In sports, data is the new frontier. In addition to the sort of Moneyball-style statistical numbers-crunching and mining of game microtrends that goes on in modern front offices, clubs are employing sophisticated performance-tracking technology to unlock new insights that simply hadn’t been available to them in the past. As that tech continues to grow more accurate and dynamic, the more useful it figures to become – not only to practitioners in training rooms and to coaches at their whiteboards but also to scouts and executives in their roles as talent evaluators.
And just as rich, reliable data can reveal tiny, imperceptible-to-the-eye changes or imbalances in an athlete that might signal significant developments (athletic improvement or an injury risk, for examples), it can also uncover nuanced but important athletic differences between players that help clubs place proper value on their own talent and inform their decisions about athletes outside their organizations.
But in the data arms race, some parties – through no fault or merit of their own – may be in a better position than others to take advantage of the latest technology. That those lines seem to be drawn fairly clearly by international borders is more happenstance than political, but they’re the reason that the United States is more likely, at least in the short term, to take the lead on data-driven scouting ahead of Europe.
Shrinking the Scouting Problem in the U.S.
In the U.S., professional sports organizations such as the National Football League, Major League Baseball and the National Hockey League primarily scout players from a relatively small, concentrated talent pool. Top-performing athletes are typically drafted from well-known universities and programs that are often meticulously covered by analysts and equipped with technology similar (if not identical) to that used by the professional organizations themselves. Implementing data-driven scouting in these leagues, then, has the potential to be a fairly comprehensive and seamless process, as most prospects are known quantities with existing baseline data profiles.
In the NFL, for example, 372 players listed on active rosters in 2023 came from the NCAA’s Southeastern Conference (SEC). That amounts to 21.9 percent of the league – more than 1 out of every 5 active players. Additionally, according to the NCAA, 57.7 percent of the league’s players come from the SEC, Big Ten and ACC. A full 86.6 percent of players on NFL active rosters were drafted out of schools aligned with the NCAA Division I Football Bowl Subdivision – a total of only 134 programs. And because many of the major American college football programs compete for talent in part based on how effectively they produce professional players, many of these programs are incentivized to use scouting and player-tracking tech similar to that found in the NFL. Suddenly. the potential vastness of the data problem appears far more manageable.
European Sports’ Sprawling Talent Pool
On the other side of the pond, Europe’s most prominent professional sport is another brand of football – soccer. And because it’s a global game, and because soccer talent is and can be found in practically every corner of the Earth, the player scouting mission becomes a sprawling and complex one. Moreover, the search for athletes happens in a much larger and more diverse talent pool, spanning perhaps thousands of academies worldwide. Many of these organizations lack the infrastructure for advanced scouting technology, which then requires a lot of guesswork or investment from a European club hoping to evaluate how a player or players might fit into its club and league.
Ironically, the best way to highlight the data-driven-scouting divide between the U.S. and Europe may be to examine the area of greatest overlap: basketball. In both the NBA and FIBA, in which one player can have a far greater impact than in, say, football or soccer, clubs and the leagues themselves scour the globe for generational talent. As the U.S. college game has lost luster over the years and the world has begun to catch up to the Americans on the court, we’ve seen more of basketball’s greatest talents arrive from less conventional origins – including Greece (Giannis Antetokounmpo, by way of Nigeria), Serbia (Nikola Jokic), Luka Doncic (Slovenia) and France (Victor Wembanyama). This effect isn’t limited only to the top talent tier. The two best basketball leagues in the world now go fishing in the same gargantuan global talent pool.
The issue, of course, has nothing to do with the location of the league or the nature of the sport itself. It simply comes down to where and whether the talent is concentrated in such a way that reduces the current challenges of data-driven scouting. Even the billion-dollar industry of sports has a reach that spans only so far. Although data-driven scouting has the power to theoretically uncover hidden talent in soccer, cricket, rugby and other European-centric sports, it will, at least for the time being, be most useful to leagues in America with smaller and more easily examined talent pools.
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