Sunday, January 28, 2007

NFL Referees: Some better for favorites than others but no home consistency

There is a consistent correlation for NFL referees and how well favorites do in their games, but no consistent correlation related to the home teams.

Here's a short explanation of my analysis (I'll put more information in the comments to this post so check there for details):

Check whether there is a correlation between how well home teams or favorite teams did for a referee crew in the first and second halves of the NFL season. If crews have an influence, then you'd see some consistency between the first-half results and the second-half. But if it's random, then there'd by no correlation.

In doing this analysis, I filtered out the strength of schedule by using a system to estimate the expected number of wins for the home and favorite teams in each half of the season.

The result?
A positive correlation of 0.1729 for referees and how well favorites did in the first and second halves of the season! So it seems some referees are better for favorites and some not so good. Why? Perhaps because a group of referees call the game consistently so the favorites do well, but others call the game a different way so the traditionally strong teams might not do as well. For example, if 80% of the referees call holding a certain way, then the favorites will do consistently well with them but not in games called by the other 20% of the referees.

Which referees were good for favorites?
Walt Anderson (+20%, 1H +10% and 2H +32%)
Terry McAulay (+17%, 1H +7% and 2H +27%)
Scott Green (+17%, 1H +32% and 2H +2%)

Which referees were bad for favorites?
Walt Coleman (-26%, 1H -16%, 2H -37%)
Larry Nemmers (-13%, 1H +10%, 2H -37%)
Peter Morelli (-12%, 1H -2%, 2H -23%)

How does Ed Hochuli do? Pretty much in the middle of the pack: +1%, 1H -5%, 2H +6%.

But no such correlation regarding how well the home teams do. The correlation was negative, actually at -0.1551.

Post your comments, questions, and criticisms of this analysis!


Blogger Rex said...

Just additional information on how I did the analysis: compile the winning rate for home and favorites in the first and second halves of the season for each referee.

Then compile the expected win rate of the home and favorites for each half of the season for each referee. I used the net season-long DVOA from for each game and created a model to predict how often a team won a game when the home team had a certain amount of DVOA advantage (or disadvantage) over the course of the season's games. It was a custom-made model but done to try to estimate the expected winning percentage.

Then chart out the rates for both halves of the season for all 17 referees and check for a correlation between the first and second halves of the season. Easy, right?

7:48 PM  
Blogger Rex said...

Here is some of the raw data: ref's name, season average for favorites, first-half average, second-half average (sorted by season-long average)

Anderson 21% 10% 32%
McAulay 17% 7% 27%
Green 17% 32% 2%
Triplette 16% 18% 14%
Carey 6% -4% 16%
Corrente 5% 15% -6%
Vinovich 3% -3% 8%
Boger 1% 2% 0%
Hochuli 1% -5% 6%
Winter 1% -16% 17%
Steratore 0% -3% 2%
Leavy -2% -9% 4%
Austin -5% -4% -5%
Carollo -12% -16% -8%
Morelli -12% -2% -23%
Nemmers -13% 10% -37%
Coleman -26% -16% -37%

7:51 PM  

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