It was a very rough start to the season for the Seattle Sounders. The club got of to their worst start in their five year MLS history, earning only one point from the first twelve available before rallying to a 6-5-3 record through last weekend. There were many reasons for the the rough start, but perhaps the biggest one was the lack of a consistent lineup due to national team duty, late arrivals, and injuries. Professional clubs have no control over who gets called up to the national team, and while they can control which players they sign to a contract and thus which players are available to them they are high unlikely to pass on a wanted player simply because he may arrive a few weeks after the season starts. Absence due to injury is usually seen as a combination of preparation, training, and luck, but the high prices of today’s professional athletes are making injury analytics one of the hot fields within sports. MLS players may be one of the lower paid professional sports athletes in the United States, but that isn’t stopping clubs like the Sounders from trying to leverage data to prevent injuries. The availability of a key player within a league built upon parity almost demands such a focus.
The Sounders are have invested in sports science from day one with the goal of minimizing playing time lost due to injury. Lead fitness coach David Tenney has been with the team since its founding in 2009, coming to the side with prior experience in similar roles at George Mason University and the then Kansas City Wizards. Tenney has been integral to executing General Manager Adrian Hanauer’s and Head Coach Sigi Schmid’s vision for how fitness data should integrate into the wider organization. Tenney described how these two men’s vision permeates the way the Sounders use data:
"Being the business person and leader that he is, and being extremely into data, [Adrian Hanauer] wants to be at the forefront at what people are doing with technology and analytics. I think being in the environment we’re in with Seattle, this is an aspect of the club he really wants to drive. Having said that, we’ve found that Sigi is not intimidated by numbers. That’s important. As we use various pieces of the puzzle like Omega Wave technology that look at fatigue post-game, that was a Sigi decision to drive that. He saw the technology, he was in the presentation, he talked to … Chelsea about it. He wanted it. I think that’s extremely important. You’ve seen Sigi give interviews and be able to talk about Omega Wave, and how some of his decisions have been driven in part by Omega Wave data."
Central to the process of sports science within soccer is the ability to measure the load on the players and their response to it. FIFA bans these types of measurements during a match, so the only thing that can be measured directly in a match is positional data from sources like Opta, Prozone, or Match Analysis. This means teams must build models that infer how a player might respond within a match based upon direct biometric readings taken in between matches. Tenney described how a typical data capture and analysis cycle transpires.
"One of the relatively unique things about soccer is that the match is by far the heaviest load or outlay for that particular week… You can use questionnaires and other things, but Omega Wave becomes a critical piece when you really need to quantify each individual’s response to that very heavy load… The day after the game, the players will do the Omega Wave test with a set of five electrodes and a full EKG, some heart rate readings, and we get a pretty good sense just based on that sort of data for a player. For example, with Osvaldo Alonso we have probably close to 150 data points on him post-game, so we know and we have a pretty good sense by now of where he’s at in terms of fatigue relative to his baseline fitness levels.
So now we as a coaching staff need to go in and develop that week’s training based upon where the team is. With the GPS and heart rate stuff we can get a pretty good sense of which exercises and what types of training will hit certain training loads over the week. Ultimately, it’s Sigi’s decision to choose what types of exercises he wants to do, what tactical things he wants to work on. This data is more just about guidelines of how hard we should train, how long the session should be, what intensity should it be at. The GPS and heart rate data really help us quantify what that load factor is throughout the week.”
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