When I was around six years old, my dad decided it was time that I took the trip across London to Stamford Bridge on a Saturday for my first home Chelsea game - the match ended tied at 1-1, a hard-fought draw with Everton. My favorite player at the time, Dennis Wise, scored Chelsea's only goal of the game and I can remember the celebration after he slotted it home with uncharacteristic coolness. I was happy enough despite the result; I'd gotten to see my hero score at a ground I'd only ever seen on television.
Fast forward nearly 20 years and watching soccer is a very different experience. I understand (to a degree) what is happening on the pitch, I have an active interest in the stats, and I'm as jaded as any fan that's seen their team win and lose on a cycle for two decades would be. The childlike wonder isn't entirely gone, but we take a far more analytical approach when watching games. If a player's pass completion rate goes down, or they're not covering as much ground as they should be, that's a topic of conversation in of itself.
It's gotten this way for a number of reasons. Firstly, broadcasters have jumped headfirst into the world of data because it gives pundits something concrete to discuss, rather than having them vaguely talk about the game or argue whether or not a refereeing decision was correct. Secondly, fans have always wanted as much technical knowledge as possible about the sports they love, both so that they can understand what's happening on the field and so that they have ammunition in discussions. Perhaps more importantly, though, is how integral data has become to the running of sports clubs themselves. If basketball teams are heavily using analytics to evaluate player performance, it is only natural that this focus will bleed into basketball broadcasting and news reporting.
The same can be said for any sport. Data analytics has made a significant footprint on every major sport to some degree, and it's now the accepted wisdom that analytics is no longer an optional extra, rather it is vital to keeping up with the competition. Sports analytics has, ultimately, been a huge positive for the industry. When the difference between success and failure is often razor thin, proper analysis of the data can give teams the edge. It's used to prevent potentially career-inhibiting injuries, squeeze the best out of emerging talent, and form new ways of playing sports altogether.
Better understanding a sport does make watching it a more enjoyable experience. The problem comes when the numbers take precedence over the unquantifiable magic of a player's talent or that of a particular passage of play. The conversation - both among pundits and groups of friends - often turns from how incredible a Lionel Messi performance was, for example, to his shot accuracy percentage over the last few seasons. When pundits discuss the 'expected goals' figure Messi contributed in Barcelona's games, something is lost. When they wax lyrical about the impact he has on games or how he dazzles defenders and seems to make the ball stick to his feet, on the other hand, this can inspire fans. Both are interesting, but the latter is emotive - just as sports spectatorship ought to be.
Analytics also inherently encourages sportsmen to play more conservatively. Again taking soccer as an example, the simple fact that every pass a player makes is logged, as either successful or unsuccessful, means that players will be less willing to take risks with their distribution. When risk is mitigated in a sports game, the odds of seeing something spectacular get longer. Placing athletes under the microscope is in many ways non-conducive with the moments of wonder that makes some sports so popular. This is not to say that coaches wouldn't have picked up on an overzealous performance in the past, but that it has never been as immediately obvious as it is today. Coaches and players will tell you that this has little to no bearing on their style of play, but even the most self-assured athletes will have one eye on their personal statistics at all times, and there is less of a case for risky or expressive play in this environment.
The use of data among broadcasters also often puts excessive emphasis on individual performance rather than team performance or tactical nous. Focusing on an athlete's distance covered over the course of a game is interesting and can be worthy of conversation, but the fact is that this conversation often comes at the expense of, say, a discussion about a tactical shift put in place by management. The bigger picture can inform and explain changes in player performance, and the focus on individual statistics can push it the back of broadcasters' agendas.
Ultimately, you'd argue that analytics has had a positive impact on the world of sports. We're seeing sports teams make marginal gains across the board thanks to the effective use of data, and the overall quality of these sports will improve as a result. For the average fan, though, a wide receiver's average sprint duration over the course of a game isn't as emotive or interesting as looking at the team's plays more generally. Analytics has well and truly bled its way into sports, let's just hope it doesn't sterilize what are often fluid and occasionally magical occasions.