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Artificial intelligence is no longer just powering highlight reels and fantasy stats — it is increasingly the engine behind the decisions that shape competition: which player to draft, when to press, whether a goal stands. Crucially, in almost every serious deployment a human still makes the final call; AI compresses oceans of data into something a coach, scout, or referee can act on in seconds. This report looks at how AI supports sporting decision-making, anchored in real, sourced case studies.

Key takeaways

• Roster decisions: the Toronto Raptors used IBM Watson (“Sports Insights Central”) from 2016 to automate a historically manual player-evaluation process.
• Officiating decisions: FIFA’s Semi-Automated Offside Technology tracks up to 29 points per player, 50 times a second — but the referee still decides.
• Broadcast & fan decisions: IBM analyzes 100,000+ data points per match at Wimbledon to generate insights, predictions, and the Power Index.
• The market: estimates vary widely, but one projection puts AI in sports at roughly $60.8B by 2034 (~21% CAGR).
• The constant: these are decision-support systems — human-in-the-loop is the design principle, not an afterthought.

1. Roster & draft decisions: IBM Watson and the Toronto Raptors

In February 2016 the Toronto Raptors unveiled a “digital war room” built on IBM Watson, branded IBM Sports Insights Central. The system pulled together box-score statistics, video, medical records, and even social-media sentiment, then weighed prospects against the team’s specific needs — a player’s likelihood of succeeding, staying healthy, and fitting the locker room over the life of a contract. The point was not to replace scouts but to automate a process the Raptors had previously run with whiteboards and printed magnets, freeing decision-makers to focus on judgment. Three years later, Toronto won the 2019 NBA Championship. Source: IBM / TechCrunch, 2016.

2. In-game & coaching decisions: optical player tracking

Once a game is underway, the decisions move faster than any human can fully process. The NBA’s optical tracking system (Second Spectrum) uses AI-powered cameras to follow every player and the ball in real time, mapping defensive formations and quantifying shot quality and matchups. Coaching staffs — famously the Golden State Warriors — use this to refine rotations and tactics. The same pattern recurs across football, baseball, and tennis: computer vision turns raw movement into actionable reads, but the coach still chooses the adjustment.

3. Officiating decisions: FIFA’s Semi-Automated Offside Technology

Few decisions are as contested as offside. At the 2022 World Cup, FIFA deployed Semi-Automated Offside Technology (SAOT): 12 dedicated cameras track the ball and up to 29 data points on each player, 50 times per second, while a sensor inside the ball reports the exact kick point 500 times per second. The system flags potential offsides to video officials, who verify before the referee makes the final call — hence “semi-automated.” For the 2026 World Cup, FIFA is upgrading SAOT with 3D-scanned player avatars and tighter alert thresholds to make calls faster and harder to dispute. Source: FIFA, 2022 & 2026.

4. Broadcast, fan & tournament decisions: IBM at Wimbledon

Wimbledon and IBM have one of sport’s longest-running AI partnerships. IBM’s Power Index combines statistical analysis with natural-language processing of millions of expert opinions to quantify each player’s momentum, while Match Insights mines more than 100,000 data points per match to generate predictions and analysis. IBM pioneered AI-curated highlight reels in 2017 — using crowd noise, player gestures, and game context to detect the most exciting moments — and has since layered on generative-AI features like “Catch Me Up” player summaries (2024) and AI-generated spoken commentary, all running on watsonx. These shape editorial and broadcast decisions about what to surface to a global audience. Source: IBM case studies; ESPN, 2023–2024.

The market — and a caveat on the numbers

The AI-in-sports market is growing fast, but analyst estimates diverge sharply: 2025 sizing ranges from roughly $1.2 billion to more than $10 billion depending on what each firm counts. One widely cited projection (Precedence Research) puts the market near $60.8 billion by 2034, a ~21% compound annual growth rate, with predictive analytics and generative AI as the largest segments and North America the largest region. Treat any single figure as directional; the trajectory — up and to the right — is what the sources agree on.

The through-line: decision support, not decision replacement

Across drafting, coaching, officiating, and broadcasting, the winning pattern is the same: AI handles the volume and speed of data; humans keep authority over the call. The Raptors’ scouts still pick the player. The referee still signals offside. The coach still makes the substitution. That human-in-the-loop design is not a limitation to be engineered away — in high-stakes, high-scrutiny environments, it is the feature.

Methodology & sources

• IBM Watson & the Toronto Raptors — TechCrunch (2016)
• FIFA Semi-Automated Offside Technology — FIFA media release (2022) and FIFA innovation (2026)
• IBM & Wimbledon generative AI — IBM case study; ESPN (2023)
• AI in sports market sizing — Precedence Research

Frequently asked questions

How is AI used for decision-making in sports?

AI ingests large volumes of data — tracking, video, statistics, medical and sentiment data — and turns it into recommendations for roster, coaching, officiating, and broadcast decisions. In nearly all serious systems, a human makes the final call.

What did IBM Watson do for the Toronto Raptors?

From 2016, the Raptors used IBM’s “Sports Insights Central” to evaluate draft prospects — combining stats, video, medical and social data against team needs — automating a process previously run manually with whiteboards.

Does AI make the offside calls at the World Cup?

Not on its own. FIFA’s Semi-Automated Offside Technology measures player and ball positions and alerts video officials, but the on-field referee makes the final decision — which is why it is called “semi-automated.”