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Network World - If humans can't beat a computer at "Jeopardy!" why should we trust them to make the right call on fourth down in the Super Bowl?
That was the fundamental question asked by some researchers at the MIT Sloan Sports Analytics Conference in Boston on Friday and Saturday.
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"Jeopardy!" players Ken Jennings and Brad Rutter "are some very smart people and they can't beat a computer [IBM's Watson] when it comes to one variable," says Tarek Kamil, founder of WhatIfSports.com and an executive at InfoMotion Sports Technologies. "How is a coach supposed to keep up with a computer when you're talking about 10 players on a [basketball] court," and variables including referee tendencies, defensive tempo and players' positions on the court? "There are literally 20,000 variables that come into play" in determining the right strategy, he says.
"Fifty years from now, we're going to laugh about how we used to give coaches this much responsibility," he says.
One might make the opposite argument, that Watson could only beat human players as long as the game was contained to one task -- answering trivia questions. And Watson had to consider millions of pieces of data to answer those questions. But Moore's Law ensures the exponential growth of computers' processing power, and sports experts are taking notice of their analytics capabilities after years of dismissing stat geeks as not living in the real world.
Although Kamil gave an extreme example of computers taking over human functions in sports, he also stressed the need for human guidance. "Am I saying we're going to get rid of coaches? Absolutely not," he says. "Someone has to be in charge of discipline. Someone has to be in charge of teaching players" and acting as mentors.
But human coaches are "not optimized for strategy and in-game decisions," he says.
Statistical analysis has already shown that baseball managers have over-relied on stolen bases and sacrifices, and that players are making a mistake when they slide into first base rather than running through the base. But convincing managers and players to change their habits, even in the face of unmistakable data, is an ongoing challenge.
At least in the United States, the analytics wave was led by baseball researchers, a no-brainer given that nearly every interaction in baseball can be assigned a statistic. Stat geeks, in general, have found that traditional statistics like batting average and earned run average aren't the best predictors of future performance. And their techniques are being applied to football, basketball, hockey and soccer.
Number-crunching can help teams choose the right players in the draft or trades, adjust in-game strategy, and even predict the likelihood of injuries.
Stat nuts have had to overcome intransigence in a sports world often resistant to technology. While sports teams will pour billions into enhancing the fan experience, they often won't make basic changes that could enhance the game. Major League Baseball finally allows video reviews of home runs and foul balls, but soccer referees still can't use instant replay to determine whether the ball went into the net -- even in the World Cup.