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Wagner also tells the Leaders Performance Institute about the further inroads made by Sparta Science in US special ops (“that’s now our largest area”) and in the medical space, where its technology can be found in hospitals, clinics and surgeries across the globe. It is undoubtedly impressive but our focus this bright California morning is its roots in sport. “In 2008, we started as a training facility for college and pro athletes during their offseason,” Wagner continues. “Then after a few years, being based in Silicon Valley, it began to evolve into a full-blown technology business that continued to leverage the individual data here but also began to license that technology to sports organizations.”
That came in 2012 and in the ensuing period, Sparta Science’s network of partners has expanded to include a wealth of colleges and professional teams across some of the biggest sports in the world, including the NFL, English Premier League, and southern hemisphere rugby’s Super League. The organization has enabled almost 600,000 completed scans across all its verticals.
Taming the Wild West
Wagner, who has a background in strength & conditioning and who spent a period in the late 1990s playing rugby in New Zealand, firmly believes that Sparta Science’s roots in the sporting world better equip it is to tame the Wild West that makes sports tech such a volatile and mistrusted space. “Starting as a sports training facility is unique in this space and it means we’ve been very action and application-oriented from the beginning,” he continues.
“Everyone is aware by now that having data and having actionable data are two different things; sports science and data have grown disproportionately to the personnel that has been able to process it and, as a result, I think it’s been tough for the sports organization or the athlete to be able to fully understand what they’re looking for or what they’re trying to get out of it. We’ve been able to maintain this mindset of running a training facility, from our executive staff, software engineers, product managers and all the way down.”
The sports performance space represents by far their most challenging vertical, as Wagner says: “Nothing is harder than working in sport and part of the reason is the high transiency of staffs. We work with one team who have gone through five managers in two years; there is a risk that, all of a sudden, whatever nomenclature or language was developed with the team, you go back to square one.”
As a resident of Silicon Valley, Sparta Science has latched on to a term common in software development: agility. “Being agile in software means that individuals are capable of doing all things, which makes different inputs possible, allows for assimilation, and a cross-disciplinary outcome.” In practice, this means instilling good habits through providing diagnoses and prescriptions, with a view to assigning an athlete the right program and, in essence, making the data ‘theirs’. “You have to be really sticky in the sports vertical, so we force our product to be simple and really insightful for the end user – the athlete – because they are the ones who are least transient within a sports organization.
“The way we’ve gone about approach it is having a layered technology or product. So at the most superficial level, those who are less tech-savvy or less tech-interested can obtain good information; ‘this is where I’m at and this is where I was at before, great’. Whereas, sports scientists or data analysts can take that to a deeper level and say, ‘OK, I don’t want to know where I’m at with an overall number, I want to know my training stress balance and precise changes over this standard negation to the next.’ Having those layers enables one technology to be engaging for everybody.”
Accessibility has been key: “We have IOS, Android and web apps for mobile and desktop devices, which is stored in a secure cloud, with the exception of the Special Forces, who have an offline version. And one of my favorite philosophies, which is used out here in Silicon Valley, is that the best technology is invisible; ideally, it has a small footprint and it doesn’t disrupt the normal day to day of the organization. So if you walked into any of these organizations you may not even notice it beyond people checking their phones for their workouts or others doing jumps or balance screenings on a force plate. Perhaps you’d overhear coaches, trainers or physios explaining findings or changes to athletes and then making adjustments to the athlete’s training program.”
The value the company places on simplicity also inspired the Sparta Science name: “We had this idea that we were going to create a ‘Spartan’ product; a simplistic platform and solution that could analyze individuals’ risk potential quickly yet simply and, ultimately, provide the most time-efficient way to reduce that risk.”
Sparta Science is also engaged in a constant process of service and product improvement with its clients, whom they refer to as ‘partners’. “One of the things that’s helped us is that most of our team is made up of former athletes who understand that feedback is an opportunity to get better and there’s a saying in sports that you should only be worried when the coach doesn’t say anything to you. We have regular check-ins with our partners, whether that’s video or phone calls. We also happen to be in a location with a lot of nearby teams, so when other teams comes in and out of the area to play the local teams we’re able to host them face to face and maximize that facetime.”
Often, these teams will come to them with questions. “The biggest question is ‘How am I doing?’ and they want to know if they’re doing it better than the average pro team or if they’re doing worse or maybe even the same,” observes Wagner.
“There’s always that interest and that’s great because we want to tap into that competitiveness because it makes everybody better. The second major question we tend to get concerns outliers, because when we talk about data and prediction, because the space is so new, most people assume, whether it’s injury or performance, are guaranteed – and that’s not the case. Those conversations will revolve around statistics, which helps us improve our models further. There are no guarantees and it’s about explaining to them the science side of things so we can improve our systems to reduce negative outcomes.
“Whenever we get feedback the immediate step is deciding the order of priority in the strategy of the business; there will be discussions with department heads, whether it’s engineering, customer or sales-related. We’ll find the priority that needs to be addressed and ask ourselves if it’s something that we need to be aware of in a year or if it’s something we need to address immediately and delay some other priorities.”
It is a constant process of evolution and Wagner feels that some of the most significant trends may develop away from the lab, as he explains: “Individuals and athlete unions are starting to come forward to ask who owns all this data. The UK is a little ahead in this regard, as wearable data is classed as medical data. The ethical discussion around who owns that information will be a big issue and we’re of the belief that most of the data we collect and provide is medical data, so the individual owns it, not the sports organization or Sparta. In cases where unions are involved in the banning or wearables or the gathering of data, I think that comes from athletes who are not being educated on what’s being gathered and, as a result, we have a natural inclination to be fearful of what we don’t know.”
There is also an opportunity here: “We have to make sure that the technology we provide speaks to the organization but also speaks to the end-user: the athlete. Once that’s occurring, for the individual to get pure data and to optimize their engagement, the individual has to want to be involved; and so they have to understand how this is going to help them. It’s making sure that the technology is energizing and engaging in a way that helps the athlete to be consistent. Part of that consistency comes from optimizing the user interface but, interestingly, we believe that a lot of that is rooted in science because if a product or data is unreliable, then the individual is going to lose trust in that data. If you can cheat the data then you’re less likely to be consistent and interact with it; the best program for any individual is something that they do consistently and the foundation of that consistency is having the right purpose and a trust in that purpose to ultimately to deliver the results.”
We have to make sure that the technology we provide speaks to the organization but also speaks to the end-user: the athlete.
Dr Phil Wagner
In terms of trends, Wagner also feels that we will begin to witness increased quality control. “The other thing that’s going to change is an increased medical and scientific rigor behind a lot of these companies and the claims that are being made; either that’s going to happen formally by federations or agencies requiring it or it’s going to happen informally with the ones selling snake oil just going out of business. Those are all good things and I don’t think there’s going to be a new technology that’s going to revolutionize things. I think it’s more a cleaning up or refining of the current stage.”
To conclude, we touch upon Sparta Science’s hopes for the future. Wagner says: “Unlike a lot of sports tech companies we’re not only in sports; this allows us to take our time because we’re getting revenues from other areas such as medical and the military, which allows us to help the industry as a whole.
“Where we’re heading is making our insights more accurate. Right now, at a typical sports organization, we can predict about 18% of all injuries that occur – that’s a saving of about $12 million for a US pro team a year. As we gain more data, that allows us to have more branch points in the decision tree. If you take hamstring injuries in soccer, if we’re getting more data, assessing more athletes of, say, different ages and ethnicities, that sort of data science is going to allow an increased percentage in the accuracy of the prediction.”