This paper reviews about 50 years of activity in OR as applied to sports. After some history
and an overview, including discussions of what we mean by sport and what we mean by OR …

A football match is modelled as a four-state Markov process. A log-linear model, fed by real
data, is used to estimate transition probabilities by means of the maximum likelihood …

Publisher Summary This chapter discusses the application of operations research in sports.
Professional sports teams, events, venues, and related gambling constitute major business …

In this paper, we use k-means clustering to define distinct player types for each of the three
positions on a National Hockey League (NHL) team and then use regression to determine a …

We extend the classic Poisson model of hockey based on score differential and time
remaining in the game to include the effect of penalties, and derive the associated Markov …

This article develops a simulator for matches in the National Hockey League (NHL) with the
intent of assessing strategies for pulling the goaltender. Aspects of the approach that are …

We propose a model to estimate the rates at which NHL teams score and yield goals. In the
model, goals occur as if from a Poisson process whose rate depends on the two teams …

This paper proposes a dynamic programming (DP) approach to find the optimal substitution
strategy for a football match, which maximises the probability of winning or the expected …

To develop a novel approach for performance assessment, this paper considers the problem
of computing value functions in professional American football. We provide a theoretical …

We demonstrate the use of a model calibrated using data from every 1999–2000
Premiership match to determine the circumstances under which a player 'should'commit a …