point shooting and very high percentage two-point shooting.  Defenses that forced opponents to take lower percentage two-point shots became the new basis for determining effectiveness.

There was one other change that greatly affected the college game.  When the shot clock moved from 35 to 30 seconds, it appeared on the surface that it would minimally affect the game by maybe two or three possessions per game.  This was not the case.  Defenses discovered that they could pressure the offense more and more in hopes that they would force a turnover or force the offense to escape the pressure to find a good shot.  Many times, the pressure defense led to a hurried shot by the offense.  Thus, teams that were patient all of a sudden saw their shooting percentages fall when good pressure defenses forced too many hurried shots.  There was also the case where a defense that could keep the ball out of the close two-point range and force three-point shots to be taken a few feet farther back, could stop the patient offenses.  What was the solution to these defenses?  Up-tempo basketball came back in vogue.  Offenses began to try to hurry up their tempo to beat these gambling defenses or to get the preferred close in two-pointer or right behind the line three-pointer before defenses could organize.  The newer up-tempo style of play brought back basketball from 40 years ago.

Once again, the teams that can get up and down the court in a hurry and do so without becoming sloppy in execution have begun to dominate the game.  The patient offenses and non-pressuring defenses have found out that it is really hard to win consistently when the opponent is now finding a way to score 10 more points per game due to their new style of play.

What did we do at the PiRate Ratings to combat our decline in effectiveness?  The PiRates stripped our criteria down back to the basics.  We felt like we were missing the obvious.  Here is what matters when the NCAA Tournament begins play.

1. True Shooting Percentage Margin

2. R+T Rating

3. Schedule Strength

These three basic principles make up an overwhelming majority of how we will select our brackets when we release them Tuesday afternoon.
1. True Shooting Percentage Margin:  this is the difference between a team’s offensive true shooting percentage and defensive true shooting percentage.For college basketball, true shooting percentage is:

(100*Pts)/[2*(fga+{.475*fta})]. 

Don’t let this stat look intimidating.  We would never force you our patron that we love so much to have to figure the offensive and defensive percentages for 68 teams.  Do you know how long it takes to go to 68 different official athletic sites to get this information?  We do!  We have already calculated this informaton.

 

2. R+T Rating:  We hope most of you reading this today have some familiarity with our R+T Rating.

The formula for R+T is:

(R * 2) + (S * .5) + (6 – Opp. S) + T

R = rebounding margin; S = Steals per game; and T= Turnover margin

3. Schedule Strength:  It is obvious that a team could compile some very lofty True Shooting Percentages and R+T ratings playing the weakest 30 teams in the nation, while another team could compile some really awful stats playing the top 30 teams in the nation.  The first two data points must be weighted with the strength of schedule, and there is the rub.  How much do we adjust the data from True Shooting Percentage Margin and R+T Rating to factor in schedule strength?  We think we have the answer.  Based on the fact that a certain schedule strength number has held consistent as the floor among past Final Four teams, we believe we know the cut-off points that will allow us to interpolate the winners of each round.  Obviously, it is not an exact science, but hey, nobody has ever picked a perfect bracket, and we hear that the chances are better than somebody can win the Power Ball and Mega Millions jackpots in the same week than picking a perfect bracket.
The PiRates will reveal our entire bracket Tuesday afternoon.  And, after each round, we will then post an updated bracket for those people that play in contests where you can pick the winners round-by-round.

Additionally, we will issue our regular PiRate Ratings spreads for each tournament game.
We hope you return Tuesday after 12 Noon EDT to see what we believe will be an exciting and informative Bracketnomics 505 course.  Yes, you can earn your BM degree!

PiRate Ratings Bracketnomics 505 Bracket Reveal & First Four Preview

For those that just want to see our Red-White-Blue Ratings for the First Four, here they are.

Team	Team	Red	White	Blue
New Orleans	Mount St. Mary’s	3	-1	1
Wake Forest	Kansas St.	1	1	1
UNC-Central	UC-Davis	4	3	6
Providence	USC	1	1	1

Now, for the rest of you:

Welcome one and all to our annually most viewed edition of the PiRate Ratings.  We have been working diligently for the past 42 hours getting this edition of March Madness Bracketnomics ready for you.

If you are new to this site today, there is something you need to do, and even if you are not, you should take this advice.  Open another window and bring up our primer from yesterday where we explain how we have come up with the numbers that we will show you today.  The link to the primer is:

https://piratings.wordpress.com/2017/03/13/bracketnomics-505-the-advanced-level-course-in-bracket-selection/

Before we begin picking winners in our bracket based on the PiRate Criteria, let us give you another little bit of advice in selecting your own brackets.

1. Do not select a lot of early upsets.  Realize that nobody ever has picked a perfect bracket.  The chances are so slim that nobody may ever pick one!  The key to winning bracket contests where you must choose all the games at the beginning and do not get to select new winners after every round is to pick the National Champion, the Final Four, and the Elite 8 teams.  Realize that in about 95% of the cases, the Final Four teams come from one, two, three, or four seeds.  There will frequently be a seed lower than 4, but good luck trying to pick one.  What you will most likely do is remove one of the favorites to get there, so select very few upsets early.
2. In the last 60+ years, only 2 times was the national champion a team from outside a major conference, and it has not happened since 1990.  So, go heavy on the best teams in the power conferences–Atlantic Coast, Big 12, Big East, Big Ten, Pac-12, and SEC.  No Pac-12 team has won the title since Arizona beat Kentucky in 1997, so you might discount the Pac-12 a little.  No Big Ten team has won the title since Michigan State in 2000, so you might also want to discount the Big Ten a little.
3. The most likely spots for upsets early come from 10-11-12 seed lines for good reason.  The top lower and mid-major teams usually end up on one of these seed lines, and in actuality, some of these teams would beat their higher-seed opponent 7 times out of 10.  In other words, these upsets are not really upsets.  They are incorrect seedings by the Committee.

Okay, we will leave the rest of that strategy up to you.  Let’s get to the Bracketnomics Facts for 2017

 

Who Has The Statistical Criteria That Looks Like A Final Four Team

This is an unusual year.  There are no teams closely similar to the Connecticut women’s team.  There is no obvious best team like in some years out of the past.  On the other hand, there are an inordinate amount of teams this year that look like they would have trouble winning the NIT 10 years ago.  There is parity by virtue of mediocrity.  The way the game is played in 2017, and with the 30-second shot clock, the game has become harder to isolate on just two or three teams and call them the heavy favorites to make the Final Four.

Let’s eliminate some teams so that what we have left is a much easier group to compare.

A. First, let’s forget the chance that a low-major or mid-major conference team will make the Final Four this year.  This does not include Gonzaga, Saint Mary’s, or Wichita State, who we consider to be above mid-major.

B. Next, let’s take out any team that played a schedule too soft to prepare them for the top echelon of opponents.  From what’s left after (A), that will remove Wichita State and UCLA.

C. Next, let’s dump any team with a single-digit R+T rating after the Sweet 16 round.  Any single digit team in the Elite 8 gets knocked out, unless their opponent also has a single digit rating.  From this list of teams still in contention after (A) and (B), we now dump: South Carolina, Butler, Wake Forest, Arkansas, Minnesota, Michigan State, USC, Northwestern, Michigan, Notre Dame, Maryland, Marquette, Kansas State, Providence, Iowa State, Creighton, Vanderbilt, and Virginia Tech.

D. Let’s remove any teams that are missing key players and might be able to get to the Sweet 16 without these players, but they are most likely to bow out at this point when the competition is too strong.  Say good bye to Xavier and Oregon.  For now, Creighton and Florida stay in because they played a significant number of games without their key players.

Now we have a much more manageable list of Final Four and Elite 8 Contenders, down to just 21 teams.

But, we are not finished eliminating teams.  What about teams that have not played all that well away from home?  We can eliminate the 22-9 team that went 17-0 at home and 5-9 away from home, because these teams are not going to all of a sudden beat the nation’s finest teams away from their home floor, at least not 4 consecutive times.

Let’s now say bye bye to Florida State, Miami (Fla.), and Seton Hall, lowering the number to 19.

And, then there is the essential thing of having enough consistency to win four games in a row against quality competition.  We cannot keep any teams that did not sustain at least one long winning streak or two extended winning streaks.  Only West Virginia fails to meet this criterion from the remaining group, lowering our list to 18.

Now,  let’s look at how the remaining 18 teams rate in the criteria that matter.

Scoring Margin

There is a reason both Gonzaga and Saint Mary’s are still in this list.  They are serious contenders this year.  Gonzaga has the highest scoring margin and Saint Mary’s has the third highest among the 17 remaining teams.  From the list of 17, there are a couple teams that do not meet the 8 point minimum to be considered as a strong Final Four contender.  There are teams that make the Final Four with less than 8 point scoring margins, but they are the exception rather than the rule, and we are looking for angles that increase our percentage chance of hitting on Final Four teams.  It’s the end of the line here for Oklahoma State.

 

Field Goal Percentage Differential

Eventually, in order to get to the Final Four, a team is going to have to be superior when it comes to shooting and defending the shot, because eventually, being able to dominate the glass or force a lot of turnovers will not work against teams that can also rebound and force turnovers.  We are looking only for a difference of 5% or more to stay in the hunt for Final Four contention.  We must say adieu to three more teams that cannot meet this standard–Florida, Duke, and Wisconsin.  Now we have 14 teams on our list of Final Four contenders.

 

Rebound Margin

Remember that R+T rating is much more important than any of its components (Rebounding, Turnovers, and Steals), but for Final Four consideration, well over 90% of the past Final Four teams had positive rebound margin.  In what may help vindicate our selections to this point, all 14 teams remaining have positive rebounding margin.

 

Okay, Already, Who Is Left?

The following teams have resumes that could get them to the Final Four.  In alphabetical order, they are: Arizona, Baylor, Cincinnati, Gonzaga, Kansas, Kentucky, Louisville, North Carolina, Purdue, Saint Mary’s, SMU, Villanova, Virginia, and West Virginia.  If our criteria is worth anything these years, we expect the Final Four to come from this list of teams.  But, we need to do better.  You cannot select 14 teams to make the Final Four or even Elite 8.

 

What we need to do now is look at each game as it is played.  It won’t help us to go with the 4 best resumes if these teams cannot all make the Final Four because they will play each other prior to that round.

Here is how we see the First Four games according to PiRate Criteria.  Note that our criteria and our Red-White-Blue Ratings have no real correlation, so the teams we predict to win may not be the same as the teams our criteria says will win.

First Four

New Orleans over Mount St. Mary’s

UNC-Central over UC-Davis

USC over Providence

Kansas St. over Wake Forest

Most brackets allow you to miss here without penalty and start in earnest at 64 teams, but we don’t go for that.

Round of 64

You will not see us picking many upsets in this round.  Remember the important factoid we revealed at the beginning: you win your bracket contests by getting your teams into the Elite 8, Final 4, and National Championship.  If you pick a lot of upsets, you are liable to have very few teams left by the Elite 8.

Villanova over New Orleans (Mount St. Mary’s)

Wisconsin over Virginia Tech

Virginia over UNC-Wilmington (upset possible, but we’ll take the Cavs)

Florida over East Tennessee (like a home game for the Gators)

SMU over USC in a rematch (also over Providence) near tossup vs. USC close to 50-50

Baylor over New Mexico St.

South Carolina over Marquette in close one that will be like home game for Gamecocks.

Duke over Troy

Gonzaga over South Dakota St.

Northwestern over Vanderbilt (close game)

Notre Dame over Princeton

West Virginia over Bucknell (not this year for Bison as Mountaineers are too physical)

Maryland over Xavier (Chris Mack becomes an early candidate for other big openings)

Florida State over Florida Gulf Coast (FGCU not as strong as their Sweet 16 team)

Saint Mary’s over VCU (Will Wade comes free for promotion to power conference team)

Arizona over North Dakota

Kansas over UNC-Central (UC-Davis)

Miami over Michigan State (MSU one and done two years in a row)

Iowa State over Nevada (but this one should be nip and tuck)

Purdue over Vermont (Boilermakers finally have the right type of resume to advance)

Creighton over Rhode Island (freeing up Dan Hurley if a big school wants him)

Oregon over Iona (loss of Chris Boucher does not hurt yet)

Oklahoma State over Michigan (This upset we will pick.  Cowboys have better criteria resume)

Louisville over Jacksonville State (UL almost has a home game in Indy)

North Carolina over Texas Southern

Seton Hall over Arkansas (should be physical and close)

Minnesota over Middle Tennessee (Blue Raiders are the Vegas favorite, but Gophers can exploit interior defense)

Butler over Winthrop (we would not be shocked if Butler has to rally to win this one)

Cincinnati over Kansas State (Wake Forest)

UCLA over Kent State

Wichita St. over Dayton (Will Archie Miller be the next NC State coach?)

Kentucky over Northern Kentucky (Norse would be happy with a lead at under 16 timeout in 1st half)

 

Round of 32

Villanova over Wisconsin

Virginia over Florida (should be very close, maybe overtime)

Baylor over SMU (this one should be a great game–Tim Jankovich in play at Illinois)

Duke over South Carolina (We don’t see Frank Martin leaving the Palmetto State unless he has 4 million reasons)

Gonzaga over Northwestern (Cinderella season ends here–no Cubs repeat in the Windy City)

West Virginia over Notre Dame (Irish wear down in the second half)

Florida State over Maryland

Arizona over Saint Mary’s (expect a hard-fought game but Gaels are outmanned)

Kansas over Miami (closer than expected)

Purdue over Iowa State (Boilermakers look impressive to this point)

Oregon over Creighton (Boucher’s absence felt but not enough for Ducks to lose)

Louisville over Oklahoma St. (Brad Underwood vs. Rick Pitino–Brilliant!)

North Carolina over Seton Hall

Butler over Minnesota (Should be a great game)

Cincinnati over UCLA (Bruins numbers padded by substandard overall schedule–not strong enough inside)

Kentucky over Wichita State (because Wildcat players appear to be on a mission and if so are the class of the field)

 

Sweet 16 to Elite 8

Villanova over Virginia (Cavs do not have enough offense to win at this point)

Baylor over Duke (Our big upset pick in this round, because Duke has holes Bears can exploit)

West Virginia over Gonzaga (Sorry Bulldog fans, WVU style of play is not what you want to face)

Arizona over Florida State (We expect Wildcats to win big in this one)

Kansas over Purdue (KU will have to play lights out to put Boilermakers away)

Louisville over Oregon (Boucher’s absence is too much to overcome in this round

North Carolina over Butler (If Heels are rolling at this point, then next round is actual title game)

Kentucky over Cincinnati (Should be ultra-physical and highly emotional game)

 

Elite 8 to Final Four

Unfortunately, at this point the top two teams in the field will meet

Baylor over Villanova (no repeat for Wildcats but a great game)

Arizona over West Virginia (Mountaineers run out of gas at this point)

Louisville over Kansas (Cards win a sloppy game)

Kentucky over North Carolina (This should have been the National Championship Game)

 

Final Four Semifinals

Baylor over Arizona (tough to go against a team playing in its home state)

Kentucky over Louisville (how much will this ticket cost)

 

National Championship

Kentucky over Baylor

 

The Kentucky criteria best matches that of past national champions.  Add to the fact that they have the most talent and a coach that can use the right psychology to motivate these future millionaires to play like their draft status is to be determined in this tournament, and we believe the Wildcats will cut the nets in Arizona.

 

Here is how the 14 top Pirate Criteria teams rank overall

1. Kentucky
2. North Carolina
3. Baylor
4. Arizona
5. West Virginia
6. Gonzaga
7. Louisville
8. Villanova
9. Kansas
10. Purdue
11. Duke
12. Cincinnati
13. Saint Mary’s
14. SMU

 

TV Schedule For First Four in Dayton

Day	Time (EDT)	Network	Team	vs.	Team
Tuesday, March 14	6:40 PM	truTV	New Orleans	vs.	Mount St. Mary’s
Tuesday, March 14	9:10 PM	truTV	Wake Forest	vs.	Kansas St.
Wednesday, March 15	6:40 PM	truTV	UC-Davis	vs.	UNC-Central
Wednesday, March 15	9:10 PM	truTV	USC	vs.	Providence

 

 

 

 

Bracketnomics 505: The Advanced Level Course in Bracket Selection

PiRate Ratings Bracketnomics 505 for 2017: Money Ball on the Hardwoods
Welcome to Bracketnomics 505 for 2017–The Advanced Level Course in Picking NCAA Tournament winners. The best way to describe our PiRate Ratings NCAA Tournament Bracket-Picking formula is to compare it with the 10-K financial reports of publicly traded companies. Each team’s data serves as a prospectus showcasing their worth. Do you want to buy or sell based on what the data portrays?
If you have followed our statistical releases for the past 17 years, you will not see any real changes this year, as the PiRate Ratings have added only one minor statistical detail to our repertoire, and those are in our algorithm formulas and not in the data to be presented.

However, we have strengthened our beliefs in the idea that the NCAA Tournament is a different animal from the regular season, so there are teams that did well in the regular season and even won their conference, but they are ill-prepared for the postseason. Now, we actually have new incites into why, and it comes from our experiences with Major League Baseball.

Some of you reading this know that I, the Captain of the PiRate ship, am a baseball metric specialist. You can call me one of the “Moneyball” scouts or as some even say, a “Beane Counter.” If you read the book, Mr. Beane had a famous quote, that we will paraphrase to eliminate four-letter words: “My ‘stuff’ doesn’t work in the playoffs.”

Re-reading that statement sent me off on a long research project last Autumn leading to my spending way too many hours trying to put math formulas to Beane’s statement. What I came up with was this: in baseball, the offensive statistics that produce runs, for example weighted On-Base Average, works quite effectively during the regular season, when a team plays a certain number of games against every team in the league. Thus, a team will play a goodly number of games against mediocre and poor teams, and having an offense built on getting on base and hitting for power dominates against the weaker teams.

But, in the playoffs, all the opponents are very good. All of them have good offenses and usually very good pitching and defenses. Trying to win by getting a lot of runners on base by the walk and then hitting three-run homers might work against the number four and five starters of a pitching staff or the mediocre top level pitchers of the 90-loss teams, but in the playoffs, you see mostly top three starting pitchers from teams that won 90 or more games. And, Beane’s “stuff” does not work against these elite teams with the top pitchers. You have to be able to steal an extra base on a hit, steal a base, and execute the hit and run against the best of the best, which means you frequently play for just one run, because the pitching is too good to give up those three-run homers and will scatter baserunners over the course of 6 or 7 innings. Think Maury Wills scratching out a run for the 1965 Dodgers, while Sandy Koufax shuts out the opponent in a 1-0 win.

The same belief can be applied to college basketball in the NCAA Tournament. A team might win their conference by playing excellent half-court offense and defense, even if they do not rebound well nor force turnovers and pick up steals. Let’s use Purdue in the Gene Keady days as an example. Keady’s teams executed half-court offense and defense like precision clockwork. The Boilermakers almost always enjoyed better shooting opportunities than their opponents. They usually finished with a better field goal percentage than their opponents every year, and they won or shared a lot of Big Ten titles.

These Purdue teams were not all that strong on the offensive glass, and while they played intelligently and did not turn the ball over much, they did not force turnovers, nor did they steal the ball very much, frequently finishing at or near the bottom of the Big Ten in these stats.

Like Moneyball and the A’s, this “stuff” (excellent half-court offense and defense) worked just fine in the regular season, where Purdue easily handled the bottom half of the Big Ten year after year and did just well enough against the top half to finish 15-3 or 14-4. Then, the Boilermakers would get into the Big Dance looking like a Final Four contender. Unfortunately, their “stuff” didn’t work in the NCAA Tournament, and the Boilermakers lost as favorites early in the Dance to athletic underdogs with double-digit losses (Auburn, Florida, LSU), never making it to the Final Four in that time. They were no longer playing the 6-12 and 8-10 Big Ten teams Once their opponent was also good at getting open shots and preventing them on defense, the extra scoring opportunities derived from getting offensive rebounds and forcing turnovers, especially by steals, took on much more significance, just like running the bases and playing for one run in the Major League Playoffs.

Just in case you say that maybe Purdue was not capable of getting enough talent to go to the Final Four, remember that Purdue did make the Final Four under previous coach Lee Rose (he also led Charlotte to the Final Four in 1977), when Rose’s coaching philosophy included pressure defense with the hope of getting a lot of steals and an inside glass cleaner or two to dominate on the boards.
This year, we will give added weight to our special R+T metric along with schedule strength and ability to win away from home as serious factors to consider when picking teams to advance in the NCAA Tournament. These will be the three of our basic building blocks to begin the process of eliminating pretenders from the true contenders. Here are our basic blocks to begin our search for a national champion.

1. R+T Rating
2. Schedule Strength
3. Ability to win away from home
4. A member of a power conference (AAC, ACC, Big 12, Big East, Big Ten, Pac-12, and SEC)
5. One long winning streak against quality competition or two winning streaks of 6 or more games.
Don’t worry if this looks a bit challenging for you at this point. We will explain it all in this primer, and your test is an open book test, so you will pass with flying colors.

Here is a description of all the pertinent information you need to pick your brackets. We will explain each important statistic and tell you how it applies to the NCAA Tournament. Then in the next edition, we will apply it to all 68 teams in the Big Dance and let you use what you want to fill out your brackets. You can easily open two windows with this primer in one window, and the statistics in the other window, and voila, you have an exceptional reference at your disposal.

Remember one important bit of information–this process deals a lot with past tendencies trying to predict future outcomes. It is mechanical and includes limited subjective data. It will not include information such as how your team’s star player may have the flu this week, or he ended his season in the Pac-12 Championship Game with an ACL injury, so if you have other information, by all means include this in your selection process.

The PiRate Ratings Criteria Statistics
For 16 years, the PiRate Ratings have relied on specific back-tested data that showed us what stats have been important in selecting Final Four teams. We looked back in history to see how previous Final Four teams dominated in certain statistical areas while not dominating in other areas. Here is what we found.

Scoring Margin
For general bracket picking to the Final Four, 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.

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 said team is from one of the six power conferences, you have a team that can advance deep into the tournament.

This is an obvious statistic. If State U outscores opponents by an average of 85-70 and Tech outscores similar opposition by an average of 75-70, State figures to be better than Tech before you look at any other statistics.
In the days of the 64 to 68-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 five points per game to win four times in a row, much less six or seven consecutive games.

This statistic 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. As you can see from looking at all the NCAA Champions in the 2000’s, every team had a scoring margin of 8 or better, and 15 of 17 had double digit scoring margins (and all from power conferences).

A look at recent national champions’ scoring margins
2016 Villanova: 13
2015 Duke: 15
2014 UConn: 9
2013 Louisville: 16
2012 Kentucky: 17
2011 UConn: 8
2010 Duke: 16
2009 North Carolina: 18
2008 Kansas: 19
2007 Florida: 17
2006 Florida: 15
2005 North Carolina: 18
2004 UConn: 15
2003 Syracuse: 10
2002 Maryland: 14
2001 Duke: 20
2000 Michigan St.: 15

Field Goal Percentage Differential
Take each team’s field goal percentage minus their defensive field goal percentage to calculate this statistic. Throughout time, the differential among the most successful teams has been +7.5% or better, and for most Final Four teams, the differential has been positive by 3% or better. For example, a team that shoots 47% while their opponents shoot 39% has a FG% differential of 8%.

Teams that have singificantly positive field goal percentage differentials are consistently good teams. A team can win a game or two or possibly even three games with negative field goal percentage differentials, but in the Big Dance, they certainly are not going to win six games like this, and they have little chance to win four games.

This statistic holds true in back-tests of 50 years. Most teams that have won the tournament had FG% differentials above 3%, and many had more than a 7.5% field goal percentage advantage. In the years of the 64 to 68-team tournament, this stat has become a more accurate predictor, especially when the team comes from a power league. In the 21st Century, the teams from power conferences with field goal percentage margins in the double digits have dominated the field. For example, if you see an ACC, Big 12, Big Ten, or SEC team with a FG% differential of +10% or better, that team is going to be very hard to beat in large arenas with weird sight lines.

One caveat: in the most recent couple of years, shooting percentages have normalized somewhat, so overall, FG% differentials are moving closer to 0. More three-point shooting, a reduction in the shot clock, and more fast break offenses have led to more parity in shooting percentages. And, this has to be something to monitor closely this year; teams that had the best field goal differentials last year were upset early by teams that excelled in forcing turnovers and running the fast break. This could mean that shooting percentages are going to lose some of their importance, while extra scoring opportunities are going to become more important. Think about that as you read on.

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 past the first weekend in the tournament. What we are 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 is just as important.

There are complete rebounding statistics back to 1954, and in the 61 NCAA Tournaments between 1954 and 2014, the National Champion out-rebounded their opponents for the season all 61 times! Yes, no team with a negative rebound margin in that season has ever won the NCAA title.

The reason this statistic becomes even more important in mid-March is that teams do not 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 put-backs 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 as the number of teams drop from 64 to 32 to 16 to eight, it is rare for one of these teams to continue 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.

Use the rebounding rule in selecting your brackets, but think about this. Rebounding is only one way to obtain a possession. There is another way to get a possession–via a turnover. Bear that in mind as you read on. So, don’t just use rebounding margin alone, as it is only one part of the equation.

Turnover Margin & Steals Per Game
Turnover margin can give a weaker rebounding team a chance to advance. Any positive turnover margin is good. If a team cannot meet the rebound exceptionally well, they can get win if they have an excellent turnover margin. Not all turnover margin is the same though. A team can have an excellent turnover margin because they seldom turn the ball over. Committing 10 turnovers per game, while the opponent commits 12 leads to a positive turnover margin of 2 per game, but it seldom amounts to much in this instance. A team that forces a high number of turnovers by way of steals has a real advantage. A steal is better than a defensive rebound, because most of the time, a steal leads to a fast-break basket or foul (or both). 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 an immediate numbers advantage. A steal with quick points can demoralize a team, especially one that plays patiently and limits possessions.

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 and/or control the boards are the ones who will get that spurt.

Like the rebounding margin, we must not judge turnover margin and steals as standalone criteria, as they are just part of an all-encompassing statistic to determine extra scoring opportunities and the ability to go on lethal scoring spurts. What follows is the criteria to use.

The All-Important PiRate Ratings R+T Margin
Using both rebounding and turnover margin, how best can we assign an extra scoring value and the ability to go on big scoring spurts? In a tight game, a 10-0 run in three minutes will usually lead to a win for the team that makes the spurt, so we need to have a stat that shows us how much a team has spurt potential.
Our answer is the PiRate Ratings’ “R+T Rating” The R+T Rating combines rebounding margin, turnovers, and steals, and weights the three stats so that the result is a number that indicates what Clark Kellogg calls “spurtability.”
The R+T Rating Formula is: (R * 2) + (S * .5) + (6 – Opp S) + T, where R is rebounding margin, S is average steals per game (Opp S is opponents steals per game), and T is turnover margin. The numbers are all rounded to one decimal point.
If a team’s R+T rating is 20 or better, and they hail from a power conference, this is a serious potential Final Four team. North Carolina had the top R+T rating last year among the power conference teams, and the Tar Heels came within a second of winning the title. In almost every year since steals have been officially kept as a statistic, the Final Four teams have enjoyed double-digit R+T Ratings.
Look for teams with R+T ratings at 15 or above. These are the teams that will get several additional opportunities to score points and go on scoring runs that put opponents away. When both teams have flashy R+T Ratings, this game becomes much harder to predict, because both teams could go on big scoring spurts.
When the R+T is 7.5 to 15, you have a team that can overcome a few other liabilities to win and still advance to the Final Four if they have exceptional FG% differentials, really difficult schedules, and an ability to win away from home. However, when they run into a team from the 15 or better R+T range with similar shooting percentages and defense, this frequently means the end of the line for the lower R+T rated team.
When the R+T is 4.5 to 7.5, you have a team good enough to win early and get to the Sweet 16 or Elite 8 but not advance past that round, unless said team has a very large field goal percentage difference margin.
When the R+T is 0 to 4.5, you have a team that cannot advance very far in the NCAA Tournament. They might win the Round of 64 and might have some chance to win in the Round of 32, but if they sneak into the Sweet 16, they are a candidate to lose big to a team with the right stuff in the R+T department.
When the R+T stat is negative, this team has the same chance of making the Final Four as a mule has of winning the Kentucky Derby. Many monumental early upsets where a double digit seed upsets a single digit seed frequently comes about when the favorite has a negative R+T rating, or the underdog has a decided R+T Rating advantage along with a halfway decent schedule strength.
A few years ago, Georgetown had a negative R+T rating but was a prohibitive favorite against Ohio U. The Bobcats had a positive R+T rating and decent numbers in the other PiRate criteria. We called for Ohio to upset Georgetown in the first round, and Ohio won by double digits.
The same thing occurred a couple years later when Georgetown once again had a negative R+T rating as the Hoyas faced unknown Florida Gulf Coast. FGCU not only pulled off the upset, they blew GU off the floor.
Last year’s negative R+T teams all lost their first games in the NCAA Tournament. In 2015, there were two Power Conference teams with negative R+T numbers, Oklahoma State and St. John’s. We pegged these two teams to lose immediately as 9-seeds against 8-seeds with positive R+T ratings, and they did just that.
The inferior R+T might win a game over the superior due to other factors, but a poor R+T rated team is eventually going to get thumped when their shots don’t fall, or they run up against a great defense (there are a lot of great defenses in the Dance).

Power Conference Plus Schedule Strength
Up to this point you might have been thinking that it is much easier for New Mexico State or North Dakota to own these gaudy statistics than it is for Arizona or Butler. And, of course, that is correct. We have to adjust this procedure so that teams that play tougher schedules get rewarded and teams that play softer schedules get punished.
Basically, the cut-off line for a Final Four team the way we rate schedule strength is 54.00, although there have been a few long shots like George Mason and Virginia Commonwealth that were below that mark. While the lowest National Champ was Florida in 2007 at 54.30, the average for the last 13 champions has been over 58. Also, bear in mind that of the 17 winners since 2000, 6 came from the ACC, 5 from the Big East , 3 from the SEC, and one each from the American, Big 12, and Big Ten. The Pac-12 has not produced the national champion since Arizona in 1997.

The last national champion that was not a member of a power conference was UNLV in 1990. Before that, it was Texas Western (UTEP) in 1966. In more than 60 seasons, just two teams that were not in power conferences have won the national title! Non-power teams have made it to the Final Four (VCU, Wichita State, George Mason, Penn), so don’t totally discount a team like Gonzaga, Saint Mary’s, and Wichita State to make the Final Four or at least the Elite 8.
In the most recent years, this stat has become quite a bit more important. Villanova and North Carolina were among the tops in schedule strength last year, with Syracuse and Oklahoma being ranked high as well. We have added a bit more weight to schedule strength this year.
Won-Loss percentage Away From Home Floor
This should be obvious. Except in the rarest of instances (like Dayton playing in a First Round Game in 2015), all NCAA Tournament games are played on neutral courts. Some teams play like titans on their home floor but become pansies when playing away from home. It is one thing to accumulate great statistics by scheduling 19 home games, three neutral site games, and eight away games and then going 18-1 at home, 1-2 on the neutral site, and 3-5 on the road to finish 22-8. However, we need to locate the teams that continue to dominate away from home. Combine the road and neutral games played and look at that percentage. When you find a team with a 75% or better win percentage away from home, this team is a legitimate contender in the Big Dance. When this number tops 85%, you have a tough team capable of winning four consecutive games and advancing to the Final Four.
Winning Streaks
The NCAA Tournament Championship requires one team to win six consecutive games (seven if in the First Four) to become the champion. It requires the other Final Four teams to win four or five times to get to the Final Four. Should we expect a team that has not been able to win five conseccutive games during the regular season against all weaker competition to win five games in a row against the elite competition? It is a major plus if a team has more than one 6-game winning streak or one 10-game winning streak during the season.

Putting It All Together
1. Begin with teams from power conferences and schedule strengths better than 54.0 (we will give you each team’s schedule strength in the stats reveal).
1A. If the team does not come from a power conference, but they have dominated this year and their schedule strength is better than 54, they should still be in your consideration as a Final Four contender.
2. Look for teams that had a winning streak of 10 games or more, or teams with both 5+ and 6+ winning streaks during the year. The minimum for two different winning streaks is that one needs to be at least six games and one at least five games.
3. Look for teams with winning records away from home when looking at Sweet 16 contenders and a winning percentage of 66.7% or better when looking for Final Four teams.
4. Look for teams with R+T Ratings of 15.0 or better when selecting Final Four teams, 10.0 or better when selecting Elite 8 teams, and 5.0 or better when selecting Sweet 16 teams. Of course, you have to look at their potential opposition and remember that the better R+T Rating has a big advantage when teams have comparable schedule strengths.
5. While relying more on R+T Rating than rebound margins, remember that no National Champion ever had a negative rebound margin.
6. Look at teams with positive FG% differentials and use this stat along with those above as a significant part of your method for picking winners.
7. Look for these power conference teams that have scoring margins of 8 or above along with schedule strengths of 54 or above.

These are the basic PiRate criteria. You might be shocked to see that there are some key statistics that are not included. Let’s look at some of these stats that the PiRates do not use.

Assists and Assists to Turnover Ratio
While a high number of assists means that a team is most likely a great passing team (and we love great passing teams), this can hide a potentially lethal problem in the Big Dance. Let’s say a team gets 28 field goals and has 24 assists. That may very well indicate this team can pass better than most others. However, it may 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 (like the type that get into the Dance).

Second, and even more importantly, it may indicate that this team cannot get offensive put-backs. As explained earlier, the offensive rebound is about as important as any stat can be in the NCAA Tournament. So, rely on this stat only if you must decide on a toss-up after looking at the more important stats. We would much rather go with a team that has 15 offensive rebound potential than a team that has assists on 85% of its made field goals. The NCAA Tournament is full of tough defenses, weird site lines, tight rims, and even tighter nerves, and the offensive put-back is an even more potent weapon than in the regular season, especially in the Round of 64, the Sweet 16, and the Final Four games. The Round of 32 and Elite 8 rounds tend to be less tense, because it is the second game on the playing floor for the participants.

Free Throw Shooting
You might say we are contradicting the Four Factors with this, but we are not. It is the least important of the Four Factors, and we only apply this caveat to the NCAA Tournament. Free throw shooting is similar to a walk in baseball. During the regular season, a lot of walks lead to a lot of runs, and a lot of free throw shooting leads to a lot of points, but things change in the Big Dance.

Of course, free throw shooting in the clutch decides many ball games, even close NCAA Tournament 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 coming as 1&1 attempts, three coming as one shot after made baskets, and the seven other trips to the line as 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.

A team with one of the top FT% only scores 4.35 more points at the foul line than a team with one of the worst. That is not a lot of points to make up, and when you consider that this is about the maximum possible difference in college basketball, this stat is not all that important. Also consider that teams that shoot 60% of their foul shots but still make the NCAA Tournament are almost always the teams that have the top R+T ratings, which is much more important after the Ides of March.

Teams that make the NCAA Tournament with gaudy free throw percentages frequently get 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 years from 1964 through 1973 when the Bruins won nine titles in 10 seasons, they never once connected on 70% of their free throws in a single season 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 in points scored. If two teams connect on 28 field goal attempts, and 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 28 made field goals and eight treys has scored only one more point than a team with 28 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 threes to win, but instead dominates in the paint on both sides. To put it another way, teams that live and die by the outside shot will almost always die before they can get to the Final Four, if they cannot dominate inside. The tournament is won in the paint. This isn’t the NBA, and there are few Steph Curry’s in college ball.
One Big Star or Two Really Good Players
Teams that get 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. These teams are tough to stop. Usually, it is the mid-major teams that appear to be sleeper teams that could beat a favored opponent because they have one big talent that falls under this category. For instance, South Dakota State’s Mike Daum this year fits that category. He cannot carry the Jackrabbits to the Sweet 16 on his 25 points per game if the rest of the team does not produce as well.
If you have a team with five double figure scorers, they will be harder to defend and will be more consistent on the attack side. It is hard for all five players to slump at once. Also, if you have a team where four or more players have scored 20 or more points in a game, and this team hails from a power conference, this team presents defensive matchup problems for its opponents.
We hope this primer will help you when you fill out your brackets this year. The raw statistics on each of the 68 teams follows at the end of this primer. Coming later today, we will show you how we picked our bracket as well as issue our Red-White-Blue Power Ratings for the First Four Opening Round Games in Dayton on Tuesday and Wednesday.
For those of you new to this website, our Red-White-Blue Ratings are based on three different algorithms using Basketball’a Four Factors. If you don’t know what the Four Factors are, here is an in-depth primer.

THE FOUR FACTORS
Statistician and author Dean Oliver created this quartet of metrics. He did for basketball what the incredible Bill James did for baseball. Oliver wrote the excellent book Basketball on Paper, where he showed that four separate statistical metrics could show how winners beat losers in the NBA. Later experimentation showed that this metric worked for all levels of organized basketball when strength of schedule is factored into the metric, and the weighting of each factor was altered as the talent level of play decreased.

The four factors are:
1. Effective Field Goal Percentage
2. Rebound Rate
3. Turnover Rate
4. Free Throw Rate

Each factor applies to both offense and defense, so in essence, there are really eight factors.
Each Factor has a formula that can be calculated if you have the statistics. Don’t worry. Our team has compiled all the statistics for every one of the 68 teams in the Dance.

For those math lovers of statistics, and we know a lot of you from baseball, here are the Four Factor stats and their fomulas:

1. Effective FG% = (FGM + (.5 * 3ptM))/FGA where FGM is field goals made, 3ptM is three-pointers made, and FGA is field goals attempted.
If a team made 800 FG, 250 3-pointers, and attempted 1750 field goals, their EFG% is:
(800+(.5*250))/1750 = .529 or 52.9%

2. Offensive Rebound Rate = Offensive Rebounds/(Offensive Rebounds + Opponents’ Defensive Rebounds)
If a team has 500 offensive rebounds and their opponents have 850 defensive rebounds, their Offensive Rebound Rate is:
500/(500+850) = .370 or 37.0%
The defensive equivalent of this factor is defensive rebound rate (Opponents Offensive Rebounds/(Opponents Offensive Rebounds + The Defense’s Defensive Rebounds)
If a team’s opponents have 400 offensive rebounds, while the team has 800 defensive rebounds, the defensive rebound rate is: 400/(400+800) = .333 or 33.3%

3. Turnover Rate = Turnovers per 100 possessions that do not include offensive rebounds. Possessions at the college level can be estimated with incredible accuracy by this formula:
(FGA + (.475*FTA)-OR+TO)/G, where FGA is field goal attempts, FTA is free throw attempts, OR is offensive rebounds, TO is turnovers, and G is games played.
We remove offensive rebounds from the TO Rate formula, because very few turnovers occur following an offensive rebound. Most of the time a shot is taken immediately, and this would skew the factor.
If a team has 1700 FGA, 650 FTA, 425 OR, and 375 TO in 30 games played, their average actual possessions per game is:
(1700+(.475*650)-425+375)/30 = 65.3
Removing the offensive rebounds, their true possessions are:
1700+(.475*650)+375 = 2,384 (rounded from 2383.75)
Once again, the formula for TO Rate is: percentage of Turnovers per / possessions
(TO/Possessions) * 100
Thus for the team above with 375 TO in 2,384 Possessions, their TO Rate is:
100* (375/2384) = 15.7%

4. Free Throw Rate: Oliver and others determined that getting to the line was actually more important than making the foul shots, so they did not include made free throws in their equation.
Their formula was simply: FTA/FGA, as they believed that getting the other team in foul trouble was the most important part.
Later statisticans changed this formulas to FT Made/FGA, which included made free throws, but it also erred by making teams that do not attempt many field goals but lead late in games look much better than they really were. If a team like Northern Iowa attempted just 50 field goals per game and won a lot of games by three or four points, going to the foul line many times late in the game, they would pad this stat by making a lot of FT in the final minutes when the opponent was forced to foul.
A third group of statisticians, including the statheads at the PiRate Ratings, believe that free throws made per 100 possessions is a better metric, and thus we go with this rating, which we call FT Rate*:
If the team above with 65.3 possessions per game averages 17 made free throws per game, then their FT Rate* is:
17 / 65.3 * 100 = 26.0

**************************************

All The Stats On The 68 Teams

OFFENSE	G	FG	FGA	3pt	3ptA	FT	FTA	OReb	DReb	Reb	To	Stl	Pts
Arizona	34	891	1873	229	576	582	768	350	901	1251	390	187	2593
Arkansas	33	920	1991	218	592	590	774	375	832	1207	385	249	2648
Baylor	32	838	1738	216	601	435	607	412	807	1219	430	162	2327
Bucknell	34	915	1902	277	734	480	707	293	878	1171	451	244	2587
Butler	31	831	1740	237	652	466	630	272	723	995	315	193	2365
Cincinnati	33	897	1954	248	709	434	638	405	821	1226	336	248	2476
Creighton	34	1052	2072	297	743	391	573	278	908	1186	423	211	2792
Dayton	31	802	1705	251	649	515	748	267	801	1068	370	243	2370
Duke	35	968	2029	288	767	599	790	366	905	1271	395	207	2823
East Tennessee St.	34	935	1905	256	669	591	840	345	892	1237	502	284	2717
Florida	32	851	1892	248	685	555	764	367	826	1193	378	243	2505
Florida Gulf Coast	33	978	1947	213	608	452	644	370	873	1243	411	201	2621
Florida St.	33	982	2032	227	637	530	766	389	856	1245	390	243	2721
Gonzaga	33	1002	1934	241	631	546	740	308	1022	1330	372	236	2791
Iona	34	951	2091	332	836	502	652	326	897	1223	411	235	2736
Iowa St.	33	971	2072	329	818	398	572	308	845	1153	335	261	2669
Jacksonville St.	34	834	1823	248	666	455	639	349	872	1221	463	156	2371
Kansas	32	946	1943	279	689	476	715	385	859	1244	419	222	2647
Kansas St.	33	817	1782	234	649	499	724	314	766	1080	431	258	2367
Kent St.	35	955	2231	248	781	534	743	524	894	1418	458	227	2692
Kentucky	33	999	2096	234	664	608	873	416	911	1327	394	200	2840
Louisville	32	893	1960	228	635	467	682	425	845	1270	357	216	2481
Marquette	31	894	1834	325	755	445	571	274	756	1030	378	228	2558
Maryland	32	805	1786	265	730	498	713	344	805	1149	416	173	2373
Miami (Fla.)	32	792	1748	205	571	431	600	354	799	1153	407	204	2220
Michigan	34	893	1857	318	837	443	572	260	744	1004	322	201	2547
Michigan St.	33	850	1817	259	689	408	615	313	898	1211	467	147	2367
Middle Tennessee	34	961	1962	217	590	412	590	334	874	1208	355	233	2551
Minnesota	33	863	1985	203	589	555	785	374	943	1317	385	189	2484
Mount St. Mary’s	34	831	1873	246	690	415	615	260	770	1030	447	211	2323
Nevada	34	907	2017	312	811	593	843	374	949	1323	379	181	2719
New Mexico St.	33	885	1893	244	725	591	830	426	886	1312	454	160	2605
New Orleans	31	801	1701	138	429	525	737	375	737	1112	519	242	2265
North Carolina	34	1055	2239	246	672	531	753	537	941	1478	405	236	2887
North Dakota	31	894	1850	218	563	490	682	286	829	1115	413	245	2496
Northern Kentucky	34	902	1964	292	827	493	729	378	901	1279	460	194	2589
Northwestern	34	860	1975	242	709	455	606	366	865	1231	359	172	2417
Notre Dame	34	937	2033	320	830	458	573	317	831	1148	322	245	2652
Oklahoma St.	32	922	1986	287	716	606	770	438	737	1175	422	249	2737
Oregon	34	954	1982	292	773	489	688	355	885	1240	394	221	2689
Princeton	29	750	1659	290	758	301	410	239	731	970	289	198	2091
Providence	32	779	1744	230	625	460	666	287	787	1074	403	215	2248
Purdue	32	894	1864	288	709	488	639	315	902	1217	418	167	2564
Rhode Island	33	860	1902	207	610	494	752	391	844	1235	372	211	2421
Saint Mary’s	32	842	1698	282	706	338	452	308	830	1138	337	133	2304
Seton Hall	32	846	1880	196	581	458	712	418	848	1266	434	222	2346
SMU	33	864	1825	267	663	468	672	399	872	1271	361	193	2463
South Carolina	32	787	1897	216	637	516	747	398	765	1163	428	251	2306
South Dakota St.	34	863	1880	313	863	598	771	307	884	1191	439	177	2637
Texas Southern	34	844	1955	198	666	643	877	397	804	1201	397	244	2529
Troy	36	958	2094	306	844	602	833	392	933	1325	445	220	2824
UC-Davis	34	830	1898	212	599	524	788	347	866	1213	482	193	2396
UCLA	33	1113	2144	327	807	429	576	322	973	1295	381	202	2982
UNC-Central	33	886	1938	250	735	457	671	390	893	1283	397	199	2479
UNC-Wilmington	34	1046	2170	326	891	478	691	408	813	1221	354	230	2896
USC	33	897	1977	259	713	544	736	356	837	1193	367	239	2597
Vanderbilt	34	794	1841	337	895	498	642	279	899	1178	420	140	2423
VCU	34	916	1985	197	589	510	721	375	871	1246	426	256	2539
Vermont	34	916	1848	219	594	450	641	316	848	1164	383	193	2501
Villanova	34	913	1837	300	810	515	649	291	844	1135	381	246	2641
Virginia	32	797	1717	224	570	313	442	282	772	1054	305	181	2131
Virginia Tech	32	864	1764	283	703	525	715	234	809	1043	388	128	2536
Wake Forest	32	898	1902	259	670	590	763	342	836	1178	377	175	2645
West Virginia	34	986	2153	257	711	558	823	487	783	1270	417	353	2787
Wichita St.	34	949	2004	296	725	596	812	405	981	1386	379	233	2790
Winthrop	32	866	1895	304	814	515	715	313	884	1197	421	210	2551
Wisconsin	33	869	1915	251	707	401	624	407	830	1237	358	229	2390
Xavier	34	876	1929	239	703	546	793	415	864	1279	435	209	2537

 

DEFENSE	G	FG	FGA	3pt	3ptA	FT	FTA	OReb	DReb	Reb	To	Stl	Pts
Arizona	34	808	1945	218	712	391	567	319	700	1019	405	161	2225
Arkansas	33	824	1971	246	742	540	772	413	779	1192	430	162	2434
Baylor	32	713	1791	197	623	384	540	332	601	933	357	172	2007
Bucknell	34	830	1951	211	620	419	638	332	802	1134	474	239	2290
Butler	31	737	1661	209	625	437	623	277	695	972	420	153	2120
Cincinnati	33	689	1806	223	666	396	537	348	727	1075	457	116	1997
Creighton	34	907	2076	255	765	396	584	371	848	1219	481	226	2465
Dayton	31	712	1724	221	679	417	591	301	761	1062	463	139	2062
Duke	35	908	2096	175	594	453	647	376	795	1171	419	167	2444
East Tennessee St.	34	793	1908	267	751	505	702	329	756	1085	533	230	2358
Florida	32	754	1846	179	583	443	627	337	794	1131	479	174	2130
Florida Gulf Coast	33	800	1899	230	744	440	643	341	698	1039	425	200	2270
Florida St.	33	798	1936	240	698	516	723	374	753	1127	474	166	2352
Gonzaga	33	741	2015	192	641	344	523	348	726	1074	416	172	2018
Iona	34	916	2120	271	753	493	708	416	888	1304	449	162	2596
Iowa St.	33	876	2049	254	729	370	527	398	875	1273	474	153	2376
Jacksonville St.	34	785	1891	263	701	467	649	330	750	1080	375	203	2300
Kansas	32	825	1968	235	658	431	606	375	739	1114	430	226	2316
Kansas St.	33	775	1825	236	616	423	588	369	750	1119	503	208	2209
Kent St.	35	894	2080	258	747	485	690	380	825	1205	496	212	2531
Kentucky	33	850	2006	203	656	466	695	342	814	1156	482	157	2369
Louisville	32	709	1791	197	638	492	712	340	746	1086	440	164	2107
Marquette	31	823	1803	227	615	452	648	308	733	1041	409	199	2325
Maryland	32	772	1867	203	605	423	602	375	751	1126	403	194	2170
Miami (Fla.)	32	731	1764	202	611	374	508	309	698	1007	380	196	2038
Michigan	34	847	1821	198	525	346	508	305	760	1065	437	145	2238
Michigan St.	33	777	1911	217	626	485	672	338	753	1091	363	193	2256
Middle Tennessee	34	743	1783	205	642	462	656	281	755	1036	458	162	2153
Minnesota	33	829	2084	213	699	409	599	405	870	1275	421	188	2280
Mount St. Mary’s	34	863	1925	183	532	423	641	407	873	1280	507	215	2332
Nevada	34	890	2095	228	743	404	589	334	857	1191	384	189	2412
New Mexico St.	33	792	1911	184	632	451	667	361	724	1085	454	174	2219
New Orleans	31	767	1746	199	642	415	601	345	646	991	505	263	2148
North Carolina	34	838	2013	274	799	451	628	310	737	1047	464	214	2401
North Dakota	31	788	1796	211	601	470	687	303	780	1083	472	198	2257
Northern Kentucky	34	891	2026	224	682	422	600	313	806	1119	415	202	2428
Northwestern	34	770	1911	220	656	452	678	383	820	1203	406	192	2212
Notre Dame	34	865	2007	234	694	389	533	373	838	1211	435	180	2353
Oklahoma St.	32	846	1800	219	612	586	812	342	720	1062	487	208	2497
Oregon	34	803	2002	233	748	372	520	364	749	1113	468	160	2211
Princeton	29	631	1516	191	576	330	478	231	735	966	388	307	1783
Providence	32	786	1783	200	612	360	535	307	799	1106	447	202	2132
Purdue	32	811	1962	210	650	317	445	292	704	996	385	206	2149
Rhode Island	33	711	1758	152	524	567	799	350	790	1140	434	174	2141
Saint Mary’s	32	686	1676	143	472	293	427	227	615	842	300	176	1808
Seton Hall	32	783	1813	211	621	469	654	289	765	1054	393	219	2246
SMU	33	702	1817	270	826	304	442	304	658	962	392	160	1978
South Carolina	32	671	1686	168	574	553	778	344	789	1133	552	197	2063
South Dakota St.	34	938	2077	361	960	394	539	342	803	1145	391	230	2631
Texas Southern	34	902	2038	188	581	447	656	422	834	1256	463	176	2439
Troy	36	904	2120	282	841	490	680	367	864	1231	455	209	2580
UC-Davis	34	829	1955	237	717	448	633	330	836	1166	482	232	2343
UCLA	33	912	2179	284	784	378	563	383	777	1160	399	216	2486
UNC-Central	33	766	1959	205	708	355	554	410	775	1185	456	151	2092
UNC-Wilmington	34	912	1912	185	551	539	752	316	835	1151	496	166	2548
USC	33	893	2074	276	757	353	495	379	802	1181	424	184	2415
Vanderbilt	34	836	1975	220	655	425	604	333	839	1172	367	186	2317
VCU	34	775	1852	196	580	512	737	330	818	1148	500	187	2258
Vermont	34	781	1858	190	576	342	484	305	723	1028	443	184	2094
Villanova	34	799	1912	240	768	297	417	321	691	1012	452	176	2135
Virginia	32	610	1542	191	611	369	524	246	700	946	413	158	1780
Virginia Tech	32	876	1969	251	697	378	529	345	764	1109	375	175	2381
Wake Forest	32	860	1901	264	739	509	704	317	763	1080	370	193	2493
West Virginia	34	759	1791	227	650	510	755	374	806	1180	695	190	2255
Wichita St.	34	713	1887	227	735	470	680	307	782	1089	475	177	2123
Winthrop	32	787	1941	211	681	461	636	350	815	1165	450	195	2246
Wisconsin	33	723	1782	221	589	350	475	285	744	1029	433	175	2017
Xavier	34	862	1907	253	748	449	642	288	767	1055	416	218	2426

 

Team	PPG	Def PPG	Marg.	FG%-Marg	Reb-Marg.	TO Marg.	R+T	W-L Road	SOS	Off Poss	Def Poss	Poss/G	Seed
Arizona	76.3	65.4	10.8	6.0	6.8	0.4	18.1	15-3	58.18	2278	2300	67.3	2
Arkansas	80.2	73.8	6.5	4.4	0.5	1.4	7.1	10-6	55.53	2369	2355	71.6	8
Baylor	72.7	62.7	10.0	8.4	8.9	-2.3	18.8	10-5	59.46	2044	2073	64.3	3
Bucknell	76.1	67.4	8.7	5.6	1.1	0.7	5.4	9-6	48.90	2396	2396	70.5	13
Butler	76.3	68.4	7.9	3.4	0.7	3.4	9.0	10-5	59.10	2082	2100	67.5	4
Cincinnati	75.0	60.5	14.5	7.8	4.6	3.7	19.1	11-5	54.46	2188	2170	66.0	6
Creighton	82.1	72.5	9.6	7.1	-1.0	1.7	2.2	12-5	56.81	2489	2463	72.8	6
Dayton	76.5	66.5	9.9	5.7	0.2	3.0	8.8	9-6	54.65	2163	2167	69.8	7
Duke	80.7	69.8	10.8	4.4	2.9	0.7	10.6	12-7	59.78	2433	2446	69.7	2
East Tennessee St.	79.9	69.4	10.6	7.5	4.5	0.9	13.3	14-5	49.32	2461	2445	72.2	13
Florida	78.3	66.6	11.7	4.1	1.9	3.2	11.4	15-7	59.41	2266	2286	71.1	4
Florida Gulf Coast	79.4	68.8	10.6	8.1	6.2	0.4	15.8	10-4	47.19	2294	2288	69.4	14
Florida St.	82.5	71.3	11.2	7.1	3.6	2.5	14.3	7-8	58.36	2397	2379	72.4	3
Gonzaga	84.6	61.2	23.4	15.0	7.8	1.3	21.2	17-0	54.02	2350	2331	70.9	1
Iona	80.5	76.4	4.1	2.3	-2.4	1.1	1.0	14-8	49.90	2486	2489	73.2	14
Iowa St.	80.9	72.0	8.9	4.1	-3.6	4.2	2.3	11-7	58.18	2371	2375	71.9	5
Jacksonville St.	69.7	67.6	2.1	4.2	4.1	-2.6	8.0	15-9	46.93	2241	2244	66.0	15
Kansas	82.7	72.4	10.3	6.8	4.1	0.3	10.9	14-3	58.10	2317	2311	72.3	1
Kansas St.	71.7	66.9	4.8	3.4	-1.2	2.2	3.4	9-8	56.53	2243	2238	67.9	11
Kent St.	76.9	72.3	4.6	-0.2	6.1	1.1	16.4	12-7	48.67	2518	2524	72.0	14
Kentucky	86.1	71.8	14.3	5.3	5.2	2.7	17.3	14-3	58.27	2489	2476	75.2	2
Louisville	77.5	65.8	11.7	6.0	5.8	2.6	18.3	8-7	60.87	2216	2229	69.5	2
Marquette	82.5	75.0	7.5	3.1	-0.4	1.0	3.5	5-9	56.05	2209	2212	71.3	10
Maryland	74.2	67.8	6.3	3.7	0.7	-0.4	3.7	11-3	56.23	2197	2181	68.4	6
Miami (Fla.)	69.4	63.7	5.7	3.9	4.6	-0.8	11.3	7-9	56.85	2086	2076	65.0	8
Michigan	74.9	65.8	9.1	1.6	-1.8	3.4	4.5	9-8	57.52	2191	2194	64.5	7
Michigan St.	71.7	68.4	3.4	6.1	3.6	-3.2	6.5	5-12	59.07	2263	2255	68.5	9
Middle Tennessee	75.0	63.3	11.7	7.3	5.1	3.0	17.8	17-2	50.19	2263	2272	66.7	12
Minnesota	75.3	69.1	6.2	3.7	1.3	1.1	6.8	7-6	58.18	2369	2385	72.0	5
Mount St. Mary’s	68.3	68.6	-0.3	-0.5	-7.4	1.8	-10.2	8-11	48.10	2352	2329	68.8	16
Nevada	80.0	70.9	9.0	2.5	3.9	0.1	11.0	15-5	51.96	2422	2425	71.3	12
New Mexico St.	78.9	67.2	11.7	5.3	6.9	0.0	16.9	11-4	47.15	2315	2321	70.2	14
New Orleans	73.1	69.3	3.8	3.2	3.9	-0.5	8.8	9-8	46.14	2195	2191	70.8	16
North Carolina	84.9	70.6	14.3	5.5	12.7	1.7	30.3	11-7	59.04	2465	2465	72.5	1
North Dakota	80.5	72.8	7.7	4.4	1.0	1.9	7.5	11-7	44.82	2301	2291	74.1	15
Northern Kentucky	76.1	71.4	4.7	1.9	4.7	-1.3	11.0	12-8	48.18	2392	2413	70.7	15
Northwestern	71.1	65.1	6.0	3.3	0.8	1.4	5.9	9-7	55.60	2256	2256	66.4	8
Notre Dame	78.0	69.2	8.8	3.0	-1.9	3.3	3.9	9-7	57.33	2310	2322	68.1	5
Oklahoma St.	85.5	78.0	7.5	-0.6	3.5	2.0	12.5	9-7	58.52	2336	2331	72.9	10
Oregon	79.1	65.0	14.1	8.0	3.7	2.2	14.2	12-5	56.84	2348	2353	69.1	3
Princeton	72.1	61.5	10.6	3.6	0.1	3.4	2.5	13-5	49.91	1904	1900	65.6	12
Providence	70.3	66.6	3.6	0.6	-1.0	1.4	2.4	5-9	56.05	2176	2177	68.0	11
Purdue	80.1	67.2	13.0	6.6	6.9	-1.0	15.0	10-5	55.84	2271	2266	70.9	4
Rhode Island	73.4	64.9	8.5	4.8	2.9	1.9	11.6	11-6	55.20	2240	2222	67.6	11
Saint Mary’s	72.0	56.5	15.5	8.7	9.3	-1.2	19.9	13-2	54.34	1942	1952	60.8	7
Seton Hall	73.3	70.2	3.1	1.8	6.6	-1.3	14.6	9-9	56.38	2234	2228	69.7	9
SMU	74.6	59.9	14.7	8.7	9.4	0.9	23.7	12-4	53.27	2106	2115	64.0	6
South Carolina	72.1	64.5	7.6	1.7	0.9	3.9	9.5	7-7	56.25	2282	2264	71.0	7
South Dakota St.	77.6	77.4	0.2	0.7	1.4	-1.4	3.1	7-14	50.02	2378	2382	70.0	16
Texas Southern	74.4	71.7	2.6	-1.1	-1.6	1.9	3.1	13-11	44.79	2372	2391	70.0	16
Troy	78.4	71.7	6.8	3.1	2.6	0.3	8.8	12-10	47.40	2543	2531	70.5	15
UC-Davis	70.5	68.9	1.6	1.3	1.4	0.0	4.8	11-12	44.11	2407	2408	70.8	16
UCLA	90.4	75.3	15.0	10.1	4.1	0.5	11.2	12-3	53.96	2477	2462	74.8	3
UNC-Central	75.1	63.4	11.7	6.6	3.0	1.8	12.2	14-6	38.41	2264	2268	68.7	16
UNC-Wilmington	85.2	74.9	10.2	0.5	2.1	4.2	12.8	16-4	51.48	2444	2449	72.0	12
USC	78.7	73.2	5.5	2.3	0.4	1.7	6.5	9-6	54.42	2338	2354	71.1	11
Vanderbilt	71.3	68.1	3.1	0.8	0.2	-1.6	1.4	8-10	61.16	2287	2296	67.4	9
VCU	74.7	66.4	8.3	4.3	2.9	2.2	12.2	11-7	55.31	2378	2372	69.9	10
Vermont	73.6	61.6	12.0	7.5	4.0	1.8	13.2	13-4	49.16	2219	2226	65.4	13
Villanova	77.7	62.8	14.9	7.9	3.6	2.1	13.8	17-2	58.04	2235	2241	65.8	1
Virginia	66.6	55.6	11.0	6.9	3.4	3.4	14.0	10-6	59.73	1950	1958	61.1	5
Virginia Tech	79.3	74.4	4.8	4.5	-2.1	-0.4	-2.0	7-8	55.01	2258	2250	70.4	9
Wake Forest	82.7	77.9	4.8	2.0	3.1	-0.2	8.6	8-10	58.32	2299	2288	71.7	11
West Virginia	82.0	66.3	15.6	3.4	2.6	8.2	19.1	9-6	55.57	2474	2471	72.7	4
Wichita St.	82.1	62.4	19.6	9.6	8.7	2.8	24.5	14-3	50.79	2364	2378	69.7	10
Winthrop	79.7	70.2	9.5	5.2	1.0	0.9	6.1	12-3	47.36	2343	2343	73.2	13
Wisconsin	72.4	61.1	11.3	4.8	6.3	2.3	19.0	10-7	54.48	2162	2156	65.4	8
Xavier	74.6	71.4	3.3	0.2	6.6	-0.6	15.3	9-9	58.75	2326	2340	68.6	11

 

Team	EFG	DEFG	OR%	DOR%	TO%	DTO%	FT*	DFT*	Win Streaks
Arizona	53.7	47.1	33.3	26.1	14.8	15.5	25.6	17.0	15	5
Arkansas	51.7	48.0	32.5	33.2	14.0	15.5	24.9	22.9	8	5
Baylor	54.4	45.3	40.7	29.1	17.5	14.8	21.3	18.5	15	5
Bucknell	55.4	47.9	26.8	27.4	16.8	17.4	20.0	17.5	7	6
Butler	54.6	50.7	28.1	27.7	13.4	17.7	22.4	20.8	8	4
Cincinnati	52.3	44.3	35.8	29.8	13.0	18.1	19.8	18.2	15	5
Creighton	57.9	49.8	24.7	29.0	15.3	17.0	15.7	16.1	13	5
Dayton	54.4	47.7	26.0	27.3	15.2	18.8	23.8	19.2	9	5
Duke	54.8	47.5	31.5	29.4	14.1	14.8	24.6	18.5	10	7
East Tennessee St.	55.8	48.6	31.3	26.9	17.9	19.2	24.0	20.7	6	5
Florida	51.5	45.7	31.6	29.0	14.4	18.3	24.5	19.4	9	7
Florida Gulf Coast	55.7	48.2	34.6	28.1	15.4	16.2	19.7	19.2	7	7
Florida St.	53.9	47.4	34.1	30.4	14.0	17.2	22.1	21.7	12	4
Gonzaga	58.0	41.5	29.8	25.4	14.0	15.5	23.2	14.8	29	3
Iona	53.4	49.6	26.9	31.7	14.6	15.5	20.2	19.8	6	4
Iowa St.	54.8	49.0	26.0	32.0	12.5	17.1	16.8	15.6	6	5
Jacksonville St.	52.6	48.5	31.8	27.5	17.9	14.6	20.3	20.8	4	4
Kansas	55.9	47.9	34.3	30.4	15.5	16.0	20.5	18.7	18	8
Kansas St.	52.4	48.9	29.5	32.5	16.9	19.3	22.2	18.9	7	5
Kent St.	48.4	49.2	38.8	29.8	15.1	17.1	21.2	19.2	5	4
Kentucky	53.2	47.4	33.8	27.3	13.6	17.1	24.4	18.8	11	7
Louisville	51.4	45.1	36.3	28.7	13.5	17.1	21.1	22.1	6	5
Marquette	57.6	51.9	27.2	28.9	15.2	16.2	20.1	20.4	5	3
Maryland	52.5	46.8	31.4	31.8	16.4	15.8	22.7	19.4	7	7
Miami (Fla.)	51.2	47.2	33.7	27.9	16.7	15.9	20.7	18.0	7	4
Michigan	56.7	51.9	25.5	29.1	13.1	17.5	20.2	15.8	5	4
Michigan St.	53.9	46.3	29.4	27.3	18.1	14.0	18.0	21.5	4	3
Middle Tennessee	54.5	47.4	30.7	24.3	13.7	17.9	18.2	20.3	10	10
Minnesota	48.6	44.9	30.1	30.0	14.0	15.1	23.4	17.2	8	6
Mount St. Mary’s	50.9	49.6	22.9	34.6	17.1	18.5	17.6	18.2	8	4
Nevada	52.7	47.9	30.4	26.0	13.6	13.9	24.5	16.7	9	7
New Mexico St.	53.2	46.3	37.0	28.9	16.6	16.9	25.5	19.4	20	5
New Orleans	51.1	49.6	36.7	31.9	20.2	19.9	23.9	18.9	5	5
North Carolina	52.6	48.4	42.2	24.8	13.5	16.7	21.5	18.3	7	6
North Dakota	54.2	49.7	26.8	26.8	16.0	18.2	21.3	20.5	6	4
Northern Kentucky	53.4	49.5	31.9	25.8	16.6	15.2	20.6	17.5	6	6
Northwestern	49.7	46.0	30.9	30.7	13.7	15.4	20.2	20.0	9	6
Notre Dame	54.0	48.9	27.4	31.0	12.3	16.1	19.8	16.8	9	7
Oklahoma St.	53.7	53.1	37.8	31.7	15.2	18.2	25.9	25.1	5	5
Oregon	55.5	45.9	32.2	29.1	14.6	17.2	20.8	15.8	17	8
Princeton	53.9	47.9	24.5	24.0	13.5	18.2	15.8	17.4	19	2
Providence	51.3	49.7	26.4	28.1	16.4	18.0	21.1	16.5	6	6
Purdue	55.7	46.7	30.9	24.5	16.2	15.0	21.5	14.0	7	6
Rhode Island	50.7	44.8	33.1	29.3	14.1	16.9	22.1	25.5	8	4
Saint Mary’s	57.9	45.2	33.4	21.5	15.0	13.8	17.4	15.0	9	7
Seton Hall	50.2	49.0	35.3	25.4	16.4	15.6	20.5	21.1	6	5
SMU	54.7	46.1	37.7	25.9	14.4	16.2	22.2	14.4	16	10
South Carolina	47.2	44.8	33.5	31.0	16.0	21.2	22.6	24.4	8	5
South Dakota St.	54.2	53.9	27.7	27.9	16.3	14.4	25.1	16.5	6	3
Texas Southern	48.2	48.9	32.3	34.4	14.3	16.5	27.1	18.7	9	6
Troy	53.1	49.3	31.2	28.2	15.2	15.7	23.7	19.4	6	4
UC-Davis	49.3	48.5	29.3	27.6	17.5	17.6	21.8	18.6	4	4
UCLA	59.5	48.4	29.3	28.2	13.6	14.0	17.3	15.4	13	10
UNC-Central	52.2	44.3	33.5	31.5	15.0	17.0	20.2	15.7	13	5
UNC-Wilmington	55.7	52.5	32.8	28.0	12.4	17.9	19.6	22.0	9	8
USC	51.9	49.7	30.7	31.2	13.6	15.5	23.3	15.0	14	5
Vanderbilt	52.3	47.9	25.0	27.0	16.4	14.0	21.8	18.5	4	3
VCU	51.1	47.1	31.4	27.5	15.5	18.5	21.4	21.6	9	8
Vermont	55.5	47.1	30.4	26.5	15.1	17.5	20.3	15.4	21	4
Villanova	57.9	48.1	29.6	27.6	15.1	17.6	23.0	13.3	14	7
Virginia	52.9	45.8	28.7	24.2	13.7	18.7	16.1	18.8	7	5
Virginia Tech	57.0	50.9	23.4	29.9	15.6	14.4	23.3	16.8	8	4
Wake Forest	54.0	52.2	31.0	27.5	14.3	14.2	25.7	22.2	4	3
West Virginia	51.8	48.7	37.7	32.3	14.1	24.4	22.6	20.6	8	4
Wichita St.	54.7	43.8	34.1	23.8	13.7	17.7	25.2	19.8	15	6
Winthrop	53.7	46.0	27.7	28.4	15.9	16.7	22.0	19.7	8	7
Wisconsin	51.9	46.8	35.4	25.6	13.9	17.7	18.5	16.2	9	8
Xavier	51.6	51.8	35.1	25.0	15.9	15.8	23.5	19.2	7	6

Check back later Tuesday for our Round by Round Bracket Selections, as well as our Red-White-Blue Ratings for the First Four games in Dayton.