Contact / FAQ

You can contact Brian by email at brian@mail.advancednflstats.com. Questions about the content of the posts are best as comments. All comments get read, and those with questions often get a quick response.

I'm always amazed at the overwhelming response this site has received. I appreciate all the feedback. Please keep it coming--the good and the "constructive." While I don't want to discourage anyone from writing me, I'd like to encourage everyone to use the site comments feature for any items you think might be of interest to other readers. You may get a answer to your question quicker from another reader than from me. Also, my spam filter can trap some comments and emails, so I apologize if you haven't received a response.


FAQ

Where did you get your data?

Most of my team data comes from open online sources such as espn.com, nfl.com, myway.com, and yahoo.com. It's easy for anyone to grab whatever they're interested in from those sites.

My play-by-play data comes from a source that's not publicly available, and at this time I regret that I cannot share it. However, I have been able to create a database of nearly all NFL plays since 2002 free for anyone to use for research.


Why don't you do predictions Against The Spread (ATS)?

While I don't object to gambling, it doesn't really interest me. I realize a lot of football fans are interested in it, and I'm happy if anything here helps inform fans of all kinds. I do however use Vegas odds and spreads as consensus yardsticks for my own models, and sometimes it's fun to see if some math can beat "the system." I just lack that gene for risk, and cheering for my favorite team is excitement enough for me.


I heard you're not a math professor or professional statistician, but actually a former Navy fighter pilot. Is that true?

Yes. I flew F/A-18 Hornets off carriers. The Navy sent me to graduate school where I picked up a knack for analytics. Only now do I realize that much of the combat tactics we used as pilots were derived using the same analytical techniques I use for my football research.


Why aren't you working for a team?

I'm very reluctant to relocate my family. I often do freelance consulting for NFL teams and media outlets.


What's it like flying an F/A-18?

The best way I ever heard someone describe flying a fighter plane was this: It's like simultaneously racing in the Indianapolis 500 while playing a video game and holding two telephone conversations...all while people are shooting at you. Then the hard part begins--landing on a pitching carrier deck. In reality flying a plane is a true team sport. Thousands of brave sailors and everyone else who supports them. I was very fortunate to be part of such a great organization as the United States Navy.

About the Founder

Brian Burke
Reston, Virginia

Brian is a football fan and closet math enthusiast. He has a BS in aerospace engineering and an MS in management and leadership. After spending 15 years in the Navy, most of them as an F/A-18 carrier pilot, Brian has taken up the less dangerous hobby of advanced NFL statistics.

Originally from Baltimore, Brian spent his youth either on the sidelines of Maryland Terrapin football games or in 50-yard line seats at Colts games, both thanks to his dad. His football career topped out playing tight end for the Towson High Generals. His only college football experience was playing in the Naval Academy's annual "2.7" game, an intramural game that featured the "geeks" vs "rocks" divided by the Academy's average GPA. You can guess which team Brian played for.

After graduating from Annapolis in the Class of '93, Brian attended flight school and went on to fly the F/A-18C Hornet until leaving the Navy. He attended the Naval Postgraduate School and returned to Annapolis as an instructor. Brian flew 21 combat missions and was awarded the Air Medal, the Navy Commendation Medal, and numerous other personal and unit commendations.

He now resides with his family in northern Virginia.

Is There 'Momentum' During a Season?

The 2006 season continued and I made incremental improvements to the model. Beginning at week 8, I emphasized the efficiency stats from each team's most recent 4 weeks. I hoped this would help account for a team's improvement over the course of the season and for injuries to key players. I set this to be a changable variable which I called an "emphasis factor" that I could set to 0 to see how much the predicted probabilities changed from the baseline.

What I found was that the probabilities changed, but not by much, and rarely enough to swing one team from underdog to favorite. It made intuitive sense to me, and still does, so I kept the "emphasis factor" in the model.

But this is actually a question ripe for research. Teams appear streaky. Commentators, analysts, and fans accept that teams can be on a roll or in a rut. But over the course of a season it would be reasonable that wins and losses can naturally come in bunches on occasion.

Just as if you flipped a coin 16 times, you wouldn't expect the outcome to perfectly alternate heads and tails. If you did this several times, you would find that some of the 16-coin-flip "seasons" have several instances of consecutive heads "streaks." If we were betting on heads, our human intuition would tell us that the coin is "hot" or on a hot streak. In some rare, but totally natural, cases we might even expect 8 straight heads followed by 8 straight tails, or vice-versa.

The same principal holds for sports. The 16-game NFL season is particularly short and is susceptable to natural "streaks" without any actual change in performance. In theory, an average team destined to go 8-8 could start the season 8-0 followed by an 0-8 "collapse." Admittedly this would be extremely rare. In this case the luck factor (calculated below) for this team would be +4 during the 1st half of the season, and -4 for the last half of the season.

This phenomenon may explain why the emphasis on recent performance I applied in the model didn't change the probabilities very much. Teams appear streaky in terms of wins and losses, but win/loss records are naturally more erratic than the efficiency stats, so we should expect teams to appear that they're on "a roll" or in "a rut" when winning or losing streaks are really just part of a natural distribution of outcomes.

Below is a table of Week 11 comparing the predicted probabilities using both the standard stats and the stats with the recent 4-weeks performance weighted.