top of page

In their own words: Players speak about the benefits of using personalized data

Data analytics is not just a huge part of football now. It’s everywhere. The original Moneyball was for baseball, but if there is a sport, there is a database for it, and analysts working on it. There are vast troves of information for every analysis of any sport: Football has Fbref, baseball has baseball-reference, League of Legends (that most noble sport) has, and the data revolution seems to be here already.

We’ve interviewed analysts and coaches, but we want the players’ input

Players eventually becoming end-users of analytics is a topic that we’ve discussed a lot on our blog. We interviewed analysts and coaches, who outlined the multiple benefits personalized data and videos can bring to players (and their families). Not just professional footballers from elite clubs but also youth wannabe pros and even amateurs. We have left a crucial group out of the conversation, though: the players themselves. This is why we collected a few interviews from different sports and found the advantages players said they got from data.

Steph Curry, image by Cyrus Saatasz

Basketball data helped find advantages players couldn’t

Steph Curry is one of the greatest point guards of all time, a legendary basketball player whose name is going to be around for a very long time. He started his own biometrics company in 2016, and among other stats found out exactly how quickly he released shots off his dribble. In a Business Insider interview, he said, “to know how fast it actually happens gives me a little leg up, I think.”

He added, later in the interview, that “knowing just how far we run during games, how much we change direction, things like that, it allows your practice, workouts, and routines to become smarter, more catered to what you actually do on the floor during games, as opposed to going blindly into it, which I think gives us a leg up on the competition”. Adding data to his play, when he was already great in 2016, was an advantage.

Shane Battier was more specific, and recounted a story for BigThink about how he was facing “a guy, Kobe Bryant”, and couldn’t get anything more than what “any Joe Schmo fan could tell you”. However, “after studying and going through the school of analytics”, he figured out how to counter Kobe Bryant, so that “I’m actually making him detrimental to his team”. Shane Battier used opposition research to figure out how to counter one of the strongest players in the world.

MLB Umpires, image by Justin P. Morelli

Baseball has changed

Baseball, to an extent, is where data analytics have found roots. One reason for that is the speed of the game, which by its nature includes a lot of breaks and individual moments that can more easily be calculated. With this headstart, they’ve been a very advanced field, analytically speaking. This new approach to data led Trevor Bauer to say “I’m not that strong. I’m not that fast. I’m not explosive. I can’t jump. I was made”.

Effectively, data in baseball is not limited to the Moneyball method of finding players with stats that go undervalued. It’s also about developing the talent players do have and creating the next legendary players. It is similar to how the basketball players used data, but instead of elite players making themselves better, this was an open-minded player acknowledging his flaws and using data to turn himself into a champion.

Steph Houghton, image by "EL Loko"

And the football players?

A different Steph, Steph Houghton, England, and Manchester City captain, discussed her usage of GPS-based tracking data in an interview with the Telegraph. She said, “when I first started playing, the thought of being able to track how much distance you’d run in a training session was never there, you would just judge it on ‘how you felt’ afterward or if your muscles were sore, so things have come on leaps and bounds … Knowing exactly what I’ve done in a session, it’s really developed me as a player over the past few years especially”. She found a great benefit in data, and the interview itself has much more about how she used that data.

We’ve mentioned Frenkie De Jong in previous articles, but he fits here as well, being one of the best examples of players getting data and using it to their benefit. On FCB’s official website, he said that “Finding out my numbers made me feel more confident. People said I was too slow but the data said otherwise and I drew confidence from that”. Data helped him, and not just in the transfer market.

An overview of performance analysis data now available to players at any level

So what’s next?

Football data analytics is here. It’s available, and not just to the Steph Currys and Frenkie De Jongs of sports. The sub-elite can access this data as well as the elite can if they just pay attention to the market, and the possibilities. Fully-automated analytics solutions that provide accurate tracking data to all league levels (like the one we at Track160 developed) are one example, but the market itself is growing, and options are out there for any player who wants results for themselves.

When Billie Beane, the poster boy of the Moneyball revolution, was asked about the use of analytics in sports, he said: “It’s like watching a card‑counter in Vegas playing blackjack. Once you have learned how to count cards, why would you ever go back to doing it on a hunch?”. Sooner or later, every aspiring football player will be asking the same question.


bottom of page