By Samuel Greengard
The list of uses for predictive analytics seems to expanddaily. Businesses and government are applying it in areas as diverse as health care,customer retention, energy conservation and crime prediction. Although sportsorganizations have tapped analytics for years?the book and film Moneyballhighlights the use of analytics to make player decisions in major leaguebaseball in the 1990s?software and applications are becoming more sophisticatedand widely deployed.
Enter professional rugby, one of the fastest growing sportsin the United States. It is known as a brutal contact sport with minimalprotective gear. In fact, about one-quarter of all players wind up hurt duringa typical season, and some suffer season-ending injuries. For these players, theinjuries represent an incredibly frustrating situation. For the teams, theabsence of key players on the field frequently results in lost games, as wellas diminished ticket sales and attendance.
But teams such as the Leicester Tigers in the United Kingdomare now embracing predictive analytics in order to conduct deep analysis of rawinjury data and statistics. "Sport is no longer just a game; it’s becomingmore and more a scientific undertaking that is driven by data andnumbers," notes Jeremy Shaw, IBM’s business analytics lead for Media andEntertainment. "Gone are the days of relying on raw talent and gutinstinct to succeed."
IBM is working with the Leicaster Tigers team to developmore efficient ways to understand why injuries occur and how the organizationcan reduce them. Analysts are studying a variety of factors, including fatigue,threshold and game intensity levels to detect hidden patterns and anomaliesthat provide insights into who might wind up injured and what types of injuriescould take place.
For example, if a player displays a statisticallysignificant change in one or more of his fatigue parameters and the current intensitylevel of training is high, the data might indicate that there’s an 80 percentgreater chance of suffering an injury. Someone else on the team might registera 60 percent greater risk. This level of real-time information makes itpossible for the team to alter a player’s training regimen or substitutionpattern in games in order to reduce the risk of injury.
But the analytics capabilities don’t stop there. Thetechnology also allows the Tigers to analyze psychological player data toreveal other key factors that could affect performance. This list includes theadditional stress of playing on the road, as well as social or environmentalelements that could effect the way players perform during a match. The end gameis to create custom training programs tailored to each player’s physical andpsychological state.
The concept is scoring big points. "There is atremendous value to be gained by retaining experienced players within thesquad," explains Andrew Shelton, head of sports science for the LeicesterTigers. By adopting predictive analytics, "Our team, for the first time,will be able to leverage data about the physical condition of players andconsiderably enhance our performance."
