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 […]
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 […]
We are 4 days before the new NFL season and everyone is getting their football mode on again (if they haven’t yet). Making any judgements on how the season will turn out using the pre-season game showings of the teams is rather useless. Equally bad is trying to transfer the ratings of last season to […]
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 […]
Ranking and rating teams has been one of the major tasks in the sports analytics community. One of the most elegant approaches I have seen is the one presented by W. Winston in his book “Mathletics“. In this post I will adopt the general approach presented and add a few elements more. Our case study […]
Clock management is certainly a crucial task that the personnel of an NFL team has to work on and be prepared for. However, it should be obvious even to the casual fan that the teams are all using pretty much the same guidelines for clock management. In this article, I am not going to judge these guidelines […]
What attributes explain a team’s win-loss performance? Of course this is the holy grail of sports (hoops) analytics, since knowing the answer to this question will allow a team to create a plan that will exploit this knowledge. The famous 4 factors from Dean Oliver are one such example, where a small number of statistics […]
