Sports consumption is the full set of ways people watch, follow, and interact with live sporting events. That includes broadcast TV, streaming apps, social media highlights, podcasts, fantasy leagues, and betting platforms.
The sociology of sports tells us that how we consume games informs the way we value teams, athletes and the product itself, and right now, that relationship is changing fast.
Artificial intelligence has cracked this ecosystem wide open.
AI is now behind real-time graphics that are broadcast live, personalised highlight reels, automated camera systems and dynamic betting odds that change in the space of seconds following a key play.
The AI-in-sports market alone is expected to reach a value of $10.8 billion in 2025 and more than $60 billion by 2034, according to WSC Sports.
That’s a compound growth rate of 21% per year.
So here’s the real question, does AI make us better sports fans, or is it just another way we can split our attention?
The Second-Screen Problem
A stat that should stop every sports executive in their tracks: 83% of Gen Z viewers use multiple screens at the same time when watching sports, according to research highlighted by GWI and Deloitte’s Sport Fan Insights.
That means for most fans, the game is not the only thing on their screen. It’s not even the primary thing most of the time. They’re scrolling social media, checking betting apps, texting group chats or watching a second game in a mini window.
And only 7% of second screen users even look at content related to what they’re watching, according to eMarketer.
AI accelerates this loop. Push notifications from betting apps arrive in milliseconds. AI-curated highlight clips hit social feeds before the replay goes on TV.
Personalised prop bet suggestions pop up based on your betting history. Each one of these takes your eyes off of the actual game.
That’s a design problem, of which AI is the cause and the possible solution.
How AI Is Changing What You See on Screen
If you’ve seen a Premier League, NBA or NFL broadcast in recent years, then you’ve already seen AI in action, you just might not have noticed.
Second Spectrum is owned by Genius Sports and operates the official optical tracking system for the NBA, Premier League and MLS. Its computer vision models process all the frames of game footage to track the positions of players, balls and their spatial relationships.
That creates millions of data points for each game, which is fed to coaching analytics, broadcast graphics and betting data feeds.
On the broadcast side, edge AI – where data gets processed at the stadium instead of the cloud – keeps latency under one second.
Modern deep learning models like YOLO (You Only Look Once) detect and identify objects within milliseconds. This is how broadcasters overlay real-time information about speed, tactical formations and ball trajectories onto the live feed.
Then there’s the production that’s automated.
Pixellot’s AI camera systems film, generate and stream sporting events with no human operators. The PGA TOUR introduced AI commentary in its TOURCAST app after fan research showed that 18-34-year-olds are interested in having more stats incorporated into the viewing experience.
And 54% of fans are now saying real-time stats actively improve their enjoyment of watching a game.
So AI isn’t only changing what’s happening behind the scenes. It’s changing the broadcast itself, from a passive viewing experience, to an interactive data layer.
Sports Betting and AI
The global market for sports betting reached around $112 billion in 2025, and is expected to reach between $226 billion and $325 billion by the mid-2030s.
Online platforms have led to approximately 68-75% of all betting activities. Live or in-play betting is the fastest-growing segment, representing more than 62% of the online sports betting market in 2025.
Exclusive data from betbrain signals a complex growth of influence, as confirmed by the growing public interest. That growth is deeply tied to AI.
Here’s how.
1. Live Betting Now Works with Adjustments from AI
Live betting, also called in-play betting, is making wagers on a game as it is happening and the odds are changing in real-time. This is where AI has the biggest impact.
Sportsbooks use AI to update lines within seconds of a key event: a red card, a quarterback injury, a shift in momentum.
These models monitor 50+ variables at a time and update odds, much faster than any trading team of humans could handle
For bettors, this creates a real attention problem.
You’re watching the game to look for trends. You’re also monitoring the odds to find value. Those are two different cognitive tasks simultaneously. And the speed of AI-adjusted lines means the window to act on the perception of an edge is reduced to seconds.
Stream latency is important here, as well. If your broadcast feed is even 15 seconds out of sync with the action as it is happening, the odds are already gone. Bettors who rely on streaming are structurally disadvantaged by those who can have low latency feeds – and AI is making this gap bigger.
2. Mobile-First Apps Make Every Phone a Sportsbook
Mobile betting apps have already been fitted with geolocation checks, biometric login, and push notifications that have enabled users to place a bet in under 10 seconds.
This is the real-life nature of the second screen problem.
You watch the match on your TV. You bet on your phone. If you’re really committed, you open a streaming app and a sportsbook split-screened on the same device and the game itself gets squeezed into a tiny corner window.
This means the thing you’re watching supposedly get literally shrunk to the size of a postage stamp on your screen. The sportsbook gets first priority. If the commentator says something interesting, you glance at the mini player, confirm what you heard and fire off a bet.
Both bookmakers and broadcast rights holders are aware of this.
That’s in fact why the NBA built live odds right into its League Pass streaming platform in 2024, and why Flutter Entertainment spent $350 million to acquire a 56% stake in Brazil’s Betnacional, to achieve mobile-first positioning in a market about to fully regulate sports betting.
3. AI-Powered Stats Make Every Fan an Analyst
AI has not just been a way for professionals to have better tools. It’s given casual fans access to the same depth of analysis that in the past required a full-time data scientist.
Basic stats can be found anywhere now: search engines, sportsbook dashboards and dedicated third-party trackers. These are helpful in following the flow of a game while betting live.
It’s advanced metrics that are the bigger story.
Expected goals (xG) in football, win probability models in basketball, and player efficiency ratings across every major sport used to take hours of post-game analysis.
The increase in AI computational power has now made real-time transmission of data feeds to direct analytics a reality.
For bettors, this creates a new skill layer. You’re not just watching the game. You’re cross-referencing what your eyes are telling you against what the data is saying.
If the stats are showing a team creating good quality chances regardless of the scoreline then, that could be a signal to bet on them before the odds change. It’s a deeper way to enjoy sport but it’s also more cognitive, which distracts you from enjoying the match.
AI Betting Tools
In 2026, AI betting tools have started their journey from a niche experiment to a mainstream product. So here’s what the landscape looks like:
Playbook by Action Network is a kind of an AI assistant that reads picks from a social post, screenshots or chat message and turns them into filled bet slips.
It doesn’t tell you what to bet. It cleans up the process between having an idea and placing the wager.
Platforms like Rithmm let you create your own predictive models with professional grade analytics. Their system highlights high-confidence bets with visual signs so you know which bets are rated the highest by the AI.
AI prediction bots on Telegram push 100 – 200 daily value bet alerts across football, basketball, tennis, and more.
The common thread is that none of these tools promise autopilot profits.
As Vegas Insider put it, the direction in 2026 is clear: bettors want AI as a research assistant, not a robot that is betting their money without asking. The best analogy is a “second brain” for sports analysis – it processes the data, but you still make the call.
What Gets Lost When Every Minute Is a Betting Opportunity
Here’s something that’s easy to miss in all the talk about AI tools and real-time odds: the emotional core of watching sport can get buried under the noise.
When you’re tracking live odds and monitoring prop bets and refreshing statistics dashboards, you’re engaged, but engaged as a trader, not a fan.
The adrenaline of the close game can make you go for losses or pile on risky parlays. AI tools for all their sophistication don’t have a “you should probably stop now” button.
Some platforms are beginning to deal with this.
AI-driven responsible gambling tools can identify patterns indicating problem behaviour – increased frequency of bets, betting to lose money or betting more than they can afford.
But these safeguards remain in their infancy throughout much of the industry.
So here’s a real recommendation, to watch a game this week without any bets, without the second screen and without the stat tracker. Just the match. See how it feels.
If you’re a betting person, gamble responsibly, and always keep in mind that AI is a tool, not a guarantee. The best use of all this technology is making sport more interesting, not making it a full-time trading desk.