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2.0 out of 5 stars A sacrifice of objective conclusions for surprising revelations., June 15, 2013
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This review is from: The Numbers Game: Why Everything You Know About Football is Wrong (Kindle Edition)
As a statistician and soccer fan, I have always been a fan of books that attempt to sift through the data and come to objective conclusions about the reality of the game. Unfortunately, the book's positioning statement (Why Everything You Know About Football is Wrong) appears to have been implemented at the expense of objective conclusions based on that data.
Let me give you a brief example based on certain claims made in Chapter 1.

The authors make the conclusion that half of all games are decided by luck, unfortunately, this conclusion does not follow from its premises.

- The first problem (I admit, this might be a failure to clarify as opposed to making unwarranted conclusion) is that the authors fail to specify how draws work into their analysis. They claim that "a little over half" of all games are won by favorites and that "the likelihood of the underdog winning was 45.2%" while at the same time stating that 1-1 draws are the most common score line. It may just be that the percentages they offer simply do not include game that ended in a draw, however, if this is the case, they did a terrible job communicating this to the reader.

- The authors also failed to eliminate other possible explanations for their data and instead jumped to the one conclusion that might result in the more surprising revelation. Their claim that 50% of games are decided by luck stems primarily from the fact that only about 50% of the game is won by favorites, therefore if skill is not the determining factor in a specific game, it must have been a result of chance. One very possible reason is that even though team A is favored over team B, team A's quality is only slightly better than team B so that even if skill was the determining factor most of the time, in the long run the difference in quality is not enough to break the 50/50 paradigm. In other words, the nature of the game might require a more drastic difference in quality in order for one team to dominate another, but this does not help to establish that a slight favorite losing is simply a result of chance.

- Another problem in their analysis is that they set up a false dichotomy between skill and luck, as if these were the only two contributing factors to the result. This is surprising since they talk about the 48/26/26 rule (48% of game are home wins, 26% ties and 26% losses). Most of the data they collect comes from League games, where every team plays every other team at home and away. Therefore, since 50% of all games are won by the home team and 50% of all home teams are underdogs, it renders the fact that roughly 50% of all games are won by the underdog a lot less surprising.

Examples such are these are scattered throughout the book and it is difficult to know whether these are a result of lack of clarification or intellectual dishonesty.
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Showing 1-3 of 3 posts in this discussion
Initial post: Jun 17, 2013 6:39:34 PM PDT
Saman says:
Hey Miguel, any books you can recommend about how statistics are used in the game? Or any books about soccer and stats/data in general?

Posted on Jul 8, 2013 8:06:32 AM PDT
[Deleted by the author on Jul 24, 2013 10:10:49 AM PDT]

Posted on Jul 24, 2013 10:10:40 AM PDT
G. Foreman says:
The most common outcome is a 1-1 draw, which occurs 11.63% of the time. The next most common results are 1-0, 2-1, and 2-0 home wins, so the first issue you've brought up is a total nonstarter-surely you can't think that a 1-1 draw occurring 11.63% of the time is incompatible with unfavoured teams winning 45.2% of matches. You seem to have completely misunderstood several key tenets of the book that are very well explained, these being the Poisson distribution, intransitive triplets, and Bayesian statistics. I suggest you go back and reread Chapter 1 more thoroughly.

Your second point makes no sense whatsoever-the authors are using very large datasets, and as the sample size increases there will be correction for the issues you're bringing up. Obviously when two teams are more evenly matched luck will play a greater role, but these data include matches between teams of the highest calibre against relegation fodder, where luck will have little bearing on the outcome.

I can't even begin to comprehend what you're trying to communicate with the third point, since it seems to be utter nonsense.

Your entire review suggests that you merely skimmed the book and either didn't understand or rejected the presented analysis. There's no intellectual dishonesty in the book, but this review reeks of it.
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