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Market News

Spotify Just Caught Someone Using Bots to Rig a Chart β€” and Win a Bet

A song surged to number one on fake streams. A prediction market paid out before Spotify caught it. The episode revealed a structural flaw that the industry will have trouble explaining away.

Market MunchiesΒ·Jul 3, 2026Β·5 min read
Spotify Just Caught Someone Using Bots to Rig a Chart β€” and Win a Bet

The strange case of "Earrings" has a simple, uncomfortable takeaway: Spotify's chart was gamed, and a prediction market paid out before the correction landed.

Spotify confirmed this week that more than 500,000 artificial streams had pushed Malcolm Todd's song "Earrings" to number one on its US daily chart, only to be stripped once the fraud was uncovered, sending the song back to fourth place. By then, a Kalshi market tied to Spotify's June chart results had already settled and paid out β€” based on the fraudulent data. Nobody has proven who bought the fake streams, or why. There is no evidence that Todd or his team were involved. But the episode exposed a problem prediction markets are going to have to confront: when a financial bet is tied to a gameable metric, the bet itself can become an incentive to game it.

Why it matters: Prediction markets are expanding rapidly into culture, sports, and entertainment. Those markets depend on clean, reliable data. If the underlying data can be cheaply manipulated, the contracts tied to that data become easier to game β€” and the financial incentive to do so grows with the size of the market.

What happened on Spotify

"Earrings" surged approximately 70% in a single day, vaulting from fourth to first on Spotify's daily US chart. The jump was so statistically improbable β€” roughly one in 77 octillion by chance, according to the trader who flagged it β€” that Caleb Davies, a professional prediction market trader who follows Spotify chart data to place bets on music-related contracts, presented his findings directly to Spotify.

Spotify investigated, confirmed that the streams were artificial, and stated that it does not believe they came from genuine listeners and that it does not pay royalties on manipulated plays. The streams were stripped, the song fell back to fourth, and Spotify demanded that Kalshi remove its logo from the platform and make clear that no partnership exists between the two companies. Spotify also said it would add additional checks before publishing its charts in the future.

Why Kalshi got dragged in

The Kalshi market tied to which song would be the most-streamed in the US in June had attracted approximately $3 million in bets. It had already been settled and paid out based on the fraudulent chart data before Spotify's investigation concluded. Kalshi said it is actively investigating. Some long-shot bettors appear to have earned substantial payouts on the manipulated result, while traders on the other side took losses.

Kalshi is federally regulated as a derivatives exchange, even as state regulators argue some of its contracts amount to unlicensed gambling. The CFTC designated it as a contract market in 2020. Its COO said in late April that music-related contracts had already topped $400 million in trading volume in 2026 alone. Combined monthly trading volume on Kalshi and Polymarket rose from less than $5 billion in September 2025 to roughly $24 billion in April 2026, according to Pew Research Center data. This is not a niche internet experiment. It is a fast-growing financial market, and the scale is what makes the structural problem matter.

Why this is bigger than one song

The core vulnerability is this: prediction markets work best when bettors are trying to predict outcomes they cannot cheaply control. Spotify streams are different. They can be purchased. A bettor holding a large position on a song reaching number one has a direct financial incentive to make that happen β€” by buying artificial streams to push the metric higher and hoping the market settles before the data gets corrected.

This is meaningfully different from trying to influence an election or a macroeconomic indicator. Those outcomes involve millions of actors and are expensive to move. A music chart depends on stream counts that can be manufactured at relatively low cost, with the potential return on a well-placed prediction market bet far exceeding the cost of the fraud.

The episode lands at a sensitive moment for the industry. Kalshi is federally regulated, but state regulators are actively challenging it. A Michigan judge blocked Kalshi from offering sports-event contracts in the state as recently as June 29, with Kalshi arguing it falls under exclusive CFTC jurisdiction. The platforms have been striking partnerships with major news networks and awards shows to embed themselves in mainstream culture. A caper involving a pop song and half a million fake streams gives skeptical regulators a cleaner market-integrity argument than they have previously had.

The risk is not limited to music. Box office results, app store rankings, social media metrics, and awards voting can all become targets if markets tied to those outcomes grow large enough. The surface area for this kind of manipulation expands every time a new category of cultural or commercial outcome gets a tradable contract.

What to watch

  • Kalshi's investigation: Watch whether the platform tries to claw back payouts from traders found to have participated, and whether it changes how quickly it settles markets tied to third-party data before allowing time for external verification.
  • Regulatory response: State regulators were already challenging prediction markets on gambling grounds. This episode gives them a cleaner market-integrity argument. Watch whether it accelerates enforcement action.
  • Spotify's chart security: Spotify says it will add more checks before publishing charts. The question is whether those measures prevent future manipulation or simply catch it after markets have already settled.
  • Copycat attempts: The mechanics of this scheme are now public. Watch whether similar manipulation appears in other outcome categories β€” box office results, app rankings, social metrics β€” as prediction markets expand into new areas.
  • Industry partnerships: Prediction markets are pursuing mainstream cultural legitimacy through media deals and awards show integrations. Incidents like this make that pitch considerably harder.

The bottom line

Spotify confirmed the streams were fake. Kalshi paid out before the correction. The suspected motive is financial gain through prediction-market manipulation. The bigger issue is that markets tied to gameable cultural data are vulnerable by design.

Prediction markets have built their credibility on the argument that aggregating many bettors' views produces accurate information about the future. That argument depends on bettors trying to predict what will happen β€” not paying to make something happen that would not have happened otherwise. When the bet creates a financial incentive to manufacture the outcome it tracks, the whole premise breaks down.

The infrastructure to detect and prevent that kind of manipulation is still catching up with the speed at which these markets are expanding. Until it does, every outcome that prediction markets track is also a target.

Sources