Predicting Athletic Injuries – The Final Frontier For Sports Analytics
What if? It’s a question that many of the world’s top teams asked in the last year when faced with ill-timed injuries to key players. What if Derrick Rose of the Chicago Bulls, Robert Griffin III of the Redskins, Derek Jeter and Alex Rodriguez of the Yankees or Lionel Messi of Barcelona could have avoided their season ending injuries? Some are just the result of unlucky, violent contact but others have their origin from a combination of fatigue and overuse. What if athletic trainers and team physicians could find early clues and signals that an athlete was at risk of breaking down? Now, with the use of data analytics, that crystal ball may have finally arrived.
Stan Conte, VP of medical services for the Los Angeles Dodgers, declared last year, “in a post-Moneyball world, injury risk assessment is the final frontier.” At this year’s Sloan Sports Analytics Conference, he presented some surprising data to reinforce the rising toll of injuries; just over 50% of all starting pitchers in the MLB had some type of injury during last season, lasting an average of 65 days on the disabled list. Across all MLB players in 2012, the salaries of injured players plus the players that replaced them cost their teams almost $600 million.
Even at the Olympics, the world’s premier athletic showcase, the impact of injuries is significant. Big names like Paula Radcliffe, Asafa Powell, and Rafael Nadal could not complete their gold medal quest. Lars Engebretsen, a physician and professor at the University of Oslo and chief physician of the Norwegian Olympic team, has been tracking injuries and illness at the Games for over a decade. His latest report, released this month on the 2012 London Olympics, recorded 1,361 injuries and 758 illnesses among the 10,568 athletes, which equates to injury and illness rates of 11% and 7%, respectively. Unfortunately, these percentages are similar with the last two Summer Olympics in Beijing and Athens, highlighting the lack of progress in reducing lost time in competition.
In this Scientific American graphic, Engebretsen’s data from the 2008 Summer Olympics and the 2010 Winter Olympics shows that overuse caused 22% of summer athletes’ injuries while 54% of winter athletes were injured in training.
Like the Dodgers, teams across the globe are beginning to search for answers. As Big Data creeps into all aspects of athlete development, injury analytics is the new secret weapon. That is what pushed the Leicester Tigers rugby union club to dig into the details. Leicester, 9-time English champions, faces the challenge of tight budgets that requires keeping the best players on the field.
According to Andy Shelton, Leicester’s head of sports science, strength and conditioning, any competitive edge is worth the investment. “It gets more competitive every year and our focus must be on helping our players stay injury-free for longer,” he told the BBC. “When we have our key players available against the top European sides, we can compete and we will win, so the question is how do we keep key players on the pitch?”
Factoring in variables like fatigue, stress, sleep and training intensity into a predictive algorithm can yield what may have been hidden trends and combinations that cause injuries. “Similarly we also collect data on previous injuries that they had and what they are doing in the gym, basically everything they do from when they walk in the door of the club in the morning and leave in the evening is collected,” Shelton added. “The aim is to be able to affect a player’s lifestyle through the week. For example, if they recorded a very good night’s sleep, then their risk of injury could go down from ‘predicted injured’ to ‘not-predicted injured.’”
Some coaches and trainers still feel that using predictive analytics to create an injury model based on volumes of underlying data seems a little over the top. But if your job is to develop healthy, productive athletes that win, then any tool that provides an edge is worth a look.
“Traditional baseball types tell me to just give up, that this is a waste of time because injuries are mostly bad luck,” Conte commented. “Twenty-five years ago no one listened to Bill James either.”
Andy Shelton agrees, “There is no point in collecting stats unless you can know what to do with it. But by predicting things before they happen is where we can make gains, and considerably enhance performance.”
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