## Statistical Analysis of the 2011 NCAA Tournament field

This weekend I did a statistical analysis of every team in this year’s NCAA Tournament, except for the teams that are the 16th seeds or are playing for the right to be the 16th seed.  The only way those teams would advance past Round 2 is if the 1st seeds did not show up.

The table with the statistics is at the bottom of the post.  First I will explain my approach so you can decide whether you might find my work useful or not in determining your selections.

Calculations

Since the best predictor of a basketball team’s future success  is the team’s offensive and defensive efficiency averages, the evaluation I did was centered on two different approaches that basically look at adjusted efficiency, adjusted for strength of schedule.

First, I calculated each team’s adjusted Marginal Win Score, using the offensive and defensive statistics provided by Statfox.com.  Win Score is (Pts + Rebs + Stls + .5Ass + .5Blks – FGAs – TOs – .5FTAs – .5PFs).  Marginal Win Score is the Team’s Win Score – the Team’s Opponents’ Win Score divided by 2.

The Win Score calculation accounts for the first four columns of the table (not including the column with each team’s name).  The first column is the Team’s Win Score.  For an NCAA Champion, you generally want that above 42.00.  The second column is Opponent Win Score.  For an NCAA Champion, you generally want that below 20.00.  The third column is the Team’s Raw Marginal Win Score.  I included this number to show how successful each team has been, regardless of schedule.

The fourth column is the Team’s Adjusted Marginal Win Score.  Adjusted Marginal Win Score is simply the Marginal Win Score of the team’s collective schedule plus the team’s raw Marginal Win Score.  Some teams — like Illinois — didn’t post the greatest Win Score differentials, but their numbers improve because of massive adjustments brought on by brutal schedules.  In college basketball, you have to adjust for schedule because different team’s play vastly different levels of competition.

At the same time, I get a little skittish with huge adjustments.  At some point, a team has to actually win games, not just play well against strong competition.  I included each team’s raw Marginal Win Score for this reason.  Yesterday Digger Phelps made a sound point.  He said teams that are successful during the season, regardless of schedule, tend to do better than teams that played well but lost a lot of games against a tough schedule (Georgetown, for example).  I don’t know if that is true, but you have the information to factor that in if you wish.

Adjusted Efficiency Differential measures the same thing as Adjusted Marginal Win Score, but does it in a more straightforward manner.

Adjusted Efficiency Differential is simply a team’s Efficiency Differential (Points per 100 possessions) plus their collective Opponents Efficiency Differential.  As an example, Missouri posted an offensive efficiency average of 113.0 and a defensive average of 97.8 (+15.20).  Their collective schedule posted an offensive efficiency average of 105.4 and a defensive average of 98.8 (+6.60).   Therefore, Missouri’s Adjusted Efficiency Differential was (+21.80).

The thinking is, Adjusted Efficiency Differential levels the playing field by measuring each team’s performance against the performance that a vast collection of other teams put up against the same schedule.  Its not perfect, but I don’t think you can do much better without getting into more complex math.

Effective Field Goal Differential

I added this number to this year’s analysis because Dean Oliver found that it was by far the most important of his “Four Factors”.  Effective Field Goal Differential is simply a team’s Effective Field Goal percentage minus their Opponents Effective Field Goal Percentage.  There is no adjustment made to this number.

The Table

Below I have the table with the statistics.  Its long.  I ordered each team according to the sum total of the last three columns.  That doesn’t make it a perfect ordering, but it gives some indication.

2011 NCAA TOURNAMENT

 WS oppWS MWS adjMWS adjEffDiff EfgDiff Kansas 49.01 16.81 32.21 41.81 33.6 13.4 Ohio St 45.41 16.81 28.61 40.15 36.5 8.1 Duke 41.21 19.35 21.91 33.08 32.1 9.4 Pitt 41.51 18.61 22.91 34.32 30.2 7.7 Texas 39.05 15.85 23.21 33.33 28.9 8.8 Kentucky 42.01 21.85 20.15 31.32 27.2 8.3 Syracuse 44.51 23.81 20.71 32.91 25.7 7.2 Washington 43.25 23.01 20.24 30.63 26.9 7.9 SD State 40.01 18.51 21.51 30.59 27.8 6.8 Notre Dame 43.95 24.55 19.41 31.61 24.9 7.5 Purdue 37.45 22.25 15.21 29.23 28.9 5.5 BYU 44.21 23.31 20.91 28.57 27.5 5.9 Louisville 40.51 23.11 17.41 28.05 24.1 8.7 Wisconsin 35.91 22.01 13.91 27.93 28.5 4.1 UNC 40.91 23.55 17.51 31.71 24.8 3.9 Illinois 36.65 24.51 12.15 28.64 22.3 7.7 Georgetown 36.41 26.41 10.01 28.05 22.5 7.8 Utah St 39.25 15.71 23.55 23.81 23.1 9.2 Connecticut 38.91 25.61 13.31 27.85 21.9 3.3 Gonzaga 41.01 19.21 21.81 25.31 19.9 7.6 Vanderbilt 39.05 24.91 14.14 23.94 20.7 8.1 West Virg 33.61 23.81 9.81 27.33 22.6 2.8 Cincinnati 35.11 18.51 16.59 24.51 23.1 3.5 Florida 38.05 22.31 15.74 24.97 21.4 3.6 Arizona 36.55 22.95 13.61 22.56 21.1 5.9 Marquette 40.05 26.51 13.54 25.62 21.3 1.4 Belmont 42.15 17.25 24.91 18.03 21.5 8.8 Kans State 32.21 19.35 12.86 24.93 20.6 2.7 Flor State 34.01 19.25 14.76 23.97 17.1 6.6 Villanova 37.31 25.25 12.06 24.91 19.1 3.3 Missouri 40.45 26.21 14.24 22.81 21.8 2.6 Geor Mason 39.11 20.41 18.71 19.71 18.7 7.8 UNLV 35.91 26.51 9.39 18.08 20.4 5.9 Mich St 33.41 26.91 6.51 24.95 17.2 1.1 Texas A&M 32.81 19.71 13.11 20.24 18.7 3.8 Clemson 32.85 20.35 12.49 20.29 17.1 4.8 Richmond 37.45 21.85 15.61 18.19 17.1 8.9 Temple 38.25 22.41 15.84 20.52 17.2 4.1 Xavier 36.01 22.46 13.56 18.09 17.3 5.6 UCLA 33.81 23.55 10.26 20.63 15.2 4.6 Georgiz 35.91 23.15 12.76 21.05 13.4 4.7 Michigan 31.55 27.51 4.04 18.46 16.9 3.3 Oakland 46.21 29.96 16.25 18.06 13.8 6.7 USC 30.51 23.55 6.95 18.75 15.1 3.7 St. Johns 31.31 26.45 4.86 20.17 18.1 -1.1 Old Domin 38.51 20.01 18.51 20.96 14.1 1.4 Tennessee 32.61 26.71 5.91 18.63 15.3 0.8 Butler 33.65 22.95 10.71 15.77 16.5 2.2 Penn St 28.61 27.65 0.96 19.13 15.1 -0.7 UAB 33.55 24.01 9.54 13.31 12.9 5.2 VCU 44.01 29.81 14.21 17.58 9.8 0.5 Princeton 35.15 22.61 12.54 10.99 9.4 5.2 Memphis 33.15 26.51 6.65 10.02 7.9 3.6 More State 34.51 19.81 14.71 10.15 9.1 1.9 UCSB 33.15 24.95 8.21 8.72 6.4 5.1 Bucknell 34.11 24.15 9.96 5.15 7.1 6.2 Wofford 34.05 25.31 8.74 6.42 7.8 3.3 Ind State 29.31 24.03 5.28 8.24 5.7 2.9 Long Island 41.71 26.35 15.36 6.79 5.5 4.2 Long Bea St 33.71 28.95 4.76 8.64 7.3 0.6 North Colo 31.55 23.15 8.41 4.91 6.8 1.4 Akron 32.25 25.71 6.54 2.79 5.1 3.3 St Peters 25.45 21.71 3.74 4.39 2.8 3.7 AVG 37.04 23.02 14.03 21.46 18.5 4.9

Some potential second round upsets that stand out:

Gonzaga over St Johns

Utah St over Kansas St

Florida St over Texas A&M

Mich St over UCLA (shaky, though)

Marquette over Xavier

Possible Third Round Upsets

Washington over UNC

Gonzaga over BYU

Utah St over Wisconsin (gut feeling)

Possible 4th Round Upsets

Washington over Syracuse (very close)

Texas over Duke (gut feeling)

Gonzaga over Florida (Flor is way overseeded)

Wild Card Final Four Team

San Diego State

Championship Game

Kansas over Ohio St (zzzzz…)

### 5 Responses to “Statistical Analysis of the 2011 NCAA Tournament field”

1. Blake Says:

I’m hesitant to put Gonzaga over BYU in the 2nd round, Ty…

Fredette is quite the scorer, I don’t know if they can stop him.

2. robbieomalley Says:

St Johns also lost their best wins producer (Win score wise) in DJ Kennedy to a torn acl a few days ago. I’d be very surprised if they were to beat Gonzaga.

Another note is that PG Kyrie Irving is probably going to be playing for Duke in the tournament. His WS is really high for a PG, especially a freshman PG. If he can come close to matching the level he was playing at before then he should be a major boost to the Blue Devils.

3. Blake Says:

You think Old Dominion has a chance to upset Pittsburgh in the 2nd round? Southeast bracket is really giving me troubles.

4. john kelby Says:

john kelby…

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