While in the NBA you will rarely see a game’s stats sheet mention metrics like PER and PIR, this is quiet the norm for leagues around the world. In fact, these metrics are used to award game MVPs in these leagues – and as you can imagine many times the results are strange to say… Read More Single game player contribution metrics in basketball
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
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
With the NBA playoffs right around the corner we crunched the numbers in order to give you the 2016-17 champion today! Of course we are joking since numbers do not play basketball but we simulated the 2016-17 playoffs and we obtained the championship probabilities for each of the 16 teams in the playoffs. We used the Basketball… Read More NBA Playoffs: The Champion as seen by the data
In the first part of our dealing with in-game probabilities we made some general comments about issues (or not) with these models. One of the problems with existing models is that they are not open, i.e., very little is known about their mechanics. Here I will present the details and the evaluation of a simple, yet… Read More In-game win probabilities Part 2: iWinrNFL
Now that the dust from Super Bowl LI has settled (and even Brady found his jersey) let’s talk a bit about a topic that was discussed a lot in the aftermath of the game – at least within the sports analytics community. That is no other but the in-game win probability models that several media… Read More In-game win probability models Part 1: Are they failing?
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
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