Wimbledon's AI line calls and Apple's Sports app: what sports tech actually gets right

Two failures, one tournament, and a narrative that wrote itself. During the 2025 Wimbledon fortnight, the electronic line-judging system missed a Sonay Kartal ball that had gone long, costing Anastasia Pavlyuchenkova a game, because an official had accidentally switched the system off. Days later, a Taylor Fritz forehand was called out despite landing four feet inside the baseline, after the system was confused by a ballboy still on court.

The Guardian's Sean Ingle reported on 15 July 2025 that the outrage missed the wider picture. Wimbledon was running a souped-up version of the Hawk-Eye system it has used since 2007, and researchers have long estimated that line judges get around 8% of close calls wrong.

Players are worse judges than the machines

The number that should settle the argument is the challenge record. Ingle asked IBM how often players were right when they challenged a line call at Wimbledon in 2024. Of 1,535 challenges across the men's and women's singles, just 380 were overturned, meaning players were wrong three times out of four.

"No system is 100% perfect, but they are demonstrably more accurate than relying purely on human decision-making," said Matt Drew, who founded the integrity department at StatsPerform.

That framing matters because the case for sports technology is not that machines are flawless. It is that they fail less often than people, and that their failures are visible, logged and fixable in a way that a referee's split-second judgment is not. Two incidents in a fortnight make headlines precisely because they are rare. Nobody counts the close calls a line judge gets wrong, because nobody sees them.

Why this is a data story, not a gadget story

Sports analytics is a market with money behind it. Reuters reported on 22 September 2026 that MarketsandMarkets valued the AI in sports market at $2.61 billion, growing at a 16.7% CAGR to 2030. Data providers, performance tracking vendors and analytics platforms are all chasing the same budgets. The Guardian's own reporting notes the direction of travel: from September 2026, the NFL replaces its chain gang with Hawk-Eye technology.

At the International Olympic Committee's artificial intelligence conference in 2024, a diver was shown in real time with a screen telling judges his jump height, rotations in the air and how close his legs were to his torso, with each element split into sequences and analysed in under a tenth of a second. The stated aim was fairer scoring. That is a data pipeline, not a novelty.

The counterweight is real. The New York Post reported on 21 September 2026 that DraftKings used AI to target losing bettors, quoting an internal line: "The best investment would be a problem gambler." The same analytical machinery that grades a dive can also profile a customer's losses. The technology is neutral; the deployment is not.

The Apple lesson: do one thing

Not every useful sports product is an analytics platform. Slate's review of Apple's Sports app, published on 10 June 2026, argued that its value comes from refusing to be anything more than a scoreboard. No news headlines, no streaming guides, no algorithmic feed designed to hold attention longer. Team names, records, game times, scores, standings, and a toggle to kill betting odds permanently.

The app was announced in winter 2024 with a pitch the reviewer called almost adorable: an executive saying Apple created it to give fans fast access to scores and stats. It covers roughly 30 soccer leagues plus MLS, the NWSL, tennis and the LPGA Tour, and it pushes score updates to lock screens as Live Activities.

Put the two stories side by side and the pattern is clear. The sports technology that earns trust tends to be narrow, verifiable and fast. The systems that attract anger are the ones where accuracy is disputed, or where the data is pointed at the fan rather than the game.

Wimbledon's gremlins will be forgotten. Its overturned-challenge statistics will not.