Comments on Advanced NFL Stats: What Makes Teams Win? 3

Brian, I have been playing with the dataset you p...

2009-10-31T02:41:39.711-04:00

Brian, I have been playing with the dataset you provided and can match your results on all but Off Pen Rate. The best I can get for it is a correlation of -.27 which leads to an R^2 of .725 ... can you shed some light on what stats you used to figure the penalty rate? I've tried about all the combinations (ie off + def, number and yds, etc) and no luck.

KenyonLV

Brain, Anecdotally, mean reversion seems to play ...

2009-09-22T19:45:23.392-04:00

Brain,

Anecdotally, mean reversion seems to play a role in sports, i.e, teams that lose big seem to have a tendency to come back in a big way the following game and vice versa. Have you seen this effect in the data?

Hi Brian; I was rereading one of your old (and gre...

2009-09-19T14:07:50.979-04:00

Hi Brian;
I was rereading one of your old (and great! posts Some questions about your model.

Are all! 9 variables in your prediction model
'repeatable ( i.e. attributed to skill)
If so could you post your findings i.e. first half to second half correlations ..this way we could see how much luck is invlove in each variable
Thanks I seem to recall in later

First you'd have to figure out a way to define and...

2009-02-21T09:31:59.704-05:00

First you'd have to figure out a way to define and measure momentum. I'm not convinced there's any such thing.

One thing I might do is use win probability to evaluate a team's WP before a big penalty and after the penalty. You could select high profile game-turning penalties (like in the SEA-PIT SB) as case studies.

THis is really great stuff. I am working on an ad...

2009-02-21T00:09:11.238-05:00

THis is really great stuff. I am working on an advanced stats project for school. Because I am a Seattle Seahawks fan, and yes I still roll in my sleep over the SB loss to Pittsburgh, I am trying to find a correlation between penalties and impact of momentum in a game. Not sure if a statistical model is the best tool to predict this... Any advice?

Run points against wins, and all the different sta...

2009-02-20T03:27:58.433-05:00

Run points against wins, and all the different states against points.

Fixed. Thanks, Fred!

2008-12-05T22:26:19.836-05:00

Fixed. Thanks, Fred!

Brian,As always, great article. I've recently come...

2008-12-05T18:07:07.695-05:00

Brian,

As always, great article. I've recently come across your blog and am going through it all chronologically.

Just a few clean-up points at some of the numbers at the end of the article.

1) I believe the expected number of wins in the last line of the second-to-last paragraph is 9.14 (not 9.94).

2) In the last sentence, I believe the formula you want to

Hi..just found your site and I really enjoy it. Sl...

2008-11-14T00:02:45.978-05:00

Hi..just found your site and I really enjoy it. Slowly reading all articles to get up to speed. I also try to predict NFL games and I use a regression.

I start with the assumption that game box score stats are the result of field position, score and time left in the game. I assume the box score stats are a result of the score, not a cause.

One minor nit pick in "what makes

Apparently, it is too complicated for some people....

2008-09-20T11:01:57.268-04:00

Apparently, it is too complicated for some people.

In case anyone is curious about time of possession, it does not correlate with winning. TOP is an 'intervening variable' between running and passing performance, and winning. So TOP is an intermediate result of success in other aspects of the game, not an ability in itself.

The game is far too complicated to take this analy...

2008-09-20T10:27:14.518-04:00

The game is far too complicated to take this analysis seriously. Factors such as Time of Possession, first downs/game and Average Time of Possession per offensive drive have not been taken into consideration in this quasi-mathematical analysis.

Max-Thanks. Didn't Homer Simpson go by that name i...

2007-12-10T22:37:48.740-05:00

Max-Thanks. Didn't Homer Simpson go by that name in an episode? Classic.

The adjusted R-squared for the model cited in this post is 0.791.

I think one reason the adjusted value is so high is that the model isn't a "kitchen-sink" model. A lot of people are tempted to throw in first downs, touchdowns, field goals, etc. which are really just intermediate results between yards

First off, this is an outstanding blog that I enjo...

2007-12-10T22:08:58.692-05:00

First off, this is an outstanding blog that I enjoy and read regularly.

Second, what is the adjusted R-squared of your season win model? The R-squared you reported was 0.802, but I wonder what the effect of keeping all those regressors (especially defensive run efficiency)has on the fit.