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An Anti-Scientific Approach Is Bad For Sports

Those who dismiss analytics are missing opportunities

25Oct

At this point, in late 2016, we should stop seeing articles titled things like ‘How analytics will change sports,’ or ‘The big data revolution in sports.’ So entrenched is the use of data analytics that its impact shouldn’t be news to anybody. What we are experiencing now, though, is the long period of acceptance in some sports. Data analytics has a place in all sport, but tradition can be difficult to shake and those still enamoured with an era of ‘gut instinct’ and touchline decision-making generally won’t accept it quickly.

In the US, sports have long been discussed with a focus on data. Ask any Stephen Curry fan, for example, about his most recent performance and they’ll likely reel off his stats. In baseball, an obsession with batting average gave way to an appreciation of on-base percentage as analytics swept the sport last decade. The US sports fan has been paying attention to data for years. Head across the Atlantic to Europe, though, and its most popular sport - soccer - has only recently been discussed in terms of data. Possession statistics and passing accuracy will flash onto the screen during coverage of EPL soccer, but rarely will pundits discuss these numbers such is the obsession with tactics, individual brilliance, and other less quantifiable qualities like team spirit.

The cult of the manager in soccer is partly to blame, with intuitive decision-making valued above all else and the tendency, then, to ignore the numbers. The hyper-traditional sport shuns those too heavily focused on figures and praises philosophy over analysis. It’s a bad thing, though, in any sport, to resist the numbers; the reward of embracing them is too great. From player performance to fan engagement, there’s not a lot in sport that can’t be improved by data analytics.

Player optimization

Billy Beane’s work with the Oakland As has gone down in history as the first gleaming example of numbers trumping tradition in a major sporting competition. By considering different metrics and fine tuning them, the coach was able to squeeze incredible efficiency from an underfunded motley crew of a team.

Golden State Warriors’ coaching staff have developed arguably the greatest shooter of all time in Steph Curry, and will work closely with data to improve his performances. The second stage in sport’s adoption of data analytics is taking the horde of data collected and forming it into actionable insights, much like in other industries. Once data properly informs both training and player instruction, coaches will be able to squeeze the very best out of their athletes. Fans pay top dollar to see their teams perform at their peak - data can help teams hit these heights.

It encourages experimentation

Though it may seem counterintuitive, thorough examination and interrogation of data in sports can encourage experimentation rather than stifle it. With data on past outcomes allowing analytics teams to predict the outcome of changes to tactics or personnel, for example, experimentation carries far less risk.

Data can reveal otherwise hidden patterns that can be countered. Take, for example, Lou Boudreau’s stifling of Ted Williams in the mid-20th century. Boudreau observed that Williams - one of the fiercest hitters all time - tended to pull his hits. As a response, he shifted his fielders to one side, a lopsided alignment which at the time looked ridiculous. It worked - Williams’ batting average dropped 15 points when other teams mimicked the tactic. Now, imagine if teams were able to uncover less immediately visible patterns in opponents’ play and set up to exploit them. Not only will sport see more initially baffling tactics developed off the back of stats, but their effect will be accurately quantifiable.

Fan experience

Unlike customers in other industries, sports fans are insatiable in their hunt for information. With a genuine interest in the numbers that can explain the games they love, fans will digest statistics readily - analytics and data visualization can help present the numbers in a compelling way. The remote experience has been greatly improved by this, with fans watching on the small screen given not just replays but real-time analysis of the game data.

But the in-stadium experience is also benefitting. ‘Smart stadiums’ are popping up all over the US, in particular, with greater connectivity allowing for smartphone video replays, food orders to the seats, paperless ticketing, and other information like where the bathroom lines are shortest, for example. Good fan experience drives revenue for sports teams both in the stadium and through television contracts - getting it right is good for the industry. 

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