AI to Advise NFL on What to Pay Players


AI to Advise NFL on What to Pay Players
Company owned by broadcaster, ex-player Cris Collinsworth has found that some teams are overpaying star running backs

Cris Collinsworth, a former Cincinnati Bengals player who is now an analyst for NBC’s ‘Sunday Night Football,’ took majority ownership of the analytics company in 2014. PHOTO: JONATHAN ALCORN/REUTERS

By John Murawski July 22, 2019 5:30 am ET | WSJ PRO

An analytics company owned by former pro football player and current broadcaster Cris Collinsworth is testing an artificial-intelligence system to generate recommendations on player salaries for all 32 National Football League teams.
Early results show that some teams are overpaying star running backs, among other players, by millions of dollars.
Cincinnati-based PFFA Acquisition LLC, which does business as Pro Football Focus, sells data on every player’s performance in every game, presented in a searchable format with accompanying videos, to every NFL team and to more than 60 college programs. Teams can use the data service, also called Pro Football Focus, to analyze plays, prepare for games and recruit players. Agents, scouts and sports media also use the system.
“We’re building tools where you can plug in players, you can plug in salaries, you can plug in our grades, and decide whether or not a player is worth it,” said Mr. Collinsworth, PFF’s chief executive, who took majority ownership of the company in 2014. Mr. Collinsworth, a wide receiver for the Cincinnati Bengals in the 1980s, is an analyst for NBC’s “Sunday Night Football.”
Mr. Collinsworth said pro football is becoming “a war of the mathematicians,” much like baseball before it. Teams are looking for every possible advantage and hiring data scientists.
The new salary component PFF is developing, expected to be released within a year, builds on the company’s data repository. Its machine-learning algorithms will give teams a player’s market value based on an analysis of historical data and projected performance. Metrics include standard statistics such as the number of times a receiver drops a pass considered catchable and the difficulty level of completed passes by a quarterback.
Eric Eager, a senior data scientist at PFF, said the company’s analysis indicates that running backs tend to be overrated and overpaid because they are a focal point on the field. But running backs are relatively easy to replace because there are many of them and their performance is largely dependent on other players.
A spokesman for the NFL Players Association, which represents players in labor talks, said the current salary-negotiation system is effective.
The system is being developed in two phases. The first part of the system, which has been provided to all 32 teams for feedback, uses regression models to weight a player’s historical performance in each game and to project how that player would play against new opponents under various hypothetical conditions. Such a condition could be a player’s projected performance in a third down and 15-yards-to-go situation against an opponent he has never faced, in the last 2 minutes of the game. This analysis allows PFF to predict how valuable a player is.
The second phase, which the company is testing internally, overlays a financial value to that metric for that particular position. The salary recommendation requires analyzing the difficulty of filling a particular position on the team. It also requires factoring in the diminishing returns on paying a premium for some positions, for example, an above-average offensive lineman, when that money would be better spent on another player in a key position.


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