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PROBABILITY OF WINNING
THE NCAA TOURNAMENT
FUNCTION OF RANK OF
ADJUSTED NET EFFICIENCY (ANE)
BASED ON RESULTS SINCE 2002

For several years, it has been clear that a team's ability to win the NCAA basketball tournament is a function of that team's Adjusted Net Efficiency (ANE). Data is available for all seasons since 2002, and these 14 champions have had the following final ANE rank distribution.

ANE Number
Rank Champions

The number 1 ranked team, using ANE as the ranking criteria, has won 7 of these 14 championships, and the number 2 ranked team has won another 3 championships. The remaining 4 champions had ranks of 4, 5, 8, and 9. Clearly, the sample size is too small to take this data on its face. The probability that a #3 team will win is clearly not 0%, and similarly for 6, 7, 10, and even the remainder of the NCAA field. Therefore, some manipulation of this limited sample is necessary to distribute the probabilities for the entire 68 team Tournament Field such that it continues to reflect the basic top heavy relationship and the sum of all 68 probabilities is 100%.

This analysis results in the following distribution:

The data and analysis of the data are clear. I want my team to be the #1 ANE in the nation, and if not #1, then #2. After that, I want to be in the top 5. Given the distribution, anything outside the top 10 has no realistic chance to win the tournament.

The above data is presented in the next series of tables providing more detail in two respects.  First, the tables examine more categories of statistics, and second, the data is sorted based on the following factors, in the order shown below:

1. All Games, Including Exhibitions
2. All Games-D1 [No Exhibitions]
3. Home
4. Away
5. Neutral Court
6. Non-Conference
7. SEC
8. Pomeroy Top 50
9. Pomeroy Over 50
10. Post Season Play
11. Games Since Louisville Game, 2003-2014
12. SEC Tournament Gateway
13. NCAA Tournament

You may link to any of these sorted data pages using the links above, or you can browse them in sequence using the "Continue" buttons at the bottom of each page.

To Data Tables for Games Against Team Ranked POMEROY Top 50

IMPORTANT NOTE: In 2009-10, the Kentucky basketball team's rebounding became so dominant in the first 10 games that the differences created by a varied definition of a possession became substantial, and based on a 10 game comparison of predicted and actual results using the original definition and the Pomeroy definition, I have decided to start using the Pomeroy definition for a possession beginning with the 2009-10 season, and thereafter. However, I have no means to convert the data for all prior seasons to this new definition at this time. Therefore, any attempts to compare pace and efficiency derived values for 2009-10 and later with any prior season's posted values will fail. The differences are:

1. Pace values will be lower, by the number of offensive rebounds.

2. Efficiencies will be higher due to the lower number of total possessions

3. Turnover rates will be higher due to the lower number of possessions.

CHECK OUT THESE OTHER ANALYTICAL WRITINGS

What Is Basketball?

What is a Possession?

Change in Position on Definition of Possessions

What Is Net Game Efficiency?

Why Do "Upsets" Occur?

Do Objective Performance Measures Like NGE
Account For Intangible?

 

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SugarHill Communications of Kentucky
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