Spotify Confirms Streaming Fraud After Kalshi Trader Cries Foul

New Delhi, India Jul 3, 2026 ALN: Concerns Over Market Manipulation

Top Kalshi trader Caleb Davies usually speaks to the press about how prediction markets help him rake in money. The Minneapolis-based IT worker estimates he’s made $1.2 million overall across different prediction platforms, with $414,000 in winnings from Kalshi’s culture markets alone. He especially enjoys wagering on music charts, because he carefully analyzes Spotify data to pick winners. “Every single morning, I’m going in, downloading the data, and updating my projections,” he says.

This summer, though, he’s become increasingly agitated about what he claims is an obvious, bot-fueled effort to manipulate Spotify-related markets. He recently began compiling and publishing evidence for his theory, eventually becoming so convinced that he contacted Spotify, Kalshi, and Polymarket with his concerns. The implications of such manipulation are significant, not only for the integrity of prediction markets but also for the broader music industry, which relies heavily on streaming metrics for revenue and visibility.

Incident Sparks Investigation

This week, the situation hit a boiling point when the song “Earrings” by Malcolm Todd surged to number one on a Spotify chart. In a series of posts, Davies outlined his suspected culprit: “botting,” or scammers who purchase bots to inflate streaming numbers. This practice, while not new, has gained traction in an era where streaming numbers can dictate chart placements and, consequently, an artist's financial success and career trajectory. Davies argued that prediction market traders were manipulating the charts to influence the outcome of related events contracts. Todd’s song was such an underdog that it wasn’t even listed as an option on Polymarket: “Looking at the dataset of Sunday to Monday changes, it was an 11.24 sigma event, or a roughly 1 in 77 octillion chance of happening randomly,” Davies wrote.

Such extreme statistical anomalies raise alarms about the integrity of the data being used in prediction markets. The reliance on accurate streaming figures is critical for traders who base their wagers on the assumption that the charts reflect genuine listener engagement. If those numbers are artificially inflated, it distorts the market and undermines the trust of participants.

Spotify's Response

It turns out that he was on to something. Spotify confirmed that it investigated the suspected manipulation incidents Davies flagged and found evidence of artificial streaming. “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,” spokesperson Laura Batey says. However, the company didn’t offer any explanation for the manipulation, leaving Davies’ theory that it was directly tied to a scheme to manipulate prediction markets unconfirmed. This lack of clarity raises questions about the effectiveness of Spotify's detection methods and whether they can adequately address the evolving tactics employed by fraudsters.

Adjustments to Streaming Charts

Spotify ultimately adjusted its charts to account for the discrepancy, removing over 500,000 artificial streams, which bumped Todd’s song from first to fourth. The process was not immediate, though, and Kalshi had already resolved the market to award traders who selected Todd’s song. This situation illustrates the potential for significant financial implications for traders who rely on accurate streaming data. In prediction markets, timing is everything, and those who placed bets based on the inflated numbers may feel cheated when the truth comes to light.

“We're in touch with Spotify and are actively investigating this matter,” Kalshi spokesperson Elisabeth Diana states. Those conversations did prompt a more immediate change: at Spotify’s request, Kalshi removed Spotify’s logo from its markets that relate to the company and adjusted language that initially suggested Spotify had verified chart results. This move reflects the sensitivity surrounding brand associations and the need for platforms to maintain a clear distinction between their operations and the data provided by external entities.

Ongoing Investigation and Market Dynamics

When Davies first reached out to Kalshi with concerns, the company’s head of enforcement, Robert DeNault, told the trader that only Spotify would be able to definitively confirm whether it had been botted, and noted that there could be non-suspicious reasons for the uptick. DeNault also floated a theory that Kalshi traders could be merely copying what peers were doing on Polymarket. This highlights the complexity of the prediction market ecosystem, where information can spread rapidly and influence trader behavior in unpredictable ways.

“Nobody from Polymarket profited from the fraud. That’s what undermines Kalshi’s argument, because they didn’t have a Malcolm Todd bracket,” Davies explains. Polymarket refutes this theory as well. “It’s actually not plausible since we didn’t even have Malcolm Todd as an option on this Spotify market,” said spokesperson Annabel Walsh. The company confirmed it’s reviewing the broader streaming manipulation situation but hasn’t identified any immediate manipulation thus far. This lack of consensus among the involved parties underscores the challenges in attributing responsibility in cases of market manipulation, particularly when multiple platforms are involved.

Implications for Prediction Markets

No one has spoken with the individuals or group behind the streaming manipulation, so their motivations remain unclear. (Todd did not respond to requests for comment, but there’s nothing to suggest he’s anything more than an innocent bystander.) What is clear is that this type of market introduces a new incentive for streaming fraudsters. The intersection of music streaming and prediction markets creates a unique environment where the potential for profit can lead to unethical behavior. This year, several high-profile arrests have been made related to alleged insider trading schemes on Polymarket, though none have been tied to streaming charts.

“The platforms are not supposed to list contracts at all unless they make an affirmative determination that they are not readily susceptible to manipulation. It is clear that in this market, and many other markets, they are not doing that,” says Amanda Fischer, a former Securities and Exchange Commission chief of staff and the policy director and chief operating officer of the Wall Street watchdog nonprofit Better Markets. “They’re obviously readily susceptible to manipulation.” This statement highlights the need for stricter oversight and regulatory measures to protect the integrity of prediction markets. Without such measures, the potential for abuse could undermine the trust of participants and the viability of these markets as a whole.

As for Davies, for now, he’s swearing off chart-based markets. “They've been a big gainer for me historically, but I can't play it anymore,” he concludes. His decision reflects a broader sentiment among traders who may feel disillusioned by the recent events and the potential for manipulation. The future of prediction markets may depend on how effectively platforms can address these concerns and restore confidence among their users.