Related papers: Hockey Player Performance via Regularized Logistic…
We present a regularized logistic regression model for evaluating player contributions in hockey. The traditional metric for this purpose is the plus-minus statistic, which allocates a single unit of credit (for or against) to each player…
The goal of this paper is to develop an adjusted plus-minus statistic for NHL players that is independent of both teammates and opponents. We use data from the shift reports on NHL.com in a weighted least squares regression to estimate an…
Regression-based adjusted plus-minus statistics were developed in basketball and have recently come to hockey. The purpose of these statistics is to provide an estimate of each player's contribution to his team, independent of the strength…
In this paper, we develop a logistic regression model to estimate the probability that a particular shot in an NHL game will result in a goal, and use the results to evaluate the performance of NHL skaters, goalies, and teams. We weight…
Evaluating the overall ability of players in the National Hockey League (NHL) is a difficult task. Existing methods such as the famous "plus/minus" statistic have many shortcomings. Standard linear regression methods work well when player…
It is often said that a sign of a great player is that he makes the players around him better. The player may or may not score much himself, but his teammates perform better when he plays. One way a hockey player can improve his or her…
Traditional NBA player evaluation metrics are based on scoring differential or some pace-adjusted linear combination of box score statistics like points, rebounds, assists, etc. These measures treat performances with the outcome of the game…
This project aims to assess the performance of various regression models in predicting the performance of hockey players. The measure of performance is chosen to be points scored (sum of goals scored and assists made) by individual players…
We use a simple machine learning model, logistically-weighted regularized linear least squares regression, in order to predict baseball, basketball, football, and hockey games. We do so using only the thirty-year record of which visiting…
Recording of events in National Hockey League rinks is done through the Real Time Scoring System. This system records events such as hits, shots, faceoffs, etc., as part of the play-by-play files that are made publicly available. Several…
A popular quantitative approach to evaluating player performance in sports involves comparing an observed outcome to the expected outcome ignoring player involvement, which is estimated using statistical or machine learning methods. In…
Tracking and identifying players is a fundamental step in computer vision-based ice hockey analytics. The data generated by tracking is used in many other downstream tasks, such as game event detection and game strategy analysis. Player…
This study outlines a light gradient boosted model aimed at predicting shot outcomes in the NHL. The model uses the NHL's spatiotemporal data to account for both the skill of shooters and goaltenders. This approach involves isolating and…
Passing during power plays in hockey is a crucial component to move one's team closer to scoring a goal. With the use of women's ice hockey event and tracking data from the elimination round games during the 2022 Winter Olympics, we…
Pace of play is an important characteristic in hockey as well as other team sports. We provide the first comprehensive study of pace within the sport of hockey, focusing on how teams and players impact pace in different regions of the ice,…
A typical approach to quantify the contribution of each player in basketball uses the plus-minus method. The ratings obtained by such a method are estimated using simple regression models and their regularized variants, with response…
The hot-hand theory posits that an athlete who has performed well in the recent past performs better in the present. We use multilevel logistic regression to test this theory for National Hockey League playoff goaltenders, controlling for a…
This paper takes a different approach to evaluating face-offs in ice hockey. Instead of looking at win percentages, the de facto measure of successful face-off takers for decades, focuses on the game events following the face-off and how…
This paper explores the concept of "momentum" in sports competitions through the use of the TOPSIS model and 0-1 logistic regression model. First, the TOPSIS model is employed to evaluate the performance of two tennis players, with…
In the sports of soccer, hockey and basketball the most commonly used statistics for player performance assessment are divided into two categories: offensive statistics and defensive statistics. However, qualitative assessments of…