Before a ball was kicked, the Opta supercomputer had already played the tournament 25,000 times. Its verdict: Spain were the most likely winners, winning 16.1 percent of the simulations, followed closely by semifinalists France, England and Argentina, each winning more than 10 percent.
The prediction quickly became far more than a percentage on a page. It appeared on television screens, influenced betting markets, dominated social media discussions and gave millions of fans a new way to follow the tournament. What began as a forecasting experience became part of how the World Cup was experienced in real time.
How the model works
As Jonathan Whitmore, director of analytics at Stats Perform, explains, the model combines Opta’s team rating with betting market odds. The team ratings are built on an Elo system, the same family of models used by FIFA. Elo weighs not just wins and losses but the stakes behind them. “Each respective team has a score, and if you beat a team with a better score, you have the ability to win more points and boost your score, whereas if you lose against a weaker team, they effectively win those points back off you, so it adjusts over time,” Whitmore explains.
Germany’s shock penalty-shootout defeat to Paraguay in the Round of 32 illustrates how the system adapts. The upset doesn’t just cost Germany a place in the draw, it actively transfers rating points to Paraguay, reshaping both teams’ odds in every subsequent simulation.
Ratings alone, however, cannot capture everything that shapes a match, so the model leans on a second data source to fill that gap: betting markets. “We indirectly account for information such as injuries, squad selection from the betting odds,” Whitmore says, “so we’re able to most accurately predict those upcoming games that are coming over the next few weeks.”
Ahead of the tournament, the model ran 25,000 simulations, substantially more than the 10,000 typically used for competitions such as the Premier League because of the World Cup’s smaller number of total matches. That scale paid off. At the semi-final stage, Spain, France, England and Argentina, the model’s top four pre-tournament teams, were also the tournament’s final four.
The value of A.I. predictions
Prediction has evolved from a pre-match novelty into one of sport’s most valuable products. What was once a tournament preview is now a live stream of insight powering broadcasts, enriching betting experiences and keeping fans engaged from the opening whistle to the final. Built on the trusted Opta data that underpins modern football, the Supercomputer has become one of the sport’s most trusted reference points.
The model continuously updates. “For every goal, every red card, every full-time whistle, every penalty, we get an updated simulation showing who’s most likely to win the tournament,” Whitmore explains.
Before the semi-finals, for example, France had overtaken Spain as tournament favorites, winning 34 percent of the model’s simulations. That continual recalculation is what makes modern prediction so valuable. The tournament becomes a live narrative, with every moment reflected in a constantly evolving forecast.
This reflects a wider shift across sports media. As data becomes more sophisticated, it has also become part of the storytelling. Every goal changes the probability of lifting the trophy. Every red card reshapes a team’s route to the final. Every result elsewhere recalculates qualification chances. Prediction models deepen the drama by giving every major moment additional context, revealing how the match—and the tournament—evolve with each new development.
Watch any major football broadcast today, and those insights are everywhere. Win probabilities sit beside the scoreline. Momentum graphics ebb and flow with the game. Qualification scenarios update instantly. These visuals no longer feel new because they have become part of how soccer is watched and understood.
That represents a fundamental change in fan behavior. A decade ago, expected goals was a specialist metric debated by analysts. Today, it’s part of everyday football conversation. Prediction models are following a similar trajectory, moving from niche analytics to the sport’s shared language.
For broadcasters, that context creates ongoing storytelling opportunities. Every probability update creates another talking point, another graphic, another social clip and another reason for viewers to stay engaged. Together, they turn a soccer match into an evolving narrative, with live prediction models updating throughout play.
BBC Sport demonstrated this during Scotland’s decisive Group C fixture. Using Opta’s live prediction data, viewers could watch Scotland’s chances of reaching the Round of 32 change throughout the match. The model projected that Scotland would advance if they lost by no more than two goals, raising the stakes with every attack. Brazil’s goal ultimately erased that margin, ending Scotland’s World Cup run in real time.
That’s why fans value prediction. The appeal isn’t the percentage itself but the context it provides. Every goal, save, and red card creates an immediate shift in the tournament narrative, giving supporters another reason to celebrate, debate or fear. With 93 percent of Gen Z using a second screen while watching sports, live predictions naturally extend the experience beyond the television, encouraging audiences to follow the story across multiple platforms.
The same data can also power personalized experiences. A casual fan may simply want to know who is most likely to win the tournament, while a devoted supporter wants to understand their club or country’s changing route to the final. One trusted predictive model can support broadcast graphics, editorial coverage, fan experiences and betting products simultaneously.
In this way, predictive models are becoming the connective tissue between live sports data and audience understanding. As the volume of information grows, from historical performance to player tracking to real-time match events, the challenge is making sense of what the data means in the moment. Predictive models provide that missing layer of interpretation, transforming raw inputs into narratives, recommendations and decisions across broadcasts, personalized fan experiences, betting platforms, notifications and emerging A.I. assistants. With sports data becoming more abundant and complex, prediction models provide the context that turns information into understanding. The companies that control this explanatory layer will shape how audiences experience live sports.
Trust as the ultimate competitive edge
For sportsbooks, broadcasters and media companies, the commercial value extends even further. Prediction models help explain how a match is evolving before and during play, giving broadcasts, betting products and digital experiences a shared layer of trusted context. Live probabilities, projected line-ups and tournament forecasts increasingly underpin the products and services built around live sports. None of this works without trust.
Broadcasters won’t build programming around forecasts they don’t believe. Sportsbooks won’t integrate unreliable models into customer experiences. Fans won’t return to forecasts that consistently fail to reflect the game on the field.
This is why accuracy carries so much weight. A wrong final score is quickly forgotten. A wrong prediction repeated across broadcast graphics, betting products, editorial content and push notifications becomes a credibility problem multiplied across every platform that relies on it. As prediction becomes more valuable, trust becomes even more important.
Perhaps the clearest demonstration of that trust came not from a broadcaster or bookmaker, but from the man who runs world football itself. Asked about Spain being installed as pre-tournament favorites by the Opta Supercomputer, FIFA President Gianni Infantino simply smiled and replied, “Well, if Opta says so.”
It was a light-hearted remark, but it captured something significant. The Opta Supercomputer and prediction models are trusted not because they use A.I., but because it is built on the data that millions of broadcasters, sportsbooks, clubs and fans already rely on to understand the game.
As A.I. continues to evolve, prediction models will become even more sophisticated. Their greatest value, however, will remain the same: helping millions of people understand, in real time, how every moment changes the story unfolding in front of them.
