Micro-betting has made spot fixing faster and harder to detect. Adam Fiske, CEO of Dimers sets out a real-time, data-led playbook for leagues and sportsbooks to protect sport.
When people think of match fixing, they tend to picture something big – a referee throwing a game, a player shaving points, a dramatic betrayal that decides who wins or loses. But the new frontier of manipulation is far smaller, faster, and harder to spot.
It’s called spot-fixing. And while it’s not a new threat, it’s seemingly becoming more common.
Unlike traditional fixing, it doesn’t target the outcome of a game – it targets individual, bettable moments within it. One pitch. One serve. One play. These micro-events, once too trivial to matter, now fuel real-time betting markets that move fast and pay out even faster.
Take the recent case of Major League Baseball pitcher Luis L. Ortiz. Two of his first pitches in separate games drew scrutiny. Not because they lost the game, but because they lined up perfectly with sudden micro-betting activity. Both were sliders, both missed the strike zone by a mile, and both were bet on to do exactly that.
Was it a fluke? A mechanical issue? Or something more deliberate?
That’s the fundamental gap in current detection models. When one pitch can move money, old- school integrity systems aren’t enough. Leagues need a new playbook to detect manipulation as it happens, not weeks later.
Why Spot Fixing is rising
Match-fixing – the orchestration of entire outcomes – has become increasingly rare in team sports. It’s just too hard to pull off. Spot-fixing, on the other hand, is a growing risk. It’s fast, granular, and often within the control of a single player: a benchwarmer who throws one wild
pitch, a point guard who misses one free throw.
The incentives for such plays are growing. In-play and micro-betting now let fans wager on thousands of split-second events within a single game – whether the next pitch is a strike, or the next serve a double fault. These moments are fast, low-profile, and often disconnected from the main action. That makes them ideal for manipulation and difficult to catch.
What’s more, the spotlight rarely lands on the individuals involved. These are bench players, substitutes, or role-fillers – the athletes whose actions aren’t likely to draw scrutiny from broadcasters, analysts, or fans. They may not make headlines, but in betting markets, their micro-moments have financial weight. That imbalance – low visibility, high value – creates fertile ground for exploitation, especially when the players involved are lower-paid and easier to pressure
That’s why leagues and sportsbooks can’t just focus on final scores or headline bets. Integrity threats now hide in the small moments where scrutiny is low and incentives run high. The next breach won’t make the highlight reel. It’ll happen quietly, unless the data catches it first.
How Spot Fixing signals get missed
What’s notable about the Ortiz case is that it came to light not through a whistleblower, but through data. A betting-integrity firm flagged suspicious wagers on two first-pitch sliders Ortiz threw to Randy Arozarena on June 15 and Pedro Pagés on June 27. Both were bet to be a ball or hit-by-pitch. Both missed the strike zone by a wide margin.
To the naked eye, the pitches may have looked errant but unremarkable. One was borderline. The other was, by most accounts, one of the worst-placed sliders Ortiz had thrown all season. But the real red flag was in the statistical profile. The Pagés pitch, for instance, landed far outside Ortiz’s typical range. And the Arozarena pitch, while less egregious, was thrown with an unusually high arm angle – his highest on a slider all year.
These are the kinds of signals most integrity systems still miss. Many still rely on human observation and after-the-fact reviews, with limited use of real-time performance data. A core issue is fragmentation. Performance metrics – like Statcast, biomechanics, and player tracking – aren’t consistently linked to betting market activity. A wild pitch might be written off as a fluke by team analysts, while sportsbooks flag it for abnormal wagering. But without shared visibility, those signals never meet, and the pattern gets lost.
There’s also the problem of data silos. Leagues, sportsbooks, and third-party monitors often operate on separate systems, with limited data sharing or interoperability. That leaves blind spots, especially around moments that seem routine. And timing matters. Most investigations still happen days or weeks later. In Ortiz’s case, it took close statistical review to spot just how unusual those two pitches were. Both happened early in the game, when scrutiny is low. Both attracted eerily precise betting activity.
If betting alerts and performance data had been cross-referenced in real-time, the pattern might’ve surfaced sooner. Instead, it took weeks before anyone pieced it together, by which point the bets had already been paid out. Spot-fixing depends on these gaps. As the games get faster and bets get more granular, detection must evolve just as quickly.
Building a true Early-Warning System
To stay ahead of spot-fixing, leagues need more than post-game audits and betting alerts – they need an early-warning system that connects the dots before the damage is done.
That starts with granular, real-time monitoring. Sportsbooks already analyze individual bets for odd timing, unusual volumes, or geographic clustering. But without pairing that data with in- game performance metrics – like pitch tracking, player motion, or biometric fatigue – it’s just noise. A pitch that looks off to one system might only raise eyebrows. But cross-referenced with betting behavior, it can tell a very different story. AI-driven pattern recognition is the next layer.
Machine learning can help spot the subtle signals that suggest a fix, not just a missed play. A pitch released at an odd angle, a fatigue marker out of line, a bet surge minutes before an at-bat. Each alone may seem benign, but taken together, they can form a recognizable pattern. These models, which are getting better every year, can also weigh contextual risk – flagging when a player is new, under financial strain, or suddenly attracting unusual betting interest.
Still, machine intelligence isn’t enough on its own. A model can flag something unusual, but only a human can watch a pitch and say, “That’s not just bad. That’s suspicious.” The most effective systems combine automation with human review, using AI to surface anomalies and people to assess intent. That includes separating sharp betting from something more coordinated. Signals like bet velocity, odd timing, and contradiction of public info can hint at insider knowledge, but it takes human judgment to read the full picture.
And finally, it all comes down to cross-sector coordination. Leagues, sportsbooks, and integrity monitors can’t go on operating in silos. They need to talk to each other through interoperable systems and real-time data. That means shared protocols, standardized APIs, and joint integrity teams working across organizations. Detection must move from isolated alerts to systemic cooperation. A single red flag might catch a fix. A shared network could prevent it altogether.
Such coordination already exists in tennis and cricket, where centralized alert platforms fuse betting data with match performance in real time. These systems can flag anomalies mid-game, giving officials a chance to intervene before the damage spreads. It’s not perfect, but it’s faster – and it works.
The challenge now is exporting that model to bigger leagues, faster games, and more complex betting ecosystems. The playbook is out there. What’s missing is the will to adapt it before spot- fixing becomes the new normal.
Closing thoughts
Spot-fixing isn’t just a betting issue. It’s a data problem, a transparency problem, and a coordination problem. And the longer leagues wait to adapt, the more ground they lose. But the tools exist: real-time performance data, AI-driven pattern detection, and cross-sector
coordination.
What’s missing is urgency. If leagues and sportsbooks want to protect the integrity of the game,they need to act now and build systems that can catch unusual signals before they disappear into the noise.
Adam Fiske is the CEO of Dimers, where he leads operations in North America and Australia to enhance the betting landscape in sports. With extensive experience in media, marketing, sports, and wagering, he excels at driving high-performing teams and delivering exceptional customer experiences.
