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Ebook `Moneyball: the art of winning an unfair game`: ebooks list of Michael ( Michael M.) Lewis. download PDF (original scan). This ebook is usually. Editorial Reviews. Review. Billy Beane, general manager of MLB's Oakland A's .. Download Audiobooks · Book Depository Books With Free Delivery Worldwide · Box Office Mojo Find Movie Box Office Data · ComiXology. Thousands of. Aug 15, Title: ((DOWNLOAD)) EPUB Moneyball The Art of Winning an Unfair Game [Free Ebook], Author: raxtonsagag, Name: ((DOWNLOAD)) EPUB.

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Full Collection, Read Moneyball: The Art of Winning an Unfair Game Book, Download Moneyball: The Art of Winning an Unfair Game Ebook Moneyball: The. Mar 13, Right now you can download a Kindle version of Moneyball for only $ Or, if you're an Amazon Prime member, you can read it for FREE!. Sep 9, [PDF] Download Moneyball: The Art of Winning an Unfair Game Ebook | READ ONLINE Download at.

Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. To get the free app, enter your mobile phone number. Lewis was in the room with the A's top management as they spent the summer of adding and subtracting players and he provides outstanding play-by-play. In the June player draft, Beane acquired nearly every prospect he coveted few of whom were coveted by other teams and at the July trading deadline he engaged in a tense battle of nerves to acquire a lefty reliever. Besides being one of the most insider accounts ever written about baseball, Moneyball is populated with fascinating characters.

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The library card you previously added can't be used to complete this action. Please add your card again, or add a different card. Are the stats of a high school player informative enough or does it make sense to ignore them and focus on the college players who have a longer history?

Are there metrics that confuse skill and luck and contain no useful information even about the past performance, let alone the future?

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Further, suppose the future values of a measurable characteristic e. So far so good, but exactly how much does that particular skill contribute to the ultimate objective, winning a game at the lowest cost? Say, if the future foot speed of the player is guaranteed to be as good as it has been, how much the team should be willing to pay for the player?

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If the answer is known, the GM can then perform some arbitrage by selling players whose characteristics are overpriced and buying those whose characteristics are underpriced. It may appear strange that those questions were not raised and addressed until after Billy Beane became the GM of Oakland Athletics in Apart from the philanthropic attitude of the team owners, there were other reasons why.

Before the late s, quantitative analysis of baseball data was both hard for the lack of computers and impractical because the players' salaries were not that high.

Most importantly, the eventual adoption of quantitative performance evaluation methods revealed that the baseball data are extremely noisy. To extract some useful insights, one has to generalize from a large body of stats that no living scout or other baseball insider can keep in his head.

Likewise, to see whether a given quantitative approach does not work, it's not enough to follow the career of a single player or observe the outcome of a single game. That nourished the perception that quantitative metrics are more or less useless and recoursing to one's "internal compass" works better when it's time to draft players and then decide how not to use them during the game.

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An example of such attitude is the scouts' belief that "if you see it once, it's there", which is a ringing endorsement of making a decision based on the sample size of one.

Given how much the outcome of anything that happens on the field depends on luck, that's a kiss of death for good scouting, or at least for a cost-effective version of it.

Undoubtedly, baseball teams vary in skill, but, according to the book, the contribution of skill to the outcome of an average game is about four times less than the contribution of luck.

In particular, the number of games in playoffs is so small that luck doesn't cancel out: Because a team that loses in the playoffs cannot get the coveted World Series title it creates another psychological incentive for having little faith in the quantitative approach.

To me it also means that if all of the noise were to disappear and that's what "sabermetrics" is trying to achieve , the game would become far less fun to watch and talk about. There is not much thrill in observing how a slightly biased coin is flipped.

Isn't that another reason why both the insiders and fans preferred to stick to the old ways instead of embracing the "performance scouting" and other insights offered by sabermetrics? If that's the case then The Club turns out to be far more rational and efficient than Lewis portrayed. Next, I'd like to explore the most important point made by Lewis: To me it has always been clear that being good at brainteasers does not predict one's future job performance unless the job amounts to solving brainteasers.

Both companies banned the practice in the end, even though some copycats are still lurking around. The point, however, is why it lasted for as long as it did.

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Apparently, the engineers at Microsoft and Google are no fools. They figured out that the brainteasers fail at achieving their purported objective many years ago. Why continue to use them, then? Moneyball provides a plausible explanation. Companies are not only about doing business but sometimes about being a certain social club.

The club entry requirements can be as arbitrary as anything.

If they appear, to put it mildly, irrational, that is to be expected every now and then. Therefore, the real question is not "Are you smart enough to work at Google?

Regardless of what the answer is, it has nothing to do with one's intelligence or the absence thereof. Now back to baseball. If you have some quantitative background I could highly recommend "Stein's Paradox in Statistics", a paper published by Prof. Efron in incidentally, that was the year Bill James published his first Baseball Abstract. The rather ancient article is quite in line with what I learned from Moneyball: It looks like my background in Statistics, combined with what I learned from the book, made it impossible to enjoy the game the way millions of fans do.

Nevertheless, I managed to derive a lot of value from Moneyball and I wish you the same. See all 1, reviews. Amazon Giveaway allows you to run promotional giveaways in order to create buzz, reward your audience, and attract new followers and customers.

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Moneyball : the art of winning an unfair game

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