The Oxford Anthology of Statistics in Sports Volume 1: 2000-2004

A collection of a wide range of research papers on applications of statistics to various sports from journals published by the American Statistical Association and the Royal Statistical Society from 2000 through 2004. The anthology is divided into eight sections (Baseball, Cricket, Football, Golf, Olympics/Track & Field, Soccer, Other Sports, and Miscellaneous), each comprising several research articles on applications of statistics to the corresponding sport written by leading researchers, and each featuring an original introduction written by a leading researcher on the application of statistics to the corresponding sport. The anthology includes research papers at all levels of statistical sophistication that utilize a wide variety of statistical methods, and should therefore be of great interest to the statistically inclined sports fan as well as instructors and students of statistics who are looking for examples of interesting applications of statistics to problems in sports.

1 - Were the 1996-2000 Yankees the Best Baseball Team Ever?
2 - Comparing the Performance of Baseball Players
3 - Career Records for All Modern Position Players Eligible for the Major League Baseball Hall of Fame
4 - Streakiness in Team Performance
5 - Do Baseball Players Regress toward the Mean?
6 - Gold Medals, Protests, and Trading Ratings: The 2002 Winter Olympics Figure Skating
7 - One Modern Man or 15 Tarzans?
8 - Evaluation of the Current Decision Rule in Figure Skating and Possible Improvements
9 - An Analysis of Decathlon Data
10 - College Football Rankings
11 - Tiered Polychotomous Regression: Ranking NFL Quarterbacks
12 - The Cold-Foot Effect
13 - A Penalized Maximum Likelihood Approach for the Ranking of College Football Teams Independent of Victory Margins
14 - The Return of a Missed Field Goal in Canadian Football
15 - Statistics and the College Football Championship
16 - A Fair Result in Foul Weather
17 - Rating Teams and Analysing Outcomes in One-Day and Test Cricket
18 - Rain Rules for Limited Overs Cricket and Probabilities of Victory
19 - Batting Strategy in Limited Overs Cricket
20 - Is the USGA Golf Handicap System Equitable?
21 - A Game of Which I am Not Familiar
22 - Equitable Handicapping in Golf
23 - Exploratory Analysis of European Professional Golf Association Statistics
24 - An Improved Award System for Soccer
25 - Balance in Competition in Dutch Soccer
26 - Dynamic Modelling and Prediction of English Football League Matches for Betting
27 - An Evaluation of Characteristics of Teams in Association Football by Using a Markov Process Model
28 - Making up the Results: The Work of the Football Pools Panel
29 - Coach Markov Pulls Goalie Poisson
30 - The National Hockey League Entry Draft, 1969-1995
31 - Bowlers' Hot Hands
32 - Did Lennox Lewis beat Evander Holyfield?
33 - Analysis of Sports Data By Using Bivariate Poisson Models
34 - Dynamic Rating of Sports Teams
35 - Inferences about Testosterone Abuse among Athletes
36 - Investigating the Economic and Demographic Determinants of Sporting Participation in England
37 - Using Model/Data Simulations to Detect Streakiness

James J. Cochran earned a PhD in Statistics from the University of Cincinnati in 1997. He was a founding co-chair of Statistics Without Borders and a member of the founding committee for INFORMS Pro Bono Analytics initiative. He is a Fellow of the ASA, a recipient of the ASA's Founders Award, and a recipient of the Karl E. Peace Award for outstanding statistical contributions for the betterment of society. Jay Bennett studied at Colgate University and the University of Michigan, and later obtained a Ph.D. from Temple University. He has worked and performed research in the areas of computer science, operations research, and telecommunications. He was the editor of Statistics in Sport and the co-author (with Jim Albert) of Curve Ball. Jim Albert has authored Teaching Statistics Using Baseball, and co-authored Curve Ball (with Jay Bennett) and Analyzing Baseball with R (with Max Marchi). He is a previous editor of the Quantitative Analysis of Sports. His research interests include Bayesian inference, statistics education, and statistical thinking in sports.