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Sports Analytics from a to Z

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Sports Analytics from a to Z i Table of Contents About Victor Holman .................................................................................................................................... 1 About This Book ............................................................................................................................................ 2 Introduction to Analytic Methods................................................................................................................. 3 Sports Analytics Maturity Model .................................................................................................................. 4 Sports Analytics Maturity Model Phases .................................................................................................. 4 Sports Analytics Key Success Areas ........................................................................................................... 5 Allocative and Dynamic Efficiency ................................................................................................................ 7 Optimal Strategy in Basketball .................................................................................................................. 7 Backwards Selection Regression ................................................................................................................... 9 Competition between Sports Hurts TV Ratings: How to Shift League Calendars to Optimize Viewership .................................................................................................................................................................. 9 Bayesian Generalized Linear Model ............................................................................................................ 11 Shrinkage Estimation of NFL Field Goal Success Probabilities ................................................................ 11 Bayesian Hierarchical Latent Variable Models ........................................................................................... 13 Eye on the Ball: The Relationship Between Sensorimotor Abilities and On-Field Performance in Professional Baseball .............................................................................................................................. 13 Bayesian Hierarchical Model....................................................................................................................... 15 Estimating an NBA Player's Impact on His Team's Chances of Winning ................................................. 15 Bayesian Model and Simple OLS Regression .............................................................................................. 17 Moral Hazard in Long-Term Guaranteed Contracts: Theory and Evidence from the NBA ..................... 17 Bayesian Multinomial Model ...................................................................................................................... 19 Exploring the Potential of the Plus/Minus in NCAA Women's Volleyball via the Recovery of Court Presence Information ............................................................................................................................. 19 Binary Logic Model ...................................................................................................................................... 21 Matchup Models for the Probability of a Ground and a Ground Ball Hit ............................................... 21 Bipartite Graph Algorithms ......................................................................................................................... 23 Player Centrality on NBA Teams ............................................................................................................. 23 Bland Altman Plot Analysis ......................................................................................................................... 25 Bland Altman Plot Analysis in Sports Analytics ....................................................................................... 25 Bonferroni Adjusted Comparisons .............................................................................................................. 27 A Closer Look at the Prevalence of Time Rule Violations and the Inter-Point Time in Men's Gland Slam Tennis ...................................................................................................................................................... 27 Bookmaker Consensus Model .................................................................................................................... 29 ii Searching for the GOAT of Tennis Win Prediction .................................................................................. 29 Bootstrap Simulation .................................................................................................................................. 31 Improving Fairness in Match Play Golf through Enhanced Handicap Allocation ................................... 31 Boruta Algorithm ........................................................................................................................................ 33 An Investigation of Three-Point Shooting through an Analysis of NBA Player Tracking Data ................ 33 Brownian Motion Process ........................................................................................................................... 35 The Implied Volatility of a Sports Game ................................................................................................. 35 Chapman- Kolmogorov Equations .............................................................................................................. 37 Evaluating NBA End-of-Game Decision-Making ..................................................................................... 37 Clustering .................................................................................................................................................... 39 Big 2's and Big 3's: Analyzing How a Team's Best Players Complement Each Other .............................. 39 Coaching Assistance Models ....................................................................................................................... 41 Coaching Assistance Models as a Method of Sports Analytics ............................................................... 41 Recognizing and Analyzing Ball Screen Defense in the NBA ................................................................... 42 Competitiveness Metrics ............................................................................................................................ 44 The Competitiveness of Games in Professional Sports Leagues ............................................................ 44 Computer Vision Techniques ...................................................................................................................... 45 Using Computer Vision and Machine Learning to Automatically Classify NFL Game Film and Develop a Player Tracking System ........................................................................................................................... 45 Conditional Probability ............................................................................................................................... 47 Applying Conditional Probability to Sports Analytics ............................................................................. 47 Conditional Random Field ........................................................................................................................... 48 "Quality vs. Quantity": Improved Shot Prediction in Soccer using Strategic Features from Spatiotemporal Data ............................................................................................................................... 48 Conservation of Runs Framework ............................................................................................................... 50 openWAR: An Open Source System for Evaluating Overall Player Performance in Major League Baseball ................................................................................................................................................... 50 Convex Hull ................................................................................................................................................. 52 Predicting Golf Scores at the Shot Level ................................................................................................. 52 Convolutional Neural Networks .................................................................................................................. 54 Mythbusting Set-Pieces in Soccer ........................................................................................................... 54 Cross-Validated Root-Mean-Squared Error ................................................................................................ 56 Improved NBA Adjusted +/- Using Regularization and Out-of-Sample Testing ...................................... 56 Data Science Methods ................................................................................................................................ 58 iii Data Science Methods in Sports Analytics .............................................................................................. 58 Data Tables.................................................................................................................................................. 60 The Effect of
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