Posted May 6, 2013on:
这书很好看 而且其实是讲大数据里面淘金的故事 国内的人这么热衷于讲云计算和大数据 连带着机器学习的人也火了起来 却没有一个人有很具体的例子 他们每个人都应该看看这本书 或者最差的 也应该看看坊间关于Target怎么通过用户的购买历史来预计他们的未来购买以及Target如何在一个爸爸知道之前成功的预计了他的十几岁的女儿的怀孕
闲话不提了 这个故事是说在baseball这个行业里面 没有nba那样的salary cap 所以有钱的队伍就可以拼命砸钱挖走所有的大明星 所谓大明星就是具有现在大家公认的一些能够赢球的特征的人 比如本垒打的能力 那没有钱的队伍只能拥有“二流”球员 那这个game怎么玩儿呢？ It turns out that the criteria that most people had about what makes a player valuable were wrong because baseball knowledge was gained and accumulated through scouts, players and managers, mostly human analysis. There are a small set of baseball fans who started to analyze the stats of each game using computers and finds out the result of a game is more likely to be determined by some other stats than the ones used as folklore knowledge of the insiders.
Oakland A’s is the first team that tries to utilize this information asymmetry to win the games despite their meager budget (which is like one-tenth of the Yankee’s for example). And by enlisting the players that wouldn’t pass the old human criteria, but who conforms to what a computer program (in fact, a data mining program) says, they sustained a record of most winning games and made it to the playoff, as the second to last poorest team in the baseball league.
A very inspiring story! I find the details of how they traded people very boring, since I know next to nothing about baseball and therefore cannot follow the trading logic much and therefore cannot appreciate how clever the general manager of Oakland A’s has been in terms of orchestrating such maneuvers. But I find the personal stories behind the managers, the players fascinating — a lot on talent and how talent plays out or how talent doesn’t play out because raw talent sometimes is not enough and you need to be able to manage your raw talent or release it at the time of demand.
A very fun read.