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Download Analyzing Wimbledon: The Power of Statistics by Franc Klaassen PDF

By Franc Klaassen

The sport of tennis increases many questions which are of curiosity to a statistician. Is it real that starting to serve in a collection supplies a bonus? Are new balls a bonus? Is the 7th video game in a collection rather vital? Are best avid gamers extra sturdy than different avid gamers? Do genuine champions win the massive issues? those and lots of different questions are formulated as "hypotheses" and confirmed statistically.

Analyzing Wimbledon additionally discusses how the result of a fit could be envisioned (even whereas the fit is in progress), which issues are very important and which aren't, the way to opt for an optimum provider method, and even if "winning temper" truly exists in tennis. geared toward readers with a few wisdom of arithmetic and statistics, the ebook makes use of tennis (Wimbledon specifically) as a motor vehicle to demonstrate the ability and sweetness of statistical reasoning.

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Additional info for Analyzing Wimbledon: The Power of Statistics

Example text

Let us call him player I and Nadal player J . 198 (Nadal). 455, respectively. 046, hence more Forecasting Prob. 7%) than one because of the overround. 435. 5%. 7%. 011. 2% (Nadal) from which the match profile can be computed. 1 from Federer’s point of view. 5%. 7%. Big swings occurred at the end of the fourth set. Nadal led 5-2 in the tiebreak, then double-faulted to 5-3. At 7-6 and again at 8-7, Nadal had matchpoints (the second time on his own service). Eventually Federer won the tiebreak 10-8.

Surprisingly, however, a direct estimate of the probability that a player or a team wins the match is not shown. In this chapter we provide such a direct estimate for tennis. We forecast the winner of a match, not only at the beginning of the match, but also while the match is unfolding; in fact, at each point. The forecast is produced within one second after each point, and the resulting profile of winning probabilities provides a quick overview of the match developments so far and a direct forecast of who will win the match.

The idea behind creating the new parameters is twofold. First, we realize that pi and pj are related to each other: if I is a top player while J is not, then we would expect pi to be large and pj to be small. In contrast, pi − pj and pi + pj may be much less related. Second, it may be the case that the probability si that I wins the set (which is what interests us here) depends primarily on one of these two new parameters and very little on the other. We shall see that both ideas hold here. The interpretation of the new parameters is as follows.

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