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Sports analytics on the rise as Australia plays catch-up with rest of world

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The most advanced Australian league is the AFL but ring fencing of its data has held back valuable work that could have furthered understanding of the game

 

DVOA. wOBA. PER. Y/A. BABiP. Confused? Well, welcome to analytics. Take a sport, any sport, your favourite sport. Now break it down, describe it, tell your mate about a good performance. How do you talk about it, what do you turn to? Do you talk to them about numbers, the vibe, the narrative? Do you have a way that you can actually quantify what you’re talking about, any proof other than that you saw it and you just know? This is where analytics come in and attempt to fill the gap. Building metrics to explain what your eyes told you, putting it in context.

“Most of the work being done around analytics concerns event data,” says Simon Strachan of Gain Line Analytics. A lot of that isn’t exactly new, it’s just more accessible than ever before. Coaches still want to know the same things, it’s just that where 20 years ago people were working with VHS and they might have had to wait almost a week to get their data, now they can get it on their tablet in almost real time. The amount of new insight is minimal, the technology has just made the process quicker and smoother than it’s ever been. “The evolution,” Strachan says, “is going to be understanding how teams work together.”

Strachan gives the example of the rugby player Sam Burgess making his ill-fated transition from league to union in the lead up to the 2015 Rugby World Cup. It wasn’t necessarily that Burgess was bad, or that he didn’t understand what the players around him were doing, it was also that they didn’t understand what hewas doing.

At the top level of the game, where the margins between victory and defeat are often all but razor thin, the cohesion of a team can make all the difference. It’s how we see dynasties being built. Hawthorn in the AFL, the NRL’s Melbourne Storm and Queensland in State of Origin – the systems that underpin these teams are so strong, the players are so well integrated into it, that they have an intuitive, almost instinctual knowledge of the players around them. If you’ve ever wondered why so many players who leave these great teams flounder, it’s not because they’re bad players, or that they were overrated. It’s that they’ve gone from a system that they understood, and one where they were understood, to a foreign one with foreign expectations. It’s important to remember, Strachan says, that “skill is a driver of success, but it’s not as important as assumed”.

 The most advanced of the Australian sports leagues when it comes to data is probably the AFL, which has been collecting it seriously for over 30 years. But even then, Darren O’Shaughnessy of Ranking Software says “proper analytics have really only taken off in the past two”. Previously at Champion Data, O’Shaughnessy has had an exclusive contract with Hawthorn over the past six years, a time period in which they’ve reached four grand finals, won three of them and established themselves as one of the greatest teams of all time. O’Shaughnessy believes in targeted analytics, which he provides for the club, over broad metrics that treat all clubs equally. “If we play a seven-man defence, we ought to know how much we expect the scoring to slow down for both teams,” he says. “So you have to build a predictive model that takes into account who is playing which role, the type of opposition, and our tactics in play.”

Frustratingly, little work like this has emerged in the AFL – at least not in the public view. This is largely down to the ring fencing of data, where Champion Data (49% owned by the AFL) have the licence to collect and corral the data from all AFL games – at which point they can charge clubs and media organisations a non-disclosed, but exorbitant, fee to access the vast databases they possess, effectively locking prospective analysts out of the loop and holding back valuable work that could be done to advance our understanding of the game. It’s an irritating situation for would-be independent analysts, especially when they see the data their contemporaries covering sports like baseball, basketball, ice hockey, and American football have access to.

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