5 ms·

Quest to Track Every Shot in the NBA Changed Basketball

83 points by esalazar 12y ago

adamfeldman 12y ago
"Now, as new technologies start to generate terabytes of data about players and tactics, that next great competitive advantage will go to the number crunchers and analysts who can make sense of all those signals. Take the statistical tsunami of SportVU in the NBA. “It's not an exaggeration to say that 85 percent of the teams don't know what to do with this data,” Goldsberry says. “The idea that this is going to revolutionize the NBA—well, I'm not sure that's true unless teams awaken really quickly to things like machine learning and data visualization.""
- Nimi 12y ago
  Well, this sounds pretty much like an admission of the uselessness of his methods. Contrast this with Wins Produced (http://www.boxscoregeeks.com/faq http://www.boxscoregeeks.com/faq), a simple statistical model, and it's hard to see the point...
genofon 12y ago
I have worked with some NBA teams and they are already using software to track ball, players, referee, training, sleep, Heart Rate etc.. there is really nothing revolutionary in this article
- confluence 12y ago
  Looks like a bunch of heatmaps to me. Surprised no one did this earlier.
- mountaineer 12y ago
  Are you able to share any details of the software, devices and/or sensors they use? I've been kicking around ideas on how to bring these types of things to rec sports.
  - genofon 12y ago
    software: depends on the team, device: most of them use stats http://www.stats.com/sportvu/sportvu.asp http://www.stats.com/sportvu/sportvu.asp to track games and various wearable technology (which is not allowed in games ) on training. They are not as far behind as media portrait them, all these tracking devices (sleep. HR, GPS..) have been around for a long time. You wouldn't believe the stuff they tried, there are some snakeoils salesman but they usually end up pretty badly. Also for software there is a lot of variance, I feel that they prefer people that know personally or have previous experience. There are a few people making the decision to adopt a platform for a team to track all the data floating around, usually few high managers of physio, that's your audience. Usually it's highly customized and there is a lot of support as the user (coach, physio stuff, athlete...) is not a tech person
bmoresbest55 12y ago
As a basketball player/sports fan and computer programmer/ tech enthusiasts, I love to see people post these types of articles.
- swanson 12y ago
  Do you read Grantland? If not, check it out - they have great stuff at the intersection of nerds + sports on a regular basis.
  - cglee 12y ago
    My basketball knowledge increased 1000% after I started reading Bill Simmons & Zac Lowe.
  - PKop 12y ago
    http://fivethirtyeight.com/sports/ http://fivethirtyeight.com/sports/ as well
danh1979 12y ago
A curious non-sequitor: "The data wasn't exactly private, but neither was it public—Goldsberry scraped it from the web." If Goldsberry scraped the data from the web, wasn't the data inherently public?
- confluence 12y ago
  I'm sure lawyers would have a field day answering your question.
- pp19dd 12y ago
  So this situation happens in the news world all the time. While a company or agency has original databases, excel sheets, what have you - they don't consider that publishing them in a "human-readable" format is nearly the same thing as publishing the raw data. Try calling the place for a copy, and they'll hang up on you. But, they won't think that a crafty outsider can probably reconstruct the original by scraping. What's particularly interesting here is guessing the motivation behind publishing. Was the information a trade secret, or did a middle-manager want to show that their team is ahead of the others? Or are these feathers to show the company has the know-how and capability? In either case, most of the web-published data isn't initially considered as published data by the publishers, who in turn don't think to state any restrictions governing the data. That's when we scrape and make use of it - and even if there are restrictions on republishing, you can still perform and claim transformative derivative work. The fun legalese part is what happens when they discover what you're doing and try to lash out, or interrupt a standing scrape. One time, all it took to unblock access was to show up at a meeting and get yelled at by a police captain for 30 minutes. Our retort started with "In the interest of public safety, ..."
  - function_seven 12y ago
    > One time, all it took to unblock access was to show up at a meeting and get yelled at by a police captain for 30 minutes. Our retort started with "In the interest of public safety, ..." I'd like to hear more about your example.
    - 12y ago
the_cat_kittles 12y ago
"This Guy" publishes stuff regularly on Grantland, its not like he is an unknown
jimmytucson 12y ago
I've made the same types of charts--hexbins encoded by size (for shot frequency) and color (for Effective Field Goal Percentage) using shot coordinate data scraped off of ESPN--and my charts don't come out anywhere near as smooth and "trend-depicting" as his do. I've concluded that he must be smoothing the data so much that the result barely resembles reality. First of all, the frequency of shots near the basket so overwhelms that of shots anywhere else that the hexbins away from the basket end up being so minuscule that they're barely visible. So there must be some kind of frequency capping or logarithmic scaling somewhere in his charts. This is not the most egregious "lie" in his charts but it hides an interesting truth: 70% of shots are taken from 30% of the half-court (I'm making those numbers up but you get the idea.) Secondly, I found that a player's (or even a team's) eFG% varies so much from bin to bin that you rarely get smooth color patterns like the ones that show up in his charts. His charts show orangered hexbins close to the basket that somewhat evenly and predictably get lighter and yellower as distance from the basket increases. But in practice, this is nearly impossible. Each hexbin would have to span hundreds if not thousands of shots--much more than an entire season's worth of data for a single player--for a pattern like that to appear. To me, this is almost deceitful because it tells a "story" that isn't there. eFG% is much more "random" than his charts depict. A player might go 10/20 from one location and 5/30 from the one directly adjacent.

83 points by esalazar 12y ago

"Now, as new technologies start to generate terabytes of data about players and tactics, that next great competitive advantage will go to the number crunchers and analysts who can make sense of all those signals. Take the statistical tsunami of SportVU in the NBA. “It's not an exaggeration to say that 85 percent of the teams don't know what to do with this data,” Goldsberry says. “The idea that this is going to revolutionize the NBA—well, I'm not sure that's true unless teams awaken really quickly to things like machine learning and data visualization.""

Nimi 12y ago
Well, this sounds pretty much like an admission of the uselessness of his methods. Contrast this with Wins Produced (http://www.boxscoregeeks.com/faq http://www.boxscoregeeks.com/faq), a simple statistical model, and it's hard to see the point...

genofon 12y ago

I have worked with some NBA teams and they are already using software to track ball, players, referee, training, sleep, Heart Rate etc.. there is really nothing revolutionary in this article

confluence 12y ago
Looks like a bunch of heatmaps to me. Surprised no one did this earlier.
mountaineer 12y ago
Are you able to share any details of the software, devices and/or sensors they use? I've been kicking around ideas on how to bring these types of things to rec sports.
- genofon 12y ago
  software: depends on the team, device: most of them use stats http://www.stats.com/sportvu/sportvu.asp http://www.stats.com/sportvu/sportvu.asp to track games and various wearable technology (which is not allowed in games ) on training. They are not as far behind as media portrait them, all these tracking devices (sleep. HR, GPS..) have been around for a long time. You wouldn't believe the stuff they tried, there are some snakeoils salesman but they usually end up pretty badly. Also for software there is a lot of variance, I feel that they prefer people that know personally or have previous experience. There are a few people making the decision to adopt a platform for a team to track all the data floating around, usually few high managers of physio, that's your audience. Usually it's highly customized and there is a lot of support as the user (coach, physio stuff, athlete...) is not a tech person

bmoresbest55 12y ago

As a basketball player/sports fan and computer programmer/ tech enthusiasts, I love to see people post these types of articles.

swanson 12y ago
Do you read Grantland? If not, check it out - they have great stuff at the intersection of nerds + sports on a regular basis.
- cglee 12y ago
  My basketball knowledge increased 1000% after I started reading Bill Simmons & Zac Lowe.
- PKop 12y ago
  http://fivethirtyeight.com/sports/ http://fivethirtyeight.com/sports/ as well

danh1979 12y ago

A curious non-sequitor: "The data wasn't exactly private, but neither was it public—Goldsberry scraped it from the web." If Goldsberry scraped the data from the web, wasn't the data inherently public?

confluence 12y ago
I'm sure lawyers would have a field day answering your question.
pp19dd 12y ago
So this situation happens in the news world all the time. While a company or agency has original databases, excel sheets, what have you - they don't consider that publishing them in a "human-readable" format is nearly the same thing as publishing the raw data. Try calling the place for a copy, and they'll hang up on you. But, they won't think that a crafty outsider can probably reconstruct the original by scraping. What's particularly interesting here is guessing the motivation behind publishing. Was the information a trade secret, or did a middle-manager want to show that their team is ahead of the others? Or are these feathers to show the company has the know-how and capability? In either case, most of the web-published data isn't initially considered as published data by the publishers, who in turn don't think to state any restrictions governing the data. That's when we scrape and make use of it - and even if there are restrictions on republishing, you can still perform and claim transformative derivative work. The fun legalese part is what happens when they discover what you're doing and try to lash out, or interrupt a standing scrape. One time, all it took to unblock access was to show up at a meeting and get yelled at by a police captain for 30 minutes. Our retort started with "In the interest of public safety, ..."
- function_seven 12y ago
  > One time, all it took to unblock access was to show up at a meeting and get yelled at by a police captain for 30 minutes. Our retort started with "In the interest of public safety, ..." I'd like to hear more about your example.
  - 12y ago

the_cat_kittles 12y ago

"This Guy" publishes stuff regularly on Grantland, its not like he is an unknown

jimmytucson 12y ago

I've made the same types of charts--hexbins encoded by size (for shot frequency) and color (for Effective Field Goal Percentage) using shot coordinate data scraped off of ESPN--and my charts don't come out anywhere near as smooth and "trend-depicting" as his do. I've concluded that he must be smoothing the data so much that the result barely resembles reality. First of all, the frequency of shots near the basket so overwhelms that of shots anywhere else that the hexbins away from the basket end up being so minuscule that they're barely visible. So there must be some kind of frequency capping or logarithmic scaling somewhere in his charts. This is not the most egregious "lie" in his charts but it hides an interesting truth: 70% of shots are taken from 30% of the half-court (I'm making those numbers up but you get the idea.) Secondly, I found that a player's (or even a team's) eFG% varies so much from bin to bin that you rarely get smooth color patterns like the ones that show up in his charts. His charts show orangered hexbins close to the basket that somewhat evenly and predictably get lighter and yellower as distance from the basket increases. But in practice, this is nearly impossible. Each hexbin would have to span hundreds if not thousands of shots--much more than an entire season's worth of data for a single player--for a pattern like that to appear. To me, this is almost deceitful because it tells a "story" that isn't there. eFG% is much more "random" than his charts depict. A player might go 10/20 from one location and 5/30 from the one directly adjacent.