Darren Montgomery, COO at Svexa: “There was obviously a huge gap between data and actionable insight”

In our wide-ranging interview with Darren Montgomery, COO at Svexa, one section stood out: how to turn the immense amount of data we all now have access into from a confusing torrent into actionable insights.

“Whether they are individual elite athletes, coaches, professional teams or everyday recreational players,” Darren said, “any one of us can simply strap on a watch or wear a ring and install an app to be presented with myriad different metrics, charts, thresholds etc. It can be overwhelming to try and figure out – where should I look, what is most important for me, and what should I change in my training to improve my performance?”

And it’s not just one product generating data. We all use different hardware, so how do you bring all this data together?

It’s a problem Darren was fully aware of, being a competitive cyclist, rower and XC skier. You can imagine how much data such a trio of exercises would generate. So, how to solve the problem?

This is where Svexa aims to help, and as the COO Darren helps guide not only marketing but product development. Something he has plenty of experience in, having spent a decade leading global marketing campaigns at Electronic Arts. And he has his own academic data to back this up, holding an MEng from Cambridge University and an MBA from UC Berkeley.

From the elevator pitch for what Svexa does to its technical details (such as generating a digital twin for athletes), this interview not only paints a picture of how to make diverse sources of data work together for athletes but for any technology sector.

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Tell us your elevator pitch

Svexa is a human performance intelligence company combining expertise in physiology, precision health and data science with a deep understanding of technology, molecular profiling and practical sports performance.

Our founders are world leaders in physiological science, complemented with decades of experience coaching elite international athletes. We use proven science to unlock human potential by providing hyper-personalised, actionable insights.

Unique in the space, we combine all available training and recovery data to power our proprietary algorithms. These first build truly individualised profiles based on training response, biomarkers, sleep, subjective ratings and psychology for each participant. Then deliver clear, actionable insights for readiness and training, enabling streamlined day-to-day decision-making.

Svexa is primarily B2B, serving customers ranging from sports technology and professional teams to the military, corporate health or general population wellness. In all of these situations, end users have potential that is hidden behind mental and physical barriers that can be removed with optimised data and practical solutions. We enable our clients to make their B2C products and apps more sticky, with true personalisation and adaptivity.

Our primary offering is algorithm licensing – plug-and-play into your existing technology. We also offer white-labelled software and consulting to help clients new to the use of human performance data.

What is it about sports tech that excites you? What made you get into this sector?

My background is in software, video games in particular. Over my years in that field, I was part of a dramatic shift to the use of data in every facet of the business. Sales planning and operations became deeply data-driven, from pre-launch manufacturing planning to shelf space allocation. In my role as a marketing leader we transitioned from a traditional creative business with huge TV ad spends to a much more precise, defined, online world where we could track the impact of every dollar and target ever more narrow segments of our audience.

Our products themselves generated increasing volumes of data telemetry, that we could use to better understand exactly how, where and why our customers engaged or disengaged with our products. As an avid amateur athlete, over the last decade, I watched the explosion of devices to enable data gathering.

However, as an individual it was far too easy to simply drown in all the available data with no real clue what to do with it – there was obviously a huge gap between data and actionable insight. That’s why I saw a huge opportunity in Svexa, combining deep sports domain expertise with AI and ML techniques to deliver those insights.

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Can you give an example of a complex problem in sports that you – or your company – have been involved in tackling with technology?

As I mentioned above, the broad challenge for everyone involved in sports is what to do with all the data they gather. Whether they are individual elite athletes, coaches, professional teams or everyday recreational players, any one of us can simply strap on a watch or wear a ring and install an app to be presented with myriad different metrics, charts, thresholds etc. It can be overwhelming to try and figure out – where should I look, what is most important for me, and what should I change in my training to improve my performance?

Up until now, typically each of the hardware providers will offer their interpretation of the data from their device, and they may offer recommendations for training or injury prevention and so on.

However, the two big things they are failing to do is 1) combine all available data sources for the individual, to provide a single holistic picture, and 2) deliver truly hyper-personalised insights based on that holistic picture.

Svexa aims to do exactly this – we are agnostic to the source of data, the first step in our data pipeline is to integrate all available sources and harmonise them by recalculating fundamental metrics like load from the raw underlying data capture.

With that powerful combined data set in place, we can build a digital twin of the individual that identifies, from all the thousands of possibilities, which are the specific metrics or correlations that best determine how that individual will perform or recover.

We can then simulate thousands of possible regimes to determine precisely what is best for them. Slightly different applications of our algorithms can flag when injury or overtraining is likely, or predict the outcome of upcoming milestone events, for example, we have predicted elite athlete results in major tournaments in several sports with an error of less than 0.5%.

Do you consider esports as part of your remit? If so, why?

Yes, absolutely. The principles that underpin Svexa can be applied to any field of human performance. While our work began in the world of professional team sports, we have expanded first to individual elite sports, then on to recreational sports, and have worked with clients with a focus on mental health. We work not just in general physical or mental performance, but also in skill acquisition in sports such as baseball.

When it comes to esports, we would take exactly the same steps as for any other performance goal, in other words gather all available data pertaining to the performance – what does their training look like, how many sessions for how long with what results? How do they perform in competition? What tangential metrics can we capture like subjective measures of mood, sleep, diet or physical measures like heart rate?

With these jigsaw pieces, we can build the same profile of how each ‘athlete’ reacts to their training stimuli, and what metrics are the best indicators of their future performance. We can help them tailor the optimal training plan as they work towards key events, and suggest related tweaks to their lifestyle. All hyper-personalised based on their unique data set, as each individual could be quite different.

We have actually discussed the potential of using our technology to power training recommendations for professional esports teams, though none of these have quite come to fruition yet.

Related: Anders Tånger, CEO of Photon Sports: “What fascinates us the most is when technology goes unnoticed”

Thinking of injury prevention and/or recovery, what are some technology and/or science developments you’ve found particularly fascinating?

At Svexa I’m fortunate to work alongside some of the leading scientists in the field of human performance, genomics and physiology. Our team are continually running lab-based research projects with elite athletes. In recent years these have allowed us to develop algorithms ranging from the detection of overtraining to identification of muscle fibre type to effectiveness of adaptive training.

Our Athlete Passport technology is a particularly effective advancement in the field of individualised training, and it also enables injury avoidance. As a fundamental component in Svexa’s wider product portfolio, Passport brings together all available data sources to build an integrated ‘digital twin’ picture of the individual.

For example, in work with top-tier professional soccer teams, we bring together GPS training and match data with daily subjective responses on mood, sleep etc, biological markers, glucose monitoring and strength testing. Our AI engine is informed by our team’s deep domain expertise and runs a wide range of potential correlations to identify which metrics or relationships are most predictive in terms of the individual’s performance.  Given its wide scope, Athlete Passport may also recommend alterations to each individual’s lifestyle in terms of diet, sleep and so on.

We were also able to incorporate injury history and demonstrate in a retrospective analysis that our algorithms would have correctly identified 75% of injuries in advance. The key finding is that our predictions got exponentially more accurate and effective through the combination of multiple data sources, rather than simply relying on one as many competitive offerings may do. 

What do you believe is the biggest opportunity in sports tech right now?

In general terms, the enormous opportunity in sports tech is to shift from the current paradigm of collecting and displaying data to delivering individualized, actionable insights. There is an ever-increasing range of great wearable devices, with expanding capabilities. These can potentially collect hundreds of metrics thousands of times a day. The manufacturers often have developed companion apps that nicely present this data, in a wide range of charts and stats.

However, their focus is mostly on presenting the data. It’s still incredibly difficult for an individual to fully understand what all the data means, even more where they should look and what it means specifically for them.

In addition, most existing products and apps are applying generic formulae or tables to generate training plans or recommendations, at best segmenting along broad demographic lines. They may offer ‘insights’ like heart rate zones, but again these apply standard formulae rather than being truly individualised.

To the extent that they deploy AI, it is often based on pure big data analysis rather than true domain knowledge in human performance. There is a huge opportunity to take this whole process to the next level by integrating sources and delivering true hyper-personalisation. Companies that can take that next step will be able to make their products much more satisfying, engaging and sticky for the end users.