1st Edition

Handbook of Statistical Methods and Analyses in Sports

    520 Pages 24 Color & 36 B/W Illustrations
    by Chapman & Hall

    528 Pages 24 Color & 36 B/W Illustrations
    by Chapman & Hall

    520 Pages 24 Color & 36 B/W Illustrations
    by Chapman & Hall

    This handbook will provide both overviews of statistical methods in sports and in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook will be organized by major sport (baseball, football, hockey, basketball, and soccer) followed by a section on other sports and general statistical design and analysis issues that are common to all sports. This handbook has the potential to become the standard reference for obtaining the necessary background to conduct serious statistical analyses for sports applications and to appreciate scholarly work in this expanding area.

    Baseball

    Evaluation of Batters and Base Runners

    Ben Baumer, Pamela Badian-Pessot

    Using Publicly Available Baseball Data to Measure and Evaluate Pitching Performance

    Carson Sievert, Brian Mills

    Defensive Evaluation

    Mitchell Lichtman

    Situational Statistics, Clutch Hitting, and Streakiness

    Jim Albert

    American Football

    Estimating Team Strength in the NFL

    Mark Glickman, Hal Stern

    Forecasting the Performance of College Prospects Selected in the National Football League Draft

    Julian Wolfson, Vittorio Addona

    Evaluation of Quarterbacks and Kickers

    . Drew Pasteur, John A. David

    Situational Success: Evaluating Decision-Making in Football

    Keith Goldner

    Basketball

    Probability Models for Streak Shooting

    James Lackritz

    Possession-based Player Performance Analysis in Basketball

    Jeremias Engelmann

    Optimal Strategy in Basketball

    Brian Skinner, Matthew Goldman

    Studying Basketball through the Lens of Player Tracking Data

    Luke Bornn, Daniel Cervone, Alexander Franks, Andrew Miller

    Hockey

    Poisson/Exponential Models for Scoring in Ice Hockey

    Andrew Thomas

    Hockey Performance via Regularized Logistic Regression

    Robert Gramacy, Matt Taddy, Sen Tian

    Statistical Evaluation of Ice Hockey Goaltending

    Michael Schuckers

    Educated Guesswork - Drafting in the National Hockey League

    Peter Tingling

    Soccer

    Models for outcomes of soccer matches

    Phil Scarf, Jose Rangel Sellitti Jr

    Rating of team abilities in soccer

    Ruud H. Koning

    Player ratings in soccer

    Ian G. McHale, Samuel D. Relton

    Effectiveness of in-season coach dismissal

    Lucas M. Besters, Jan C. van Ours, Martin A. van Tuijl

    Referee bias in football

    Babatunde Buraimo, Dirk Semmelroth, Rob Simmons

    Other sports

    Golf Analytics: Developments in Performance Measurement and Handicapping

    William Hurley, Mark Broadie

    Research Directions in Cricket

    Tim Swartz

    Performance development at the Olympic Games

    Elmer Sterken

    Biography

    Jim Albert is Professor of Mathematics and Statistics at Bowling Green State University; Mark E. Glickman is Senior Lecturer on Statistics at Harvard University; Ruud H. Koning is Professor of Sports Economics at the University of Groningen; and Tim Swartz is Professor of Statistics and Actuarial Science at Simon Fraser University.

    "The Handbook of Statistical Methods and Analysis in Sports is a phenomenal reference text capturing some of the best work of more than 40 statisticians active in the intersection of statistical methodology and sports data. It consists of 24 largely independent chapters each written by different authors, and outlines advances in statistical methodology applied to baseball, American football, basketball, ice hockey, football (soccer), golf, and cricket. The brilliant design of the text’s structure provides readers with a broad survey of the statistics-in-sports research landscape; it could reasonably be implemented in statistics curricula in a variety of formats and at different levels.
    ~Joe Nolan, Journal of the American Statistical Association