The Spotify Stream-Bot Betting Scandal: Can Markets Incentivize Real-World Manipulation?
On the last Monday of June, a Malcolm Todd single that had spent weeks parked at No. 4 on Spotify’s US chart jumped nearly 70% in a single day and hit No. 1 for the first time. The surge did not come from a viral moment. It came from more than 500,000 artificial streams, and it landed at the exact moment a roughly $3 million Kalshi market on June’s most-streamed song needed a winner. The Spotify stream-bot betting scandal is the clearest case yet of the question regulators have been dancing around for two years: when you let people bet real money on a real-world number, do you also hand them a reason to rig the number?
What Happened in the Spotify Stream-Bot Scandal?
Spotify removed more than 500,000 fake streams that had briefly pushed Malcolm Todd’s “Earrings” to No. 1 in the US, days after Kalshi settled and paid out a $3 million market on June’s most-streamed song using the inflated numbers. The Financial Times broke the story, and the short version is ugly: the fake streams decided the market, the market paid the winners, and only then did the chart get corrected.
“Earrings” was not some obscure track that materialized out of nowhere. It first appeared on Todd’s 2024 mixtape Sweet Boy, and Columbia sent it to US pop radio on April 14, 2026 after months of organic growth. By late June it was a fixture in the top five of Spotify’s daily US chart. Then came the spike, and the correction that followed it. Here is the verified timeline:
| Date | What happened |
|---|---|
| June 28-29 | US streams of “Earrings” jump nearly 70% overnight, lifting the song from No. 4 to No. 1 on Spotify’s daily US chart for the first time |
| June 30 | Kalshi’s market on the most-streamed Spotify song in the US for June, with about $3 million traded, settles on the inflated data; winners are paid within hours despite trader warnings |
| July 1-2 | Spotify strips 500,000+ artificial streams and re-posts corrected charts; “Earrings” falls back to No. 4 |
| July 2 | Bloomberg reports Spotify sent notices demanding Kalshi and Polymarket remove its logo and clarify that no partnership exists |
| As of this writing | Kalshi says it is “in touch with Spotify” and actively investigating; no refunds announced, no manipulator publicly identified |
Two things are worth stating plainly. First, nobody has suggested Malcolm Todd or his label had anything to do with the fake streams; every indication is that the song was picked opportunistically because it was already close to the top. Second, nobody has been publicly identified as the buyer of those streams. The link between the botting and the betting is circumstantial, but as circumstantial evidence goes, half a million fake plays landing on settlement weekend is about as subtle as a foghorn. CBS News has a clean rundown of the removal and the investigation.
How Fake Streams Turned Into Real Betting Profits
The economics were brutally simple: buying roughly half a million bot streams costs a fraction of what a longshot position in a $3 million market pays out when it hits. Kalshi, the prediction market regulated by the Commodity Futures Trading Commission, runs dozens of contracts tied to Spotify and Billboard chart results. Its music markets are not a niche sideshow anymore. Company figures put music trading above $400 million in 2026, up from roughly $70 million in all of 2025, with more than $100 million traded on the first song of Bad Bunny’s Super Bowl halftime show alone.
Here is how the trade worked, based on the reporting so far:
Step one, take the cheap side. In the week before the surge, Kalshi traders priced the chances of “Earrings” finishing June at No. 1 below 3%, according to Bloomberg. That means “yes” contracts were selling for pennies on the dollar.
Step two, move the metric. The market settles on Spotify’s published streaming data. Flood the song with enough bot streams on the final days of the month and the published number moves. The song was close enough to the leaders that 500,000-plus streams could flip the outcome.
Step three, collect before anyone checks. Winning positions returned roughly 20 to 30 times the stake per Bloomberg’s reporting, and Kalshi paid out before Spotify’s fraud team finished its math. The FT noted the potential winnings on a play like this can dwarf what the fake streams cost to buy.
If you want the mechanics of why settlement source matters this much, our guide to how event contract settlement works covers the plumbing. The one-sentence version: an event contract is only as trustworthy as the data feed it resolves against, and this market resolved against a number that turned out to be partly fiction.
The Trader Who Saw It Coming
The manipulation was not flagged by Spotify, Kalshi, or any regulator. It was flagged by a bettor. Caleb Davies, a music-chart trader who says he has made more than $1 million on Kalshi, watched the Sunday-to-Monday jump and immediately called it out as statistically absurd.
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An 11.24 Sigma Event
By Davies’ analysis, the stream spike was an 11.24 sigma outlier: roughly a 1 in 77 octillion chance of happening naturally. For context, the song was such a longshot that Polymarket had not even bothered listing it as an option in its own chart market.
Davies says he warned Kalshi before the June results posted and publicly asked the exchange to delay settlement until someone verified the streams were real. Kalshi paid the market out within hours anyway, and Davies, who held the other side, lost $4,500 on the outcome. Spotify’s correction two days later proved his read correct: strip the fake plays and “Earrings” finishes fourth, not first.
That sequence is the part of this story that should bother you most if you trade these markets. The red flag was public, specific, and raised before settlement, and the money still went out the door. We compared the two biggest venues in our Kalshi vs. Polymarket breakdown, and settlement discipline is exactly the kind of thing that separates platforms when something goes sideways.
Can Prediction Markets Incentivize Real-World Manipulation?
Yes. A betting market creates a manipulation incentive whenever three conditions line up, and the Spotify stream-bot betting scandal hit all three:
The settlement metric can be moved. A market on tomorrow’s high temperature settles on physics. A market on a streaming chart settles on a number that anyone with a bot farm can push. Fake streams are an established, cheap, industrial-scale product.
Moving it costs less than the payout. Longshot prices are the fuel. At sub-3% implied odds, every dollar staked on “yes” returned 20 to 30 dollars. When the cost of rigging the metric is lower than the prize for being right about it, the market is quietly funding its own corruption.
Settlement outruns verification. Spotify’s fraud detection worked. It just worked on a Wednesday for a market that paid out on Tuesday. Any gap between “number published” and “number verified” is a window a manipulator can drive through.
Sports betting has spent decades learning this exact lesson, which is why the parallel is so uncomfortable. When former NBA player Jontay Porter pleaded guilty to a federal wire fraud conspiracy, the scheme was structurally identical: take a position on a market (unders on his own prop lines), then manipulate the real-world input (pull himself out of games early) so the position cashes. The NBA banned him for life. The difference is that corrupting an athlete is expensive, risky, and leaves a human witness. Renting a stream farm is none of those things.
Music has its own long history here, from the payola scandals of the 1950s to modern chart gaming. What is new is the direct financial instrument: a liquid, legal, US-regulated market where a stranger can put serious money on a specific song topping a specific chart by a specific date. The moment that market existed, the incentive existed.
Why Music Charts Are Such a Soft Target
Streaming numbers are uniquely easy to fake because the underlying action is free, anonymous, and infinitely repeatable. Nobody has to corrupt an insider or fix a game. A script pressing play on a loop does the job, and there is a mature gray-market industry selling exactly that.
The scale of that industry is not hypothetical. In March, a North Carolina man named Michael Smith pleaded guilty in federal court to a streaming fraud scheme that used AI-generated songs and armies of bot accounts to rack up billions of fake streams between 2017 and 2024, siphoning more than $10 million in royalties. He agreed to forfeit $8.09 million and is scheduled for sentencing on July 29. That case established the template: stream botting at scale is real, profitable, and prosecutable as wire fraud.
Spotify, for its part, says the system caught what it was supposed to catch. “All streaming services face ever-changing stream manipulation. Spotify has best in class detection and mitigation practices for manipulated streams, and we don’t pay out associated royalties,” the company said in its statement on the incident. It has also said it will add extra checks to charts before they publish. Both things can be true: the detection worked, and it still was not fast enough to protect a market that settled on the raw number.
What This Means If You Trade Prediction Markets
The practical lesson is that settlement risk is a real cost of trading event contracts, and it is not priced into the odds you see on screen. Before you put money on any market, ask what data source resolves it, whether that source can be gamed, and what the exchange does if the source gets corrected after the fact. In this case the answer to that last question was: nothing yet.
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Settlement Risk Is Your Risk
Kalshi settled this market on numbers Spotify later retracted, and as of this writing no re-settlement or refund has been announced. Until platforms adopt clear correction policies, traders on the wrong side of a manipulated settlement eat the loss.
A few habits worth building if you trade these markets:
- Favor hard-to-fake settlement sources. Election results and game scores are publicly verified events. Privately measured engagement metrics (streams, views, downloads) are the softest targets on the board.
- Treat weird late moves as information. A longshot surging right before settlement is sometimes news. Sometimes it is someone spending money to make the news. Davies spotted this one from the data alone.
- Know the platform’s correction policy before you need it. If the rulebook does not say what happens when a data source retracts its numbers, assume the settled result stands.
- Size positions like the settlement can break. Because occasionally it can.
None of this means event contracts are a scam; we have covered the genuine strengths of the category in our look at whether prediction markets are safer than sportsbooks. It means they carry a failure mode sportsbooks mostly do not, because a sportsbook settling a Lakers game does not depend on a private company’s unverified engagement dashboard.
The Questions Nobody Has Answered Yet
The biggest open question is accountability, and every part of it is unresolved as of this writing. Kalshi’s full public statement remains one sentence: “We’re in touch with Spotify and are actively investigating this matter.” Nobody has been identified, no re-settlement has been announced, and no regulator has said a word publicly.
The unresolved list is worth laying out, because how these get answered will shape whether entertainment markets stay viable:
- Does Kalshi make anyone whole? Traders who lost when the fake No. 1 settled, including Davies, are out real money on a corrupted result.
- Who investigates the manipulation itself? Botting streams to win a bet plausibly crosses the same wire fraud lines the Smith case did, but someone has to connect the wallet to the bots.
- Does Spotify want this business to exist at all? Demanding your logo come off two exchanges is not a partnership posture. If data providers start treating markets on their metrics as a liability, the category shrinks.
- Do exchanges slow down settlement? A 48-hour verification window on manipulable metrics would have caught this one. It would also make the product less fun, and fun is the product.
Our bet, editorially speaking: music markets are too big for the exchanges to walk away from, so expect verification windows, tighter settlement language, and probably a quiet make-good long before anyone admits fault. The incentive problem is harder. You can patch a settlement rule; you cannot patch the fact that a market on a gameable number is an open invitation, and the next person to accept it will be less clumsy about the timing.
For a grounding in how this corner of the betting world works before you touch it, start with our prediction markets guide.
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Frequently Asked Questions
The Spotify stream-bot betting scandal sits at the intersection of streaming fraud, prediction markets, and betting integrity, and readers have been asking the same handful of questions. Here are direct answers based on what has been verified so far.
What is the Spotify stream-bot betting scandal in plain terms?
Someone used more than 500,000 bot streams to push Malcolm Todd’s song Earrings to No. 1 on Spotify’s US chart at the end of June 2026, right as a Kalshi prediction market worth about $3 million settled on which song finished the month on top. Kalshi paid out winners based on the inflated numbers, and Spotify removed the fake streams days later, dropping the song back to No. 4. Nobody has been publicly identified as the manipulator, and there is no evidence the artist was involved.
Did Kalshi refund bettors after the manipulated Spotify market settled?
No. As of this writing, Kalshi has said only that it is in touch with Spotify and actively investigating. The market settled and paid out before Spotify corrected its charts, and no re-settlement or refund has been announced. Traders who held losing positions on the corrected outcome have absorbed the loss so far.
Is botting streams to win a prediction market bet actually illegal?
Federal prosecutors have already treated large-scale streaming fraud as wire fraud. In March 2026, Michael Smith pleaded guilty in the Southern District of New York after using AI-generated songs and bot accounts to fake billions of streams and collect over $10 million in royalties. Using the same botting technique to rig a regulated betting market would add a market-manipulation dimension on top, though no charges have been filed in the Kalshi case yet.
Could the same kind of manipulation happen with sports betting markets?
It already has, just through a different door. Former NBA player Jontay Porter pleaded guilty to a wire fraud conspiracy after leaving games early so co-conspirators could cash bets on his unders, and the NBA banned him for life. Game scores themselves are publicly verified and hard to fake, which is why sports manipulation targets individual performance and insider information instead of the scoreboard.
How do Kalshi’s music chart markets decide who gets paid?
They settle against Spotify’s published streaming data, such as the most-streamed song in the US for a given month. That design is the core vulnerability this scandal exposed: the market resolves on the number as published, and if fake streams inflate that number before Spotify’s fraud detection catches up, the wrong side of the market can get paid. Kalshi is regulated by the Commodity Futures Trading Commission as a designated contract market.
