Wimbledon wants to teach tennis to its audience. Luckily there is an app for that.

This is not a snub; not everyone can be a professional in the chair.

“A few years ago, we did a study that showed us that the majority of people who play Wimbledon are not really year-round tennis fans,” says Alexandra Willis, director of marketing and communications for the host All England Club. .

“We accidentally heard, ‘I’ve heard of a few top players, but I haven’t really heard of many others,’ and ‘It all seems a bit confusing and misleading,'” she adds.

This is clear. Tennis is in an era where the men’s and, to some extent, the women’s game has been defined by a small proportion of dominant players with astonishing career lengths.

To fill the knowledge gap, the All England Club has teamed up with IBM to use artificial intelligence (AI) and big data to increase engagement and try to predict the winner of each match in the process.

Spectators in fancy dress are tennis icons at Wimbledon 2017.

Think of Moneyball, which is only for fans.

Within the “Match Insights with Watson“A feature in the Wimbledon app and Wimbeldon.com, an ever-changing IBM Power Index has been assigned to each player thanks to IBM Watson, the company’s artificial intelligence for business.

“Rankings are based on an analysis of the form, performance and momentum of the athletes,” explains Kevin Farrar, Head of IBM Sports Partnerships in the UK and Ireland. “Because it’s updated daily… you can see (players) that need to be watched, (and) it can start to pick up potential upset warnings – all of which are interesting for fans,” he explains.

The idea is to help less-initiated fans find players to follow, “growing their own fandom,” Willis says. Users can track players and receive personalized reviews as the tournament progresses.

An IBM technician poses with screens showing AI-generated highlights during Wimbledon 2019. The tournament has partnered with IBM to educate fans at the 2022 tournament.

Part of Watson’s party uses the data to predict the winner of each match. Displayed as a simple percentage chance, the AI ​​makes the call based on millions of data points recorded before and during the tournament. Factors include previous performance between athletes, current form, and more details such as 1st inning win percentage, aces frequency, and percentage of points won since 1st inning.

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Farrar explains that tournament data is compiled by a team of “very good tennis players” – usually at district level and above – who watch every match at Wimbledon, with three statisticians working on the exhibition courts and one on the outside courts. Hawkeye ball and player tracking is also used.

However, not all data fed into the predictor is based on exact statistics. Curiously, positive or negative sentiment in the media is also taken into account when scanning thousands of news articles about players.

“One of the markers of “who cares?” “Who cares about the media?” Willis says. “Many members of the media, especially in a sport like tennis where they spend week after week with the players, feel and understand how well people play—those soft factors that don’t necessarily show up at (structured data points) . “

More than just a makeshift hat: Newspaper articles are analyzed by Watson to determine media attitudes towards players.

Farrar reported that Watson predicted the results with “virtually 100% accuracy” on the first day of the tournament, but the third day was the first big disappointment when women’s No. 2 seed and match favorite 66% Anette Kontaveit was beaten by unseeded Jule Niemeyer in straight sets. .

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Despite using one of the world’s most famous artificial intelligences, Willis insists that “this does not pretend to be exact or exact science.”

And even if Watson loses, it’s still a win-win, Farrar insists. “It’s an interesting topic to talk about and it’s fan engagement that’s a key goal.”

“Sports fans love debate. Therefore, we give them a reason for discussion.”