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Summary
Summary
Can you really keep your eye on the ball? How is massive data collection changing sports?
Sports science courses are growing in popularity. The author's course at Roanoke College is a mix of physics, physiology, mathematics, and statistics. Many students of both genders find it exciting to think about sports. Sports problems are easy to create and state, even for students who do not live sports 24/7. Sports are part of their culture and knowledge base, and the opportunity to be an expert on some area of sports is invigorating. This should be the primary reason for the growth of mathematics of sports courses: the topic provides intrinsic motivation for students to do their best work.
From the Author:
"The topics covered in Sports Science and Sports Analytics courses vary widely. To use a golfing analogy, writing a book like this is like hitting a drive at a driving ran≥ there are many directions you can go without going out of bounds. At the driving range, I pick out a small target to focus on, and that is what I have done here. I have chosen a sample of topics I find very interesting. Ideally, users of this book will have enough to choose from to suit whichever version of a sports course is being run."
"The book is very appealing to teach from as well as to learn from. Students seem to have a growing interest in ways to apply traditionally different areas to solve problems. This, coupled with an enthusiasm for sports, makes Dr. Minton's book appealing to me." --Kevin Hutson, Furman University
Reviews (1)
Choice Review
This work discusses how mathematics is used to analyze popular American sports like football, baseball, and basketball. Minton (mathematics, Roanoke College) has based this book on several of his undergraduate courses. The book covers two major aspects: the physics involved in sports (e.g., the motion of a ball) and the statistics used to make probabilistic ratings of performance and success. The beginning chapters consider topics from mechanics, such as "Projectile Motion," "Rotational Motion," and "Collisions." The rest of the text is devoted to statistics used in sports ratings and analysis, with many examples from specific games played in the big leagues or by major colleges. The material covered is selective and quirky; the level of analytical mathematics and statistics ranges from simple to advanced, including calculus, matrixes, and game theory. Each chapter has solved examples and end-of-chapter questions, problems, and suggestions for projects. There are pictures and graphs interspersed throughout the text. The book is not suitable as a standard text in any conventional course--it will best serve as a supplement. Summing Up: Recommended. Lower- and upper-division undergraduates. --Nanjundiah Sadanand, Central Connecticut State University
Table of Contents
Preface | p. xiii |
List of Figures | p. xvii |
List of Tables | p. xxi |
1 Projectile Motion | p. 1 |
Introduction | p. 1 |
Figuring with Newton | p. 1 |
Hangin' with MJ: 1-D Motion | p. 3 |
Raining 3's with Steph: 2-D Motion | p. 4 |
K's with Kershaw: Terminal Velocity and Drag Forces | p. 6 |
Calculus Box: Solving for Velocity | p. 7 |
Bending with Bubba: Magnus Force | p. 8 |
Smiling with Dimples | p. 11 |
Calculus Box: A General Model of a Ball in Flight | p. 12 |
The Effects of Drag and Lift | p. 13 |
Knuckling Down | p. 15 |
Calculus Box: Lateral Position of a Knuckleball | p. 17 |
Exercises | p. 18 |
Further Reading | p. 23 |
2 Rotational Motion | p. 25 |
Introduction | p. 25 |
Going in Circles | p. 26 |
Torquing Off Newton | p. 28 |
All About MOI | p. 29 |
Size Is Important | p. 30 |
Calculus Box: Calculating MOI | p. 30 |
Equipment Design | p. 31 |
Supercats and Tamedogs | p. 32 |
Keeping the Momentum | p. 33 |
Exercises | p. 34 |
Further Reading | p. 38 |
3 Sports Illusions | p. 39 |
Introduction | p. 39 |
You Can't Keep Your Eye on the Ball | p. 39 |
You Can't Touch This | p. 41 |
You Can't Teach Size | p. 42 |
You Can't Afford the Yardage | p. 43 |
You Can't Bend That Way | p. 45 |
You Can't Make That Call! | p. 46 |
You Can't Clear That Bar | p. 49 |
Exercises | p. 50 |
Further Reading | p. 54 |
4 Collisions | p. 55 |
Introduction | p. 55 |
Linear Momentum | p. 56 |
Impulse and Force | p. 57 |
Calculus Box: Integration | p. 59 |
Giving to Receive | p. 60 |
Tendons and Tennis | p. 61 |
Coefficient of Restitution | p. 62 |
Incoming and Outgoing | p. 63 |
Derivative Works | p. 65 |
The Way the Ball Bounces | p. 66 |
Freeze Frame | p. 67 |
Exercises | p. 68 |
Further Reading | p. 71 |
5 Ratings Systems | p. 73 |
Introduction | p. 73 |
Right versus Best | p. 74 |
Ratings versus Rankings | p. 74 |
The Massey System | p. 75 |
Connected Schedules | p. 77 |
Massey Win Ratings | p. 78 |
Offense and Defense | p. 79 |
Least Squares Equivalence | p. 79 |
Wins versus Points | p. 80 |
The Colley System | p. 81 |
A Flaky Scaling Problem | p. 82 |
The Elo System | p. 83 |
Strength of Schedule | p. 85 |
Computing Probabilities | p. 85 |
Weighty Issues | p. 86 |
Calculus Box: A Recipe for Reduction of Matrices | p. 87 |
Exercises | p. 90 |
Further Reading | p. 94 |
6 Voting Systems | p. 95 |
Introduction | p. 95 |
How They Vote | p. 96 |
Condorcet's Intransitive Attitude | p. 97 |
Preference Lists, Voting Systems, and Chaos | p. 99 |
Fairness and the Arrow of Impossibility | p. 101 |
Positional Voting Systems | p. 102 |
A Return to Sports Voting | p. 103 |
Simulations | p. 104 |
Range Voting | p. 106 |
PageRank and MVPassing | p. 108 |
Seeding of Tournaments | p. 110 |
Probability Box: Put Some Error Bars on Those Things | p. 112 |
Exercises | p. 113 |
Further Reading | p. 119 |
7 Saber- and Other Metrics | p. 121 |
Introduction | p. 121 |
The Pythagorean Cult | p. 122 |
When Good Statistics Go Bad | p. 125 |
Rates versus Numbers | p. 127 |
Persistence and Reliability | p. 128 |
On the Defensive | p. 130 |
Plus and Minus | p. 131 |
Park Factors | p. 132 |
Four Factors, Fenwick, and Football | p. 134 |
Evaluation and Prediction | p. 137 |
Regression to the Mean | p. 138 |
Linear Weights: A Prelude to WAR | p. 139 |
Calculus Box: Linear Regression | p. 141 |
Roger Maris and the Hall of Fame | p. 141 |
Now Trending | p. 142 |
Exercises | p. 144 |
Further Reading | p. 150 |
8 Randomness in Sports | p. 151 |
Introduction | p. 151 |
Summing Up the Basics | p. 152 |
Prediction is Difficult | p. 154 |
A Slump or a Disaster | p. 155 |
Calculus Box: Probability | p. 156 |
May the Best Team Win | p. 157 |
Measuring Parity: Gini in a Bottle | p. 158 |
Measuring Parity: Luck versus Skill | p. 161 |
The Paradox of Skill | p. 162 |
Measuring Parity: Entropy | p. 163 |
Declaration of Independence | p. 164 |
Conditional Probability | p. 165 |
The Hot Hands | p. 166 |
Not So Fast, My Friend | p. 167 |
Runs Tests | p. 168 |
Joltin Joe and The Streak | p. 169 |
Not Following the Rules | p. 170 |
BABIP and DIPS | p. 171 |
Random Thoughts | p. 172 |
Exercises | p. 173 |
Further Reading | p. 178 |
9 Sports Strategies | p. 179 |
Introduction | p. 179 |
Don't Punt, John! | p. 180 |
Bill Belichick's Gambles | p. 181 |
The Value of a Play | p. 183 |
Markov Chain Models | p. 184 |
The Expected Runs Matrix | p. 187 |
Win Probability and Leverage | p. 187 |
Game Control and the Story Stat | p. 188 |
Game Theory | p. 189 |
Upsetting the Game Theory | p. 193 |
Getting and Giving Two | p. 194 |
The Physical Challenge | p. 195 |
Personnel Decisions: Aging | p. 196 |
Personnel Decisions: Transfer Fees and Stars | p. 197 |
Exercises | p. 199 |
Further Reading | p. 202 |
10 Big Data and Beyond | p. 203 |
Introduction | p. 203 |
Big Data Is Watching You | p. 204 |
A Theory of Everything | p. 205 |
Catch Me If You Can | p. 207 |
Getting Framed | p. 208 |
Anonymous Field Goal Kicking | p. 209 |
On the Rebound | p. 211 |
Breaching the Convex Hull | p. 213 |
Calculus Box: A Goal-Scoring Model | p. 215 |
Showing Hot and Cold | p. 217 |
RIP to the RPI | p. 218 |
Blackbox Analytics | p. 220 |
PeeWee Analytics | p. 222 |
Wearable Tech | p. 223 |
Exercises | p. 223 |
Further Reading | p. 226 |
Answers and Selected Solutions | p. 227 |
Index | p. 253 |