About thirteen years ago, I was sitting in Charlie Pasarell’s front row box at Indian Wells. He’d been kind enough to offer me the seats for a couple of hours because, well, that’s the kind of tournament host Charlie was. On the stadium, Roger Federer was wearing baby blue and having a rough go of it, so I had a few moments to observe the crowd. Three seats to my West, a mid-sixties man, with bamboo-shaped arms and a brown fishing hat, scribbled furiously upon his notepad. When the three senior citizens sitting between us got the call from nature, we got to chatting.
In the late eighties, he said, he’d developed an algorithm which, when run through a simulator, determined the global impact of a hundred economic variables. Over the next few decades, he made his fortune leasing the program to governments at six figures per day. As I stared at my churro, I wondered what the hell he was talking about. “Someone,” he commented, “should undertake a statistical analysis of tennis.” He asked me to walk him to his car after the match, and, with the sort of hyper-vigilance prison inmates know intimately, I conceded, curious. His Mercedes trunk popped, and he brought out a book called Moneyball, Michael Lewis’ account of Billy Beane’s major league baseball experience, where statistical data trumped every previously known scouting analysis. “Read this,” he said, “you’ll understand.”
Since then, the world of professional tennis has changed drastically. There’s Hawkeye and IBM’s Slamtracker. We see “Keys to the Match” and “Match Summary,” and any amateur who is willing to cough up a few bucks can send in a video and receive analytics. My friend, Craig O’Shannessy, strategy analyst for Wimbledon, Australian Open, ATP, WTA and more, is traveling the world educating coaches and athletes with some highly revealing insights about the game. Very quickly, tennis is becoming a high-information game. Inside the numbers, we see things like “a 2% increase in returns made” by Novak Djokovic could boost his already-insane winning percentage significantly. That kind of knowledge can translate to zeros on checks and gold on the mantle.
In the locker room, coaches are five deep in conversations about how to utilize the massive amounts of data pouring in. A few years back, Paul Annacone and I were discussing Federer’s loss to Andy Murray at Wimbledon. Paul mentioned the post-match stats showed Murray only served 67%, but that they didn’t show his 80% first serve percentage on the first two points of the game. This meant Andy could be a little more aggressive with his serve later in the games because he was serving so well early. He intimated that there is still much to be gained from watching a tennis match rather than just analyzing statistics. Maybe Professor Aaron Levenstein said it best, “Statistics are like bikinis – what they reveal is suggestive, but what they conceal is vital.”
Still, the data is getting better. The comparative analytics are helping coaches formulate strategies and providing insight into the future of the game. Perhaps we’ll never be able to address the statistical impact of fortitude and intelligence and adaptability in our sport, but it appears high-information is a path we will follow for a while. As for me, when I head back to Indian Wells this year, I’ll be looking for that guy with the brown fishing hat. I have a book for him, along with a dose of missed opportunity. And then I’m getting another churro.
Topics: 10sballs.com, Andy Murray, Atp World Tour, BNP Paribas Open, Charlie Pasarell, Craig Cignarelli, Federer, Indian Wells, Paul Annacone, Sports, Tennis News, Wta
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