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Publisher:

Oxford University Press

Publication Date:

2014

Number of Pages:

252

Format:

Paperback

Price:

99.00

ISBN:

9780199355952

Category:

General

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1. Warming up

Wimbledon

Commentators

An example

Correlation and causality

Why statistics

Sports data and human behavior

Why tennis?

Structure of the book

Further reading

2. Richard

Meeting Richard

From point to game

The tiebreak

Serving first in a set

During the set

Best-of-three versus best-of-five

Upsets

Long matches: Isner-Mahut 2010

Rule changes: the no-ad rule

Abolishing the second service

Further reading

3. Forecasting

Forecasting with Richard

Federer-Nadal, Wimbledon final 2008

Effect of smaller ¯p

Kim Clijsters defeats Venus Williams, US Open 2010

Effect of larger ¯p

Djokovic-Nadal, Australian Open 2012

In-play betting

Further reading

4. Importance

What is importance?

Big points in a game

Big games in a set

The vital seventh game

Big sets

Are all points equally important?

The most important point

Three importance profiles

Further reading

5. Point data

The Wimbledon data set

Two selection problems

Estimators, estimates, and accuracy

Development of tennis over time

Winning a point on service unraveled

Testing a hypothesis: men versus women

Aces and double faults

Breaks and rebreaks

Are our summary statistics too simple?

Further reading

6. The method of moments

Our summary statistics are too simple

The method of moments

Enter Miss Marple

Re-estimating p by the method of moments

Men versus women revisited

Beyond the mean: variation over players

Reliability of summary statistics: a rule of thumb

Filtering out the noise

Noise-free variation over players

Correlation between opponents

Why bother?

Further reading

7. Quality

Observable variation over players

Ranking

Round, bonus, and malus

Significance, relevance, and sensitivity

The complete model

Winning a point on service

Other service characteristics

Aces and double faults

Further reading

8. First and second service

Is the second service more important than the first?

Differences in service probabilities explained

Joint analysis: bivariate GMM

Four service dimensions

Four-variate GMM

Further reading

9. Service strategy

The server's trade-off

The y-curve

Optimal strategy: one service

Optimal strategy: two services

Existence and uniqueness

Four regularity conditions for the optimal strategy

Functional form of y-curve

Efficiency defined

Efficiency of the average player

Observations for the key probabilities: Monte Carlo

Efficiency estimates

Mean match efficiency gains

Efficiency gains across matches

Impact on the paycheck

Why are players inefficient?

Rule changes

Serving in volleyball

Further reading

10. Within a match

The idea behind the point model

From matches to points

First results at point level

Simple dynamics

The baseline model

Top players and mental stability

Lessons from the baseline model

New balls

Further reading

11. Special points and games

Big points

Big points and the baseline model

Serving first revisited

The toss

Further reading

12. Momentum

Streaks, the hot hand, and winning mood

Why study tennis?

Winning mood in tennis

Breaks and rebreaks

Missed breakpoints

The encompassing model

Further reading

13. The hypotheses revisited

Winning a point on service is an iid process

It is an advantage to serve first in a set

Every point (game, set) is equally important to both players

The seventh game is the most important game in the set

All points are equally important

The probability that the service is in, is the same in the men's singles as in the women's singles

The probability of a double fault is the same in the men's singles as in the women's singles

After a break the probability of being broken back increases

Summary statistics give a precise impression of a player's performance

Quality is a pyramid

Top players must grow into the tournament

Men's tennis is more competitive than women's tennis

A player is as good as his or her second service

Players have an efficient service strategy

Players play safer at important points

Players take more risk when they are in a winning mood

Top players are more stable than others

New balls are an advantage to the server

Real champions win the big points

The winner of the toss should select to serve

Winning mood exists

After missing breakpoint(s) there is an increased probability of being broken in the next game

Appendix A: List of symbols

Winning probabilities

Score probabilities and importance

Service probabilities

Quality

Operators

Miscellaneous variables

Random/unexplained parts

Parameters

Miscellaneous symbols

Appendix B: Data, software, and mathematical derivations

Data Program Richard

Mathematical derivations

Bibliography

Index

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