
Curve Ball
Baseball, Statistics, and the Role of Chance in the Game
By: Jim Albert, Jay Bennett
Hardcover | 8 June 2001
At a Glance
372 Pages
24.13 x 16.51 x 3.18
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Hardcover
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Industry Reviews
From the reviews:
"...a most interesting and useful introduction to the subject. It should make enjoyable reading for physicists who are also baseball fans, and it ought to be required reading for baseball managers, executives, and commentators." PHYSICS TODAY
"...a smart and energetic collection of essays on baseball statistics. Curve Ball doesn't play misty-eyed homage to baseball's traditions and conventional wisdoms....This is great stuff....Curve Ball makes clear how pleasurable [stats] can be, and arguably how important, to view the great American game with real precision." -- The Wall Street Journal
"Rating: 4.5 out of 5. Must own!" -- Baseballnotebook.com
"In [Curve Ball] Albert & Bennett explain the game in ways the conventional press - even titans such as Bill James - cannot." -- Baseball America
"[The book] illustrates how statistical reasoning can be useful in teasing out the role of chance from performance in baseball to better assess ability....Curve Ball represents another advance in the genre of baseball and statistics books." -- Journal of the American Statistical Association
"This is a very good, fun and highly interesting book, applying some straightforward, and some more difficult, statistical estimation and modeling concepts to baseball. ... I am a statistician, and mostly Bayesian at that, and this definitely enhanced my interest and enjoyment of the book. ... Initially this book starts out as a sneaky introduction to statistics and Bayesian concepts, however, it turns into a delight for sports fans and statisticians alike. Highly recommended ... ." (Richard Gerlach, Gazette, Vol. 31 (5), 2004)
"This book treats a wide variety of topics, including: comparing measures of batting ability; the impact of situation on performance; streaks; measuring a player's clutch performance; and did the best team win the World Series. This book has the appealing quality that you can start reading at almost any chapter and enjoy and understand the journey. And for those of us who are not statisticians by training, we can also learn some statistics." (Zentralblatt fur Didaktik der Mathematik, September, 2003)
"Curve Ball ... is a necessary addition to any library. ... Written for all followers of baseball, this book caters to those who find joy in reading (and if you are like me, memorizing) the statistics on the backs of baseball cards or who played baseball simulation games ... . For readers possessing no knowledge of statistics, this book is a great way of learning how to view and interpret data from a statistician's standpoint. Readers with statistics backgrounds will enjoy the book ... ." (Jonathan L. Templin, Chance, Vol. 15 (4), 2002)
| Introduction | p. xi |
| Simple Models from Tabletop Baseball Games | p. 1 |
| All-Star Baseball (ASB) | p. 1 |
| Model Assumptions of All-Star Baseball | p. 8 |
| The APBA Model: Introducing the Pitcher | p. 9 |
| Strat-O-Matic Baseball: The Independent Model | p. 15 |
| Sports Illustrated Baseball: The Interactive Model | p. 20 |
| Which Model Is Best? | p. 24 |
| Exploring Baseball Data | p. 27 |
| Exploring Hitting Data | p. 27 |
| A Batch of On-Base Percentages | p. 28 |
| Simple Graphs | p. 29 |
| Typical Values--the Mean and the Median | p. 31 |
| Measures of Spread--Quartiles and the Standard Deviation | p. 32 |
| Interesting Values | p. 34 |
| Comparing Groups | p. 34 |
| A Five-Number Summary | p. 35 |
| A Boxplot | p. 35 |
| Boxplots to Compare Groups | p. 35 |
| OBPs of Offensive and Defensive Players | p. 37 |
| Relationships Between Batting Measures | p. 38 |
| Relating OBP and SLG | p. 39 |
| Relating OBP and Isolated Power | p. 39 |
| What about Pitching Data? | p. 41 |
| Strikeouts and Walks | p. 42 |
| Looking at Strikeout Totals | p. 43 |
| Defining a Strikeout Rate | p. 44 |
| Comparing Strikeout Rates of Starters and Relievers | p. 47 |
| Association Between Strikeouts and Walks? | p. 48 |
| Exploring Walk Rates | p. 49 |
| Comparing Walk Rates of Starters and Relievers | p. 50 |
| Introducing Probability | p. 51 |
| Beyond Data Analysis | p. 51 |
| Looking for Real Effects | p. 53 |
| Predicting OBPs | p. 55 |
| Probability Models | p. 57 |
| A Coin-Toss Model | p. 57 |
| Observed and True OBPs | p. 59 |
| Learning about Batting Ability | p. 62 |
| Estimating Batting Ability Using a Confidence Interval | p. 66 |
| Comparing Hitters | p. 68 |
| Situational Effects | p. 71 |
| Surveying the Situation | p. 72 |
| Looking for Real Effects | p. 74 |
| Observed and True Batting Averages | p. 75 |
| Batting Averages of the 1998 Regulars | p. 78 |
| Two Models for Batting Averages | p. 79 |
| A .276 Spinner Model | p. 79 |
| Do All Players Have the Same Ability? | p. 80 |
| A Model Using a Set of Random Spinners | p. 81 |
| Situational Effects | p. 86 |
| Home vs. Away | p. 86 |
| Turf vs. Grass | p. 87 |
| The Count | p. 87 |
| Opposite Arm vs. Same Arm | p. 87 |
| Models for Situational Effects | p. 87 |
| Scenario 1 (No Situational Effect) | p. 89 |
| Scenario 2 (Situational Bias) | p. 90 |
| Scenario 3 (Situational Effect Depends on Ability) | p. 91 |
| Finding Good Models | p. 92 |
| What Do Observed Situational Effects Look Like When There Is No Effect? | p. 93 |
| The Last Five Years' Data | p. 95 |
| The "No Effect" Situations | p. 96 |
| The "Bias" Situations | p. 98 |
| The "Ability" Situations | p. 101 |
| How Large Are the True Ability Effects? | p. 106 |
| Game Situation Effects | p. 107 |
| A Lot of Noise | p. 108 |
| Streakiness (Or, the Hot Hand) | p. 111 |
| Thinking about Streakiness | p. 112 |
| Interpreting Baseball Data | p. 114 |
| Moving Averages--Looking at Short Intervals | p. 116 |
| Runs of Good and Bad Games | p. 119 |
| Numbers of Good and Poor Hitting Days | p. 120 |
| What Is Zeile's True Hitting Ability? | p. 120 |
| Mr. Consistent | p. 122 |
| How Does Mr. Consistent Perform During a Season? | p. 122 |
| Mr. Streaky | p. 126 |
| How Does Mr. Streaky Perform During a Season? | p. 129 |
| Mr. Consistent or Mr. Streaky? | p. 132 |
| Team Play | p. 134 |
| A Consistent Team | p. 138 |
| A Streaky Team | p. 141 |
| Thinking about Streakiness--Again | p. 143 |
| Measuring Offensive Performance | p. 145 |
| The Great Quest | p. 146 |
| Runs Scored per Game | p. 148 |
| Batting Average and Runs Scored per Game | p. 153 |
| Slugging Percentage and On-Base Percentage | p. 157 |
| Intuitive Techniques | p. 165 |
| On-Base Plus Slugging (OPS) | p. 166 |
| Total Average (TA) | p. 166 |
| Batter's Run Average (BRA) and Scoring Index (DX) | p. 170 |
| Runs Created (RC) | p. 171 |
| More Analytic Models | p. 174 |
| Average Runs Per Play | p. 177 |
| Finding Weights for Plays | p. 177 |
| Least Squares Linear Regression (LSLR) | p. 178 |
| Adding Caught Stealing to the LSLR Model | p. 184 |
| Adding Sacrifice Flies to the LSLR Model | p. 187 |
| The Lindsey-Palmer Models | p. 189 |
| George Lindsey's Analysis | p. 189 |
| Palmer Enters the Picture | p. 199 |
| Comparing the LSLR and Lindsey-Palmer Models | p. 202 |
| The Curvature of Baseball | p. 207 |
| The DLSI Simulation Model | p. 208 |
| The Probability of Scoring Two Runs | p. 209 |
| The Probability of Scoring No Runs | p. 211 |
| A DLSI Example | p. 215 |
| Lessons from the Simulation | p. 219 |
| DLSI and Runs per Play | p. 224 |
| Where Do We Stand? | p. 226 |
| Additive Models | p. 227 |
| Product Models | p. 228 |
| Player Evaluations in the Best Models | p. 230 |
| Player Evaluations on an Average Team | p. 233 |
| Sorting Out Strengths and Weaknesses | p. 240 |
| Measuring Clutch Play | p. 243 |
| Clutch Hits | p. 245 |
| Leading Off an Inning vs. Not Leading Off | p. 249 |
| Runners in Scoring Position vs. Bases Empty | p. 249 |
| Runner in Scoring Position vs. Runner on First Base Only | p. 249 |
| Two Outs vs. None/One Out | p. 251 |
| Late Inning Pressure vs. No Late Inning Pressure | p. 251 |
| A Player in a Short Series | p. 251 |
| Situation Evaluation of Run Production | p. 253 |
| A New Criterion for Performance | p. 259 |
| The Calculation of Win Probabilities | p. 266 |
| Player Game Percentage (PGP) | p. 272 |
| World Series Most Valuable Players | p. 279 |
| Looking to the Future | p. 282 |
| Prediction | p. 285 |
| Predicting Game Results | p. 285 |
| Guessing | p. 286 |
| Picking the Home Team | p. 286 |
| A "Team Strengths" Prediction Model | p. 286 |
| Predicting 1999 Game Results | p. 287 |
| How Good Were Our Predictions? | p. 289 |
| Predicting the Number of McGwire and Sosa Home Runs | p. 291 |
| A Simple Prediction Method | p. 291 |
| What's Wrong with This Prediction? | p. 292 |
| A Spinner Model for Home-Run Hitting | p. 293 |
| How Many At-Bats? | p. 294 |
| What If We Knew Sosa's True Home-Run Rate? | p. 294 |
| Binomial Probabilities | p. 295 |
| What If We Don't Know Sosa's True Home-Run Rate? | p. 296 |
| Revising Our Beliefs about Sosa's Home-Run Probability | p. 298 |
| One Prediction | p. 299 |
| Many Predictions | p. 302 |
| Predicting Career Statistics | p. 305 |
| Sosa's Home-Run Probabilities | p. 306 |
| How Long and How Many At-Bats? | p. 307 |
| Making the Predictions | p. 309 |
| Did the Best Team Win? | p. 311 |
| The Big Question | p. 312 |
| Ability and Performance | p. 312 |
| Describing a Team's Ability | p. 314 |
| Describing a Team's Performance | p. 314 |
| Team Performance: 1871 to the Present | p. 315 |
| Explanations for the Winning Percentages | p. 317 |
| A Normal Curve Model | p. 319 |
| Team Performances over Time (Revisited) | p. 321 |
| A Mediocrity Model for Abilities | p. 323 |
| A Normal Model for Abilities | p. 324 |
| Weak, Average, and Strong Teams | p. 325 |
| A Model for Playing a Season | p. 326 |
| Simulating a Season | p. 327 |
| Simulating an American League Season | p. 328 |
| Simulating Many American League Seasons | p. 332 |
| Performances and Abilities of Different Types of Teams | p. 333 |
| Simulating an Entire Season | p. 337 |
| Chance | p. 340 |
| Post-Game Comments (a Brief Afterword) | p. 343 |
| Bibliography | p. 347 |
| Table of Contents provided by Syndetics. All Rights Reserved. |
ISBN: 9780387988160
ISBN-10: 0387988165
Series: Copernicus
Published: 8th June 2001
Format: Hardcover
Language: English
Number of Pages: 372
Audience: General Adult
Publisher: Springer Nature B.V.
Country of Publication: US
Dimensions (cm): 24.13 x 16.51 x 3.18
Weight (kg): 0.67
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