Bayesian player evaluation

Many times, in sports we need to evaluate players with limited information.  Should we sign a QB for whom we have only observed 30 pass attempts? What is our best estimate for the probability distribution for his yards/attempt? What about a kicker that has only taken 5 field goals of 50+ yards? How can we decide […]

Faceoffs: Skill or Luck?

With the NHL season right around the corner, this marks my first ever post on hockey.  Clearly hockey is not my sport, but this shows how math and analytics can cast a net over all sports. One of the constant questions in sports is how much of a team’s or player’s success is due to […]

Eurobasket 2017: Team Ratings

With the Eurobasket 2017 tournament under way, I provide regression-based ratings for the teams. Every team T will be assigned a rating r(T) (to be found) that represents how many points better (or worse) the team is compared to an average team, which will have a rating of 0.  Using these ratings we can project […]

Rating Offensive Lines in NFL

Everyone (almost) agrees that the offensive line is crucial for the success of a team. However, evaluating the offensive line in NFL is still a mystery and underdeveloped. The offensive line has an important role in both the passing game (by protecting the QB from sacks and hits), as well as in the running game (by […]