【高级听力】（文末附视频）How Data Transformed the NBA

How Data Transformed the NBA

《文 末 附 视 频》

This may not be a word-for-word transcript.

An invisible, powerful force is lifting professional basketball to new heights, transforming how this multi-billion-dollar sport is played. 

In elite sport, the difference between success and failure is often the finest of margins.

“Go Rockets, woo!” 

The Houston Rockets are one of the top teams in NBA basketball. They boast some of the sport’s biggest stars, including the NBA’s Most Valuable Player in 2018. 

James Harden: You know, offensively what we were trying to do, and defensively what we were trying to do, so the focus is trying to be on the same page every position for every game.

In the past decade, the Rockets have risen from mid-table mediocrity to serious NBA Championship contenders. It’s not just big names that have fueled this dramatic ascent, it’s big data.

Michael Carter Williams: The data that we go over is definitely important, you know, I think it gives us a little bit of an edge. You know, to keep a balance of data and instinct is…is a big thing.

The Rockets’ recent success owes much to their pioneering decision to start crunching data about every aspect of their game. And this is the man responsible.

Daryl Morey: Analytics has really permeated everything, our edge has allowed us to win the most games, 65 last year.

Computer scientist Daryl Morey is the sport’s foremost data and statistics guru among NBA bosses.

Daryl Morey: You can break winning down into two things, one is how many points do you get per possession, and then how do you get extra possessions?

Ten years ago, Daryl set out to find that winning formula. The Rockets were one of four NBA teams to install a pioneering video-tracking system, which mined raw data from games. What they discovered changed the way teams tried to win. The data revealed which shots provided the best bang for buck, two-point dunks, and three-pointers, shot from outside the three-point line, rather than long-range two-point shots from inside it.

Daryl Morey: It’s pretty dramatic, how powerful the three-point shot is. You only have to make a third of your three-point shots to be worth a half of your two. Even within that, there’s an extra miss you might rebound offensively. 

Face up, pulls the trigger, buries it!

In the 1990s, long two-point shots from just inside the three-point line were common. But Daryl’s analysis showed that statistically, these shots provided the worst return. The number of attempted three-point shots has increased every year for the past decade.

In the 2017-18 season, the Rockets made more three pointers than any other team in NBA history. And this was a major reason they won more games than any of their rivals.

Rajiv Maheswaran: Every percentage matters in sports, and extracting those percentages is what’s really become much easier with data. We’re in a pretty big transformational stage in sport.

Professor Rajiv Maheswaran co-founded Second Spectrum. The analytics company gathers and codes a vast range of increasingly granular data for all 30 NBA teams.

“It feels like two chess pieces.”

Cameras now track and record 3D spacial data for every player and ball movement at 25 frames per second. Machine learning technology uses this huge volume of data to produce interactive visualizations, allowing teams to analyze the minutiae of their performances, and achieve marginal gains on court.

Rajiv Maheswaran: At first, we taught the machine about 20 terms, right now, it knows over 500 basketball terms. So the machine is essentially the integrated knowledge of all the elite basketball coaches.

There is a particular focus on all important data around player movement, and the probability of making a shot.

Rajiv Maheswaran: What we can do with the machine is to say: look at all the shots like this one, and tell me the chance that the shot really could go in either for this player or for an average player. And you bring in all the things that a person can see, not just where they’re standing, but how they’re moving, what type of shot they’re trying to take, where are the defenders? And what we can do is put a number to what previously was a feeling, or something qualitative.

Data analysis has even changed the type of players that successful teams, like the Rockets, have. Players today are on average leaner and more agile. 

Daryl Morey: Having skilled players, even if they’re a little smaller, is more important than having bigger guys who are less skilled. 

When it comes to recruiting new players from the college draft each season, poring over data on player performance has given the Rockets a winning edge.

Daryl Morey: We’ve been able to eke out about a 5% edge, and that actually turns out to be a massive advantage.

“Pro basketball’s finale for the NBA title.”

Basketball has constantly changed, but it’s about to enter a brave new world, where data could be court-side in the hands of coaches, helping to swing a game as it happens.

Rajiv Maheswaran: The data’s always getting faster and faster, the data used to take hours, we’ve got it down to minutes, and very soon it’ll be down to seconds. It’s basically going to become functionally real-time very, very soon. I don’t think we’ve scratched the surface of what’s possible with data.

↓ ↓ ↓

↑ ↑ ↑

↑ 建议在 WiFi 环境下观看 ↑，土豪随意