【第7弹】大数据是如何改变NBA的？ How Big Data transformed the NBA？
一股看不见的强大力量 An invisible, powerful force is lifting
将职业篮球提升到新的高度。 professional basketball to new heights.
这项价值数十亿美元 Transforming how this multi-billion dollar
体育运动的改变已经上演。 sport is played.
在精英运动中，成功与失败的区别 In elite sport, the difference between success and failure
通常相差无几。 is often the finest of margins.
加油！火箭！喔！ Go！Rockets！woo!
在NBA篮球比赛中，休斯顿火箭队 The Houston Rockets are one of the top teams
是豪门球队之一 in NBA basketball.
他们拥有一些联盟最棒的球员， They boast some of the sport's biggest stars,
包括2018赛季MVP球员。 including the NBA's Most Valuable Player in 2018.
在进攻时我们努力做到最好， Offensively what we were trying to do,
在防守时我们也尝试做到最好， defensively what we were trying to do,
因此，关键是每个晚上在任何位置上 so the focus is trying to be on the same page
我们都努力做到最好 every position for every game.
在过去十年中， In the past decade,
火箭队已经从一支联盟中游的平庸球队， the Rockets have risen from mid-table mediocrity
变成了NBA总冠军的有力竞争者。 to serious NBA Championship contenders.
这一戏剧化的转变，不仅仅是依靠明星球员的努力， It's not just big names that have
还有大数据的支撑。 fueled this dramatic ascent, it's big data.
我们分析的数据非常重要。 The data that we go over is definitely important,
你明白的，它提供了非常大的帮助。 you know, I think it gives us a little bit of an edge.
将数据和天赋融合是一件很重要的事。 To keep a balance of data and instinct is a big thing.
火箭队最近的成功 The Rockets' recent success
很大程度上归功于他们的开创性决定： owes much to their pioneering decision
开始处理有关比赛各个方面的数据。 to start crunching data about every aspect of their game.
这是负责人。 And this is the man responsible.
分析确实渗透到了一切， Analytics has really permeated everything,
我们的优势已经让我们赢得了 our edge has allowed us to win the most games,
去年65场之多的比赛。 65, last year.
在众多NBA经理中， 计算机科学家达里尔莫雷 Computer scientist Daryl Morey
是这项体育运动最重要的 is the sport's foremost data and statistics guru
数据和统计专家。 among NBA bosses.
你可以把胜利分成两件事， You can break winning down into two things,
一个是每次占有多少分， one is how many points do you get per possession,
另外一个是你如何获得额外的收益？ and then how do you get extra possessions?
十年前，Daryl开始着手 Ten years ago, Daryl set out
寻找那个获胜的法则。 to find that winning formula.
火箭队是安装先锋视频跟踪系统的 The Rockets were one of four NBA teams
四支NBA球队之一， to install a pioneering video tracking system,
该系统从比赛中挖掘原始的数据。 which mined raw data from games.
他们的发现改变了球队获胜的方式。 What they discovered changed the way teams tried to win.
数据显示了哪些投篮 The data revealed which shots provided
提供了最优的回报，两分扣篮和三分球， the best bang for buck, two-point dunks,
从三分线外投篮， and three-pointers, shot from outside the three point line,
而不是从内线投射的远距离两分球。 rather than long-range two point shots from inside it.
这确实很戏剧化， It's pretty dramatic,
三点投篮有多强大。 how powerful the three point shot is.
你只需要让投三分球成本的三分之一 You only have to make a third of your three-point shots
值得你的两分球的一半即可。 to be worth a half of your two.
即使这样，还会有额外的想法， Even within that, there's an extra miss
你可能会在进攻时反打。 you might rebound offensively.
在20世纪90年代，三分线内的 In the 1990s, long two-point shots
长距离两分球很常见。 from just inside the three-point line were common.
但Daryl的分析显示，从统计学上来说， But Daryl's analysis showed that statistically,
这些投篮却收到了最低的回报。 these shots provided the worst return.
在过去十年中，每年尝试 The number of attempted three-point shots has increased
三分球的次数都在增加。 every year for the past decade.
在2017-2018赛季，火箭队的三分球命中率 In the 2017-18 season, the Rockets made more
超过NBA历史上任何一支球队。 three pointers than any other team in NBA history.
这是他们比任何竞争对手 And this was a major reason they won more
赢得更多比赛的主要原因。 games than any of their rivals.
每个百分比参数在体育运动中都很重要， Every percentage matters in sports,
并且提取这些百分比 and extracting those percentages
则是数据变得更简单化。 is what's really become much easier with data.
我们正处于一个相当大的体育转型阶段。 We're in a pretty big transformational stage in sport.
Rajiv Maheswaran教授 Professor Rajiv Maheswaran
共同创立了Second Spectrum。 (运动数据分析公司) co-founded Second Spectrum.
这家数据分析公司收集和编码了 The analytics company gathers and codes
来自30支NBA球队的 a vast range of increasingly granular data
大量日益细化的数据。 for all 30 NBA teams.
感觉就像两个棋子。 It feels like two chess pieces.
现在，摄像机可以跟踪和记录 Cameras now track and record
每个球员的3D空间数据 3D spacial data for every player and ball movement
以及每秒25帧的篮球移动。 at 25 frames per second.
机器学习技术使用大量数据 Machine learning technology uses this huge volume of data
来产生交互式可视化， to produce interactive visualizations,
并允许团队分析他们的表现细节， allowing teams to analyze the minutiae
并在球场上获得的边际收益。 of their performances, and achieve marginal gains on court.
起初我们教了机器大约20个术语， At first we taught the machine about 20 terms,
现在它知道超过500个篮球术语。 right now it knows over 500 basketball terms.
因此，该机器基本上是具备了 So the machine is essentially the integrated knowledge
所有精英篮球教练的综合知识。 of all the elite basketball coaches.
它们特别关注围绕球员移动的 There is a particular focus
所有重要数据 on all important data around player movement,
以及投中的概率。 and the probability of making a shot.
我们可以用机器做的就是 What we can do with the machine is to say
看看像这样所有的投篮， look at all the shots like this one,
然后告诉我这个投篮真的可以用于 and tell me the chance that the shot really could
这个球员或其他普通球员的可能性。 go in either for this player or for an average player.
而且你收获了一个人可以看到的所有东西， And you bring in all the things that a person can see,
不仅仅是他们站在哪里，而是他们如何移动， not just where they're standing, but how they're moving,
以及他们想要采取什么类型的进攻， what type of shot they're trying to take,
防守者在哪里？ where are the defenders?
而我们能做的就是 And what we can do is put a number
把以前感觉或定性的东西进行数字化。 to what previously was a feeling, or something qualitative.
数据分析甚至改变了 Data analysis has even changed
如火箭队这样成功球队 the type of players that successful teams,
所拥有的球员类型。 like the Rockets, have.
今天的球员平均而言更精简，更敏捷。 Players today are on average leaner and more agile.
拥有熟练的球员， Having skilled players,
即使他们有点小， even if they're a little smaller,
也比拥有技术水平较低的大个子 is more important than having bigger guys
更重要。 who are less skilled.
在每个赛季从大学选秀中招募新球员时， When it comes to recruiting new players
仔细研究球员表现的数据 from the college draft each season,
已经让火箭队 poring over data on player performance
获得了优势。 has given the Rockets a winning edge.
我们已经能够勉强维持5％的优势， We've been able to eke out about a 5% edge,
而事实证明这是一个巨大的优势。 and that actually turns out to be a massive advantage.
职业篮球队的NBA总决赛结局。 Pro basketball's finale for the NBA title.
篮球不断变化， Basketball has constantly changed,
但它即将进入一个勇敢的全新世界， but it's about to enter a brave new world,
在教练的手中， 数据可能会是球场上的一个方面， where data could be court-side in the hands of coaches,
有助于扭转比赛。 helping to swing a game as it happens.
数据总是变得越来越快， The data's always getting faster and faster,
数据过去需要几个小时， the data used to take hours,
我们已经把它缩短到几分钟， we've got it down to minutes,
而且很快就会下降到几秒钟。 and very soon it'll be down to seconds.
它基本上会 It's basically going to become
非常非常快地实现功能。 functionally real-time very, very soon.
我不认为我们已经触及到 I don't think we've scratched the surface
这些存在可能性的大数据的表面。 of what's possible with data.