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How to Treat Your Team’s Data Fatigue

The data revolution in sports hasn’t just arrived. It has been here. By now, it practically has its own parking spot and VIP box at the arena. Almost 50 years have passed since Bill James coined the term “sabermetrics,” and we’re decades deep into organizations from every major professional sports league employing data analysts to study key measurables and develop new ones in order to reveal hidden truths.

This development was no Big Bang. The acceptance of data in sports has occurred over time, in fits and starts. Some of that can be attributed to the typical patterns of business and technological innovation. But just as important has been the buy-in of executives, managers, coaches and players. And although the modern athlete has gradually come around to trusting the value of data, fatigue can – and at some point likely will – set in.

Athletes are creatures of habit, and they are often guided by years of physical hard-wiring that becomes characterized as skill and instinct. Their confidence often borders on the irrational, which may, in fact, be a function of the drive and perceived self-determination that helped push them to peak athletic performance in the first place. Many have little use for concepts such as probabilities, and they may be actively repelled by the notion of their employer, for instance, using data to help the team hedge against their personal health. It’s a tight line to walk for all involved.

In that sense, any club that relies on data (which is to say all of them) also relies on an organization-wide culture that embraces this information. Data fatigue is bound to plague a team eventually. But when it does, how should it be managed? Start here:


Don’t try to talk around a data strategy or, worse, cut players out of the conversation altogether. Managers and coaches must be involved, for obvious reasons. But the players should also understand why data is important to the organization, and they’re more likely to be resentful of a process they’re already skeptical of if it’s treated like a front-office secret that’s deliberately kept from them.

Clear explanations

Part 2 of the transparency equation: The value of data and the information itself should be communicated to everyone in the organization in a language that can be easily understood. Athletes aren’t dumb, but they’re frequently no better equipped to crunch complex numbers than a mathemetician is trained to lace a corner kick between a keeper’s mitts and the top crossbar. Be clear and intentional with everyone in the organization about data and what the expectations are around it.

Make it actionable

Athletes respond to goals, and most have trained their entire lives to achieve by following a specific, detailed game plan. By helping players understand how data can reduce injury risk, improve performance and ultimately increase their longevity, earning power and viability in an ultra-competitive, zero-sum enterprise, a club is far more likely to receive their emotional investment in any data strategy.

Still it’s critical to continue to ask questions about your data. A sound data strategy relies upon the quality and accuracy of the data. The more accurate and actionable the data, the more likely your team is to buy into its validity. And that along will not only treat data fatigue but also could prevent it altogether.

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