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Wimbledon wants to teach the audience about tennis. Fortunately, there is an app for that

(CNN)The organizer of Wimbledon, the most prestigious grass court tournament in the world's oldest tennis grand slam, I'm thinking of some of those followers I don't know much about modern games.

It was not intended as a trivial matter. Not everyone can be an armchair professional.

"A few years ago, we found that most people who attend Wimbledon aren't really tennis fans all year long," said All England's Marketing and Communications Officer. Director Alexandra Willis said. The club that hosts the tournament.

"We anecdotally heard," I've heard of top players, but I haven't really heard of many other players. " This is all a bit confusing and feels like bamboo, "she adds. ..

That's understandable. Tennis is experiencing an era in which men's games and to some extent women's games are defined by a small assignment of dominant players with amazing career longevity.

To fill the knowledge gap, the All England Club is working with IBM to use artificial intelligence (AI) and big data to increase fan engagement and all in the process. I tried to predict the winner of the match.

Think of Moneyball. Only for fans.

As part of the Wimbledon app and's "MatchInsights with Watson" feature, each player is assigned an ever-changing "IBM PowerIndex" ranking. IBM Watson's

rankings, the company's AI for business, are generated by analyzing athletes' forms, performance and momentum, explains Kevin Farrar, Irish Sports Partnership Leader, IBM UK&. To do. "It's updated daily so ... (players) can see it and (and) start identifying potential upset alerts-everything is interesting to the fans," he explains.

The idea is to help novice fans find players to follow and "develop their own fandom," Willis says. Users can choose to track the player and are provided with personalized highlights as the tournament progresses.

Watson's party pieces use the data to predict the winners of every match. Shown as a simple percentage possibility, AI makes calls using millions of data points recorded before and during the tournament. Factors include previous results between athletes, current form, and more detailed details such as first serve win rate, ace frequency, and percentage of points earned back to first serve.

Farrar said the tournament data was edited by a team of "very good tennis players" (usually at county level and above) watching each match at Wimbledon, with three statisticians on the show court. , Explains that one is on the outside court. .. HawkeyeBall and player tracking is also used.

However, not all data entered into the predictor is based on hard statistics. Interestingly, the positive or negative sentiment of the media is also taken into account, and thousands of news articles about the player are scanned.

One of the markers of "who is interesting", "Who is the media excited about?" Willis says. "Many members of the media have a sense and understanding of how well people are playing, especially in sports with players every week, such as tennis. Always (structured data points). Will be displayed. "

Farrer reported that Watson predicted results with" almost 100% accuracy "on the first day of the tournament, but on the third day he was the second-ranked seed for women. 66% caused the first big mess when they lost to their favorite Annette Conservate. Straight set unseeded Julie Niemeyer.

Despite adopting one of the most famous AIs in the world, Willis claims that "this is not intended for accurate or accurate science."

And even if Watson loses, Farrer claims it's still win-win. "It's an interesting story point, it's the relationship with the fans, and that's an important goal."

"Sports fans love debate, so what we discuss with them Is given. "