Skill Curves in the NFL: Unlocking the Interactions between Passing & Rushing

The NFL has clearly turned to a pass-first league during the past decade or so, and for a good reason.  Passing is overall more efficient!  Indeed using play-by-play data from the 2014-2016 NFL seasons and the Winston-Sagarin-Cabot model for expected points, a passing play adds on average 0.25 expected points, while a rushing play adds… Read More Skill Curves in the NFL: Unlocking the Interactions between Passing & Rushing

A Shooting Dictionary for Players and Teams in Basketball Champions League

Shooting charts have been an integral part of a basketball game’s summary for quiet some time now. Fans like visual information and can easily grasp it. However, if one wants to understand the shooting patterns of teams/players and how they differ (and how potentially this can drive pre-game scouting and in-game strategy) heuristic comparison of… Read More A Shooting Dictionary for Players and Teams in Basketball Champions League

Predicting the Basketball Champions League Tournament using Data

This year FIBA launched a new European professional competition for basketball clubs, namely, Basketball Champions League (BCL). A total of 52 teams from 31 European leagues participated in the inaugural season of BCL and the actual format of the competition can be found on the league’s site. Currently the competition is at the first round… Read More Predicting the Basketball Champions League Tournament using Data

Evaluating logistic regression beyond classification accuracy: The case of NFL matchup prediction

Probabilistic predictions are everywhere and of course in sports as well.  The holly grail of sports analytics is to predict the outcome of a game after all.  A typical approach that is used to evaluate predictions is focused on the accuracy, that is, how many correct predictions did the prediction engine make.  In theory this is… Read More Evaluating logistic regression beyond classification accuracy: The case of NFL matchup prediction