Chasing Perfection: A Behind-the-Scenes Look at the High-Stakes Game of Creating an NBA Champion (15 page)

This kind of off-court movement training has become an increasingly large part of what is an increasingly sophisticated data puzzle for NBA teams, with the so-called Holy Grail of athlete injury prevention and performance improvement expertly connecting in-game tracking data, practice tracking data, and so-called off-site biometric data culled from tracking sleep, monitoring diets, and taking
periodic bloodwork to check players’ vital levels. Unfortunately, all of this data continues to come from disparate sources, with different levels of exactness, and all of it is complicated by the National Basketball Players Association (NBPA)’s collective bargaining agreement with the league, which prevents certain current measures, while others—namely, possible invasions of privacy like blood samples—will be a major talking point for the next agreement that could come as early as 2017 should either the owners or players opt out of the existing deal. That seems likely in light of the new $2.6 billion national TV contract the league struck late in 2014, which creates a huge new pot of money for the franchises and players to haggle over.

The current agreement allows players to wear biometric tracking devices that keep constant track of players’ vital signs and workloads in practices, but not in games. According to a
CBSSports.com
column by Ken Berger during the 2015 NBA Finals, twelve NBA teams used
Catapult devices during the 2014–15 season. They included the usual analytics suspects like the Dallas Mavericks, Golden State Warriors, Houston Rockets, Philadelphia 76ers, and Toronto Raptors, as well as the Memphis Grizzlies, New York Knicks, Orlando Magic, Sacramento Kings, and San Antonio Spurs. Zephyr Technology Corporation is a competing firm that makes wearable harnesses that monitor things like core temperature, heart rate, and other body data. Zephyr clients include the Phoenix Suns, the Oklahoma City Thunder, and (of course) the Houston Rockets.

Because of the limitation of such devices to practice, though, in-game data has to come from the three-dimensional player tracking provided by SportVU, which is still a fairly rough interpretive cut of player workload. An additional issue with the value of practice data is that NBA team schedules are very compact, so teams tend to practice less and less as the season wears on. If they do practice at all, the effort levels in those sessions usually are well below the standards needed in games, so even if the players are being monitored, there is a question as to the value of the data being collected. Getting
data established at the beginning of a season, when players are going harder in practice, is valuable—especially as a baseline if a player is injured and you need to gauge their recovery—but in-season data can start to lose value pretty quickly in terms of real-time monitoring of player loads.

All this said, bargaining issues will work themselves out. In Berger’s column, NBPA executive director Michele Roberts said, “To the extent that the team and the player could come up with a better advantage based on the information, who’s got a problem with that?” The technologies also will continue to improve, and there will be a huge amount of value (and money) for the teams (and companies) that figure out the best ways to tie all of this data together into a comprehensive monitoring plan for players.

A key figure in all of this is Kopp, who built up SportVU before joining Catapult in 2013. Early in his tenure at STATS, he hired Paul Robbins as the company’s director of elite performance. According to Kopp, it was Robbins who came to him early on during the SportVU experiment and convinced him that SportVU’s on-court data would be the primary source of load-measuring during games, and that that feature would be a big selling point to potential clients.

“What he basically told me was, ‘I do all of the stuff in training,’—so kind of like P3 and Marcus Elliott. You mentioned those guys, they do amazing work in a lab,” Kopp said. “And there’s other things, like Catapult and others that you can do in practice, but the missing piece was anything in games. You do all the stuff in labs, you do all the stuff in practice, [then] you go to a game, and there’s nothing. So he convinced me this could be the game part of that equation, but as part of that, not only do we want to create things like speed and distance, but being able to approximate player load using x, y data. [That] isn’t true player load, but in a sense, the way we sold it was, ‘Well, currently there’s nothing. It’s better than nothing,’ which isn’t the best sales pitch, but it worked there for a while.”

Kopp understands the current critiques about the usefulness of Catapult’s data. He hopes the players’ union will relent in the next series of labor negotiations because, unlike sleep monitoring devices and blood samples, Kopp reiterates that Catapult devices are to be used “in a workplace setting.” He then used an example from a sports league in Catapult’s home country to make a point that significant advancements could come to the NBA once the devices are approved for game use.

“The best example we have—it’s really the only example in the world that you can point to—is what happens in Australia with Aussie Rules football,” Kopp said. “They use these devices in games . . . on the sidelines, and they actually—it’s kind of like hockey with its dynamic substitutions—they make substitution patterns based on what they see in the data. And they use it in practice in terms of monitoring guys and how hard they push.

“And they also use it in the Combine for guys that are coming up through the system, and what they found is, it’s actually eliminated injuries in the Combine—because they used to have all these injury problems with guys coming to the Combine and pushing themselves too hard and they get hurt.

“It eliminated those injuries and they use it in a way to create that baseline for players. And it’s all viewed as a positive. It’s not viewed as a negative. It’s not viewed as something where we’re going to make a decision based on, ‘Oh, hey, you’re not trying hard enough.’ The fact of that matter is, can you use it to say someone’s not trying hard enough? I guess, but is that a bad thing?”

In the interim, SportVU data remains the most useful on-court load tracking data available, and Robbins is a key figure in its interpretation. As of early 2015, he said he was working as a consultant to seventeen different NBA teams to help them review performance data to aid their maintenance programs. According to Robbins, five NBA teams were already working with a Canadian company called
Kinduct, which provides a technology platform designed to tie all of these different data sources together, but the quantity and preciseness of data simply isn’t there yet to properly piece everything together.

Robbins, who comes from an exercise science background and was a strength coach for many years, works directly with the strength coaches and trainers for the teams that engage STATS for this service, which is an interesting intersection with the on-court analytic data provided by SportVU. He provides weekly reports to his clients that help them consider issues regarding their players’ physical workloads.

“I will start by giving some predictions on basically what kind of workload a player might have this upcoming week, and that’s based off of how did that guy play against whom he’s matched up coming up this week, so [at first] I’m using last year’s data just to give me a feel of what a player might be going through,” Robbins said. “Later in the season, I’ll be able to use more of this year’s data, obviously, in comparing players.

“So I’m looking at predictions. What happens to a player, who’s covering Kobe Bryant, how much load is that player getting, what does Kobe typically do to a player? And I’ll do that for all the teams, and basically the top five, six players on the teams. So I’ll give them prediction of the load—that’s the first thing I’ll do for everybody in the week.

“And the second thing, I’ll review last week or the trends that are going on in players right now. If it looks like their intensities are dropping—it could be because of fatigue, a minor injury, it could be just the matchup he’s playing against—I will highlight anything I think is interesting to look into.

“And again, somebody could come back and say, ‘Oh, it’s just a matchup, no big deal,’ or, ‘we blew those guys out by twenty points, it really doesn’t mean anything,’ but what I’m really trying to do when I send out these reports and I’ll go through each player, and anyone
I’m concerned with, it’s to engage the strength coaches and the athletic trainers, and if there’s something that they’re like, ‘Well, I’m not sure why the intensity’s dropped in this guy. Paul, can you go and look deeper?’ And that’s when I go into the data. So what I’m trying to do is bring up red flags and question them, ‘What do you need me to look into?’”

In 2015, Robbins estimates that SportVU’s on-court cameras are only providing him with maybe 30 to 40 percent of the data he would ideally need to track player loads. He assumes at some point, the league will allow on-court tracking monitors during games, which will close that data gap. Until then, there’s no issue with him providing consulting advice to more than half of the league, because Robbins says there’s a surprising amount of information sharing going on between training staffs at the team level. A lot of new team trainers and strength coaches are coming from the same placement sources, and a good number of them know each other. According to Robbins, there were two teams in the league that absolutely will not share data or any findings or techniques with other teams, but he guesses that as many as two-thirds of the strength coaches in the league are friendly enough to trade some basic tips.

While advancements continue to be made across the board, the ability to truly know what the game-to-game loads are for players, and to track those trends against the off-court training, diet, and sleep data, would lift this discipline to an entirely new level.

“The whole thing is managing loads for a player,” Robbins said. “Just make up some numbers here, but a player may have a load of ‘5,000’ in a week. That’s what he could do. I’ve got to manage that load. Is 3,000 of that load coming from games? Well, that means he only has 2,000 on all the other things going on. Now can they get some points back if they sleep well? Can they lose more points if they don’t sleep well? And the same thing with eating. They eat poorly, maybe it’s not 5,000, now it’s only 4,500. So I can manage that. And then the players start understanding the big picture.

“So that’s where we’re really going. And then that will then help start connecting that with injuries because there’s a lot of injuries due to overuse. And that’s the load—if you have too high of a load, then that’s overuse, and there’s going to be injuries. So if I can manage those injuries . . . There’s other injuries that I’ll never be able to manage, but if I can manage overuse injuries? That’s the ultimate goal. But we’re nowhere near that yet.”

Nine months later, back in Santa Barbara, P3’s business is booming. Just during the summer of 2015 alone, Elliott estimates that they did one hundred new or continuing assessments of NBA players. The company’s Twitter feed periodically posts photos of the players who do training there, and the 2015 batch included Detroit Pistons center Andre Drummond, Memphis Grizzlies wing defensive specialist Tony Allen, Charlotte Hornets big man Al Jefferson, Chicago Bulls center Joakim Noah, Atlanta Hawks center Al Horford, and many other well-known NBA veterans. The company also did a lot of pre-draft work for incoming rookies, with players like Jahlil Okafor (the No. 3 overall pick to the Philadelphia 76ers) and Emmanuel Mudiay (No. 7 to the Denver Nuggets) also training there.

Word of mouth clearly is driving the expansion of P3’s business, but it’s not specious to also draw a connection between the burgeoning client list and the testing the company did at the 2014 NBA Draft Combine. After P3’s technicians analyzed the results of that testing, the company provided the NBA with a list of fifty-eight to sixty players in order of their likelihood of getting seriously injured. Then the 2014–15 season unfolded, and as noted earlier, a huge number of high-profile rookies suffered serious injuries. Like Mike Clark, Elliott is not at liberty to divulge exactly what risks were assigned to which players, but he did say, “We didn’t just say who was likely to be injured, but we said
where
they would be injured. And it ended up being very predictive.”

The accuracy of scale and specificity of injury really spooked the NBA, which ran the 2014 exercise as a closed test, but invited Elliott and Clark back to the 2015 Combine, where Elliott says P3 examined all but about four or five of the attendees, even though they were an opt-in process and not required. And the NBA subsequently changed its stance about allowing P3 to share its prognosis projections with the players.

“This is going to be a great project with the NBA,” Elliott said about his company’s now-annual involvement at the Combine. “There is going to be so much value that comes out of this. This is the first time a league has taken something like this on. We collect thousands of data points on each one of these guys, and we make predictions about them, and then we get to see what happens.”

This new disclosure created a much bigger talking point than the actual test results, though, which relates back to the collective bargaining agreement and the players’ union’s stance on biometric data: Who owns the data that companies like P3 are collecting?