Sports Relying More On Analytics than Athletics

Though the Brad Pitt vehicle, Moneyball, has made analytics synonymous with baseball, the big-data approach to competition has branched into a broad array of sports, promising a boost in performance and efficiency for effective adopters.

Analytics uses large data samples of in-depth performance analysis to better evaluate a player’s effectiveness. For example, rather than merely counting a player’s completed passes, it can analyze exactly how effective those passes were. This seems to give teams a distinct tactical advantage, and those neglecting the breakthrough do so at their peril.

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There is plenty of criticism however; opponents, mostly the sporting world’s aging vanguard, fear that the human heart of their respective sports is under attack. Indeed, the positive results of big data have arisen precisely because they behave with a dispassion that human beings are incapable of. It needn’t override intuition, but analytics can play an important role in balancing the biases that go with it.

This dispassion suggests, also, that sports fans read far too much into their teams’ performances. Aaron Clauset, a computer science professor at the University of Colorado, recently analyzed each and every point scored across 40,000 games in pro hockey, basketball, and football.

Clauset realized that game patterns and scoring rhythms remained remarkably stable across his data set. The scoring rate is relatively low at the beginning of a game or period, then picks up, and spikes somewhere towards the end. In football and hockey, winning teams tended to increase their lead, while in basketball, losing teams tended to catch up (perhaps due to greater determination, a much faster scoring rate, or the different use of substitutions).

Clauset says there is no evidence that different momentums or scoring streaks make a significant impact. Nor, he claims, is there any evidence of successful strategic planning over longer term plays, but that teams largely react to events as they occur with the focus on increasing their short-term scoring opportunities.

Apparently, fluid sports like these might be as similar to each other as stop-start games like baseball, cricket, or even golf. Could the new approach kill fandom’s passion for conjecture and trivia? How can undermining a sport’s uniqueness not put a damper on it?

Instead, analytics emphasizes the uniqueness of each individual. Hockey teams can select players who might be better at scoring against a certain goalie. Soccer defenders can be selected specifically for the effectiveness of their long balls in successful counter attacks, opening up a wide range of new possibilities for the sport’s tacticians.

It’s not just in this country either. Data analysts are now employed at each of the English Premier League’s 20 clubs. Statistical analysis has leapt from simply counting shots on goal and possession to recording around “1,500 events” per game. The last couple of seasons have been two of the most exciting and least predictable in years.

Being early adopters of analytics, Everton FC, though never lifting the trophy themselves, have been the highest performing club based on expenditure for several years. There is plenty of anecdotal evidence to suggest that analytics is an incredibly efficient approach to sport. Early adopters in ice hockey, the Los Angeles Kings and Chicago Blackhawks, have won 4 of the 5 possible Stanley Cups since 2010.

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So should coaches trust their eyes over the stats? Billy Beane, the Oakland A’s GM who inspired Moneyball, says “I don’t buy that because I’ve seen magicians pull rabbits out of hats and I know that the rabbit’s not in there.” Will sportseventually become a war between computers? Unlikely. For all the computer power in the world, our lauded athletes are still going to have to score at some point or another. Analytics is merely dragging sporting culture into the modern age, directing competing teams to play the best they’ve got, week in, week out.

That’s good news for sports fans!


 

Nick Rojas is a business consultant and writer who lives in Los Angeles and Chicago. He has consulted small and medium-sized enterprises for over twenty years. He has contributed articles to Visual.ly, Entrepreneur, and TechCrunch. You can follow him on Twitter @NickARojas, or you can reach him at NickAndrewRojas@gmail.com

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