By Christopher Clarey / New York Times
THE Australian Open, once the clear laggard among the four Grand Slam tennis tournaments, has regained its luster by expanding relentlessly and taking chances.
It was the first major tournament to build a stadium with a retractable roof and is now the first with three such stadiums. This year it will become the first Grand Slam event to sell a small block of on-court tickets that will allow spectators to sit opposite the chair umpire, less than 8 meters (26 feet) from the sideline on the Open’s main show court, Rod Laver Arena.
But the tournament director, Craig Tiley, is interested in more than facilities and revenue. Tiley, a former college tennis coach at the University of Illinois, has long been interested in improving the information available to both tennis insiders and fans. In his role as chief executive of Tennis Australia, he pushed to create an entity at the federation called the Game Insight Group (GIG).
One of the benefits to the public is a new flow of compelling and creative player statistics that have been published ahead of this year’s Open and will be updated and released during the tournament itself.
“We are in an intensely competitive marketplace, and we owe it to these wonderful athletes, to our sport and to fans to constantly strive for more insight into the unique prowess of these remarkable players,” Tiley said in an interview earlier this month. “We want our sport to keep attracting the next generation, interacting with them in the manner they want with information that appeals.”
Among GIG’s findings, based on data collected from the seven primary courts at the last three Australian Opens:
n Based on a metric created by GIG, Andy Murray had the highest work rate per shot in the men’s game and Gilles Simon the highest work rate per point. Barbora Strycova had the highest work rate per shot in the women’s game; Yulia Putintseva the highest work rate per point.
n Nick Kyrgios ranks No. 1 and Roger Federer No. 2 in reaction time on service returns in the men’s game, ahead of Novak Djokovic, widely viewed as the game’s best returner, who ranks seventh by this measure.
n Serena Williams, known for her aggressive style of play, ranks near the bottom among women in shots that land close to the line.
GIG also calculated average forehand and backhand speeds on impact: a significant statistical step forward in a sport where service speeds are typically the only speed data made widely available (and can vary depending on the brand of speed gun used).
GIG provided data to The New York Times on players who had been in at least 10 matches on the seven show courts from 2012 to 2016. The young American star Madison Keys’s average forehand speed ranked first among the women, but also ahead of all men, except Tomas Berdych. Keys’s average backhand speed was also higher than any of the men’s, ranking just behind the now-retired women’s star Li Na.
In another surprise, GIG also provided foot-speed data to The New York Times showing that Milos Raonic, a big server not known as a particularly quick mover, had the highest recorded maximum speed over the five-year span and that even his average foot speed of 10.1 mph was slightly above Murray’s.
Stephanie Kovalchik, the data scientist at GIG responsible for much of the new research, said a player’s height (Raonic is 6-foot-6) could be a factor.
“We know from sprinting that the benefits and costs with height are complex,” she said. “The complexity in tennis is likely greater, since movement is more sporadic and in all directions.” She also said the movement research did not account for “how a player was moving.”
She added, “If some players cover more distance forward versus laterally, for example, it could impact how their speed characteristics compare to each other.”
Data analytics have become de rigueur in major sports. Tennis has been slow to embrace the trend and, when it has, the information has often been restricted for commercial reasons and has too seldom been released to the public, frustrating many statistics-minded fans.
“If you contrast something like tennis to Major League Baseball, it really seems the openness of the data is the main barrier,” Kovalchik said. “If you look at tennis, everything is so siloed. There’s almost an infrastructure problem. We are limited, of course, to only the Australian Open series, which is one type of surface and one region and that has its limits in terms of representation of the tour, but we still think there’s insight there in terms of measurement compared to how it’s been in the past.”
Tennis’ traditional streak has also played a role in limiting data, as has the sport’s relative simplicity, said Paul Annacone, former coach of Pete Sampras and Federer. Annacone said he used analytics sparingly with Sampras, but “40 percent to 50 percent more” with Federer.
Annacone said he thought statistics were less prevalent in tennis because there were fewer moving parts than in other sports.
“Look at all the moving parts on a football field or basketball court,” he said. “There are so many things you have to take into consideration. In tennis, at the top of the game there are certain patterns that are just really prominent, and if you look at the best of the best, you understand why they are able to expose weaknesses and finish the points the way they need to finish them. It’s a more clear vision because there aren’t any other teammates out there, so I think that’s one of the reasons behind the technology lag.”
Image credits: AP