Luke Stanke

Data Science – Analytics – Psychometrics – Applied Statistics

Who should be the NFL MVP

It’s the end of the National Football League regular season tomorrow. With that, comes talk about who the best player — the MVP — will be. Since 2000, the MVP award has been won by 11 times by quarterbacks and 4 times by running backs. In fact, since the award has been given out only two defensive players — Alan Page in 1971 and Lawrence Taylor in 1986 have ever won MVP. The award has been given out to a special teams player just once — to Mark Moseley in the strike-shortened 1982 season. His recognition is a bit of an oddity, and some suggest he might not have even been the best kicker that year.

It’s easy to suggest what Most Valuable means — a player that has contributed the most to his team’s success — but it’s a lot harder to quantify that. It’s what smart statisticians that work for big sports companies work on all the time and think about with more data than I have access to, but I’m going to give it a shot. Using play-by-play data from Armchair Analysis, I created a model that gives the chances of winning of a game given the context of the games — things like time to play in the game, down, distance to go, distance from goal, and the difference in score.

Using this information I could then figure out what the chances of team are to win at any given point in the game. Take this situation: Let’s pretend Aaron Rodgers has the ball on his opponents 40 yard line. It’s 2nd and 7 yards to go with 7:50 remaining in the game and the Packers are down by four. In this situation, Rodgers and the Packers have a 45.92% chance to win the game. On the next play he is forced to run, and he gains 34 yards. The new odds of winning the game for the packers are 50.02%. This mean Rodgers contributed .051 points to his team’s chances of winning. We can figure this out for every player on every play. And then we can add it all up to figure out who’s the MVP.

So who is the MVP?