Overview
Executive Summary
Cardi B wasn't the only one making "money moves" ahead of this year's Super Bowl: so did thousands of traders on prediction markets.1 Before the big game, approximately $57 million in trading volume was tied to a single, seemingly straightforward question: would Cardi B "perform" at the Super Bowl?2 The answer, unfortunately, was not so clear. As the millions who watched know, Cardi B did appear during Bad Bunny's halftime show—but she only appeared briefly in the background and did not have a microphone. So did she "perform" or not? As a result of this lack of clarity, prediction market platforms like Kalshi and Polymarket were forced to confront how to resolve millions of dollars in event contracts tied to what had been framed as a binary question but was, in fact, much more nuanced.
The episode highlights a basic feature of prediction markets: users are trading against one another (rather than against 'the house') and when contract terms are unclear, bettors will inevitably feel wronged. In a high-volume market, that dissatisfaction can quickly translate into reputational harm, regulatory scrutiny, or even legal exposure.
The Cardi B bet has laid bare the fact that as prediction markets gain popularity, clear, comprehensive drafting of event contract terms will be critical as prediction markets continue to expand into high-profile cultural and sporting events.
More than Checks – How Prediction Markets Work
Prediction markets are trading platforms that allow users to buy and sell contracts tied to the outcome of future events. Unlike traditional sportsbooks, participants are not wagering against a casino. Instead, they are taking opposing positions against one another.3
Most prediction markets are structured around seemingly simple, binary questions. A contract typically resolves to a fixed amount — often $1 — if a specified event occurs, and $0 if it does not. For example, one of the most prominent US-based platforms, Kalshi, lists event contracts tied to economic indicators, political developments, and sporting outcomes. A contract might ask whether the United States will win a gold medal in a particular Olympic event. Traders can purchase 'Yes' shares if they believe the US will win, or 'No' shares if they believe it will not. If the specified outcome occurs, 'Yes' shares pay out at $1 and 'No' shares expire as worthless.
Prices fluctuate as users buy and sell positions, reflecting the market's collective assessment of the probability of the event. In theory, the structure is straightforward: a clearly defined event, a binary outcome, and a predefined resolution source.
But that apparent simplicity depends entirely on how the event is defined. When the triggering term is ambiguous — such as whether an artist performed — the yes-or-no framing can obscure significant interpretive risk.
When "Binary" Isn't So Clear — Millions on the Line with no Obvious Winner
The Cardi B contract exposed how quickly a seemingly simple yes-or-no event can become a dispute when millions of dollars are wagered and definitions are unclear.
Leading up to Super Bowl Sunday, Kalshi's "Who will perform at the Big Game?" market amassed more than $47.3 million in trading volume, while a similar contract on Polymarket saw over $10 million traded.4
During Bad Bunny's halftime show, Cardi B appeared briefly, dancing and mouthing lyrics alongside other entertainers. But she did not audibly sing, have a microphone, or play an instrument. A seemingly straightforward question became complicated: was this a performance?
Polymarket resolved its contract in favor of "Yes," determining that Cardi B's live, in-person presence qualified as a "performance" under its rules.5
Kalshi, however, interpreted its own terms more conservatively: its rulebook specified that "dancing or appearing on stage without singing/playing instruments" did not qualify as a performance.6 Faced with ambiguity about whether Cardi B actually sung, Kalshi invoked a rule that gives the platform sole discretion to settle contracts when there is an ambiguity not addressed by the rules.7 Ultimately, Kalshi froze trading and settled the contract at its last traded price, $0.74 for "No" holders and $0.26 for "Yes" holders, effectively paying partial value to both sides of the market. In other words, a trader who purchased $20 worth of "No" contracts would have received $14.80 back, regardless of the price at which those contracts were originally purchased.
Kalshi's decision—particularly its invocation of a clause giving the platform discretion in unresolved cases—drew backlash from users. One Kalshi trader who backed "Yes" has since filed a complaint with the Commodity Futures Trading Commission (CFTC), alleging that Kalshi's settlement violated the Commodity Exchange Act and seeking roughly $3,700 in damages.8 The CFTC, however, was quick to distance itself from the dispute, emphasizing that prediction markets operate pursuant to their own self-governing rulebooks—frameworks that are not drafted, mandated, or dictated by the agency.9
The split resolution and resulting dispute underscore the challenge: even among sophisticated platforms, interpretation of key terms can diverge materially. While Cardi B's Super Bowl cameo may have felt like a 'one of one' moment, prediction markets are uniquely susceptible to ambiguity when fluid cultural events are shoehorned into rigid equations. Co-recipients of an award (as when Peyton Manning and Steve McNair shared the NFL Most Valuable Player Award in 2003) can transform what would otherwise be a moment of shared achievement into a contract interpretation battle. The same dynamic arises outside of sports, where, for example, prediction markets may ask whether one actor or another will cameo in a popular film or series—if both ultimately appear, the market can yield multiple plausible 'correct' outcomes but only one contractual payout. Where one market operator sees sufficient evidence to pay out, another may see ambiguity necessitating discretionary settlement; and participants on the losing side may challenge that outcome through regulatory or legal channels—either alone or via a class action dispute.
No Time for Hail Marys – Managing Regulatory and Contract Risk
The divergent resolutions by Kalshi and Polymarket illustrate more than a disagreement over semantics. They underscore how ambiguity in high-volume event contracts can quickly evolve into regulatory and legal risk.
That risk is heightened in the current enforcement environment. In May 2025, the Department of Justice's Criminal Division announced that it will prioritize fraud that victimizes US investors, individuals, and markets, emphasizing that complex frauds can weaken market integrity and devastate investors.10 As discussed in Steptoe's February 11, 2026 Client Alert, US Attorney Jay Clayton of the Southern District of New York (SDNY) (previously the head of the US Securities and Exchange Commission) recently anticipated an uptick in prosecutions in the prediction markets, noting that prediction markets are not "insulated from fraud."11 Prediction markets are not traditional securities markets, but they involve real capital, retail participants, and public-facing event contracts. If users believe contract terms were unclear or resolution was inconsistent with disclosed rules, disputes can quickly take on the character of investor harm.
The structural reality of the prediction market is that every contract produces a winner and a loser. When significant trading volume turns on an undefined term, the losing side has both incentive and opportunity to escalate complaints—whether through regulators, litigation, or public pressure.
For operators, the lesson is to eliminate ambiguity before trading begins. Practical steps include:
- Defining key terms with specificity. Where a contract turns on the occurrence of a particular event, the rules should clearly articulate the objective criteria for resolution; identify the controlling evidentiary sources; and disclose in advance how ambiguities will be handled, including whether trading may be paused, reviewed, or settled pursuant to discretionary provisions.
- Incorporating mandatory, non-class arbitration provision in user agreements. Properly structured clauses can require individual arbitration of disputes, waive class and collective actions, and establish defined procedures for challenging contract resolution decisions—thereby limiting downstream litigation risk even where ambiguity arises.
Critically, however, an arbitration provision is only as enforceable as the method used to obtain user assent. Operators should ensure their online terms of service comply with best practices governing enforceability, including clear and conspicuous presentation, affirmative clickwrap acceptance mechanisms, and thoughtful design choices—such as language clarity, placement, font size, color, underlining, and hyperlink visibility—to reduce the risk that a court later finds the arbitration clause procedurally deficient.
- Identifying authoritative resolution sources in advance. Broadcast footage, official event announcements, or designated third-party verification should be expressly prioritized.
- Limiting discretionary settlement provisions. Broad discretion may provide flexibility, but it can invite scrutiny if exercised in high-profile markets.
- Stress-testing contracts against edge cases. Surprise appearances, partial participation, or ambiguous on-stage roles should be contemplated and addressed before markets open.
As prediction markets continue to expand into high-profile sporting and cultural events, clarity and completeness in contract drafting will be essential to maintaining credibility and mitigating regulatory and litigation exposure—particularly in an enforcement climate focused on protecting US investors and market integrity.
In markets framed as binary, precision is the playbook.
1 Cardi B, "Bodak Yellow," Invasion of Privacy (2017)
2 Jay Cohen, Cardi B's cameo in Bad Bunny's Super Bowl halftime show leads to dispute on prediction markets, AP News (Feb. 11, 2026), https://apnews.com/article/super-bowl-kalshi-cardi-b-bad-bunny-d3b51d8848934d69c39ff92fa2c51278.
3 See, e.g., Polymarket US Overview, Polymarket US Documentation, https://docs.polymarket.us/polymarket-learn/home (last visited Feb. 11, 2026).
4 Cohen, AP News (Feb. 11, 2026).
5 Who Will Perform at Super Bowl Halftime Show?, Polymarket, https://polymarket.com/event/who-will-perform-at-super-bowl-halftime-show (last visited Feb. 11, 2026).
6 Will <performer> Perform at <event>? Rulebook: PERFORM, Kalshi, at 1–2 (defining "performs") (on file with author).
7 Danielle Abril, Prediction-Market Platforms Kalshi and Polymarket Spar Over Whether Cardi B "Performed" at the Super Bowl, Business Insider (Feb. 9, 2026), https://www.businessinsider.com/kalshi-polymarket-cardi-b-performance-super-bowl-2026-2.
8 Ryan Phillips, Cardi B Super Bowl Prediction Market Dispute Draws Scrutiny, CBS News (Feb. 10, 2026), https://www.cbsnews.com/news/cardi-b-super-bowl-prediction-market-dispute/.
9 New CFTC Chairman Michael Selig on How to Regulate Prediction Markets, YouTube (Feb. 12, 2026), https://www.youtube.com/watch?v=K_Q9jv088Sw.
10 Matthew R. Galeotti, Head of the Crim. Div., US Dep't of Justice, Memorandum to All Criminal Division Personnel, Focus, Fairness, and Efficiency in the Fight Against White-Collar Crime (May 12, 2025).
11 Jessica Corso, SDNY Chief Says Office Has Eye On Prediction Markets, Law360 (Feb. 5, 2026), https://www.law360.com/whitecollar/articles/2438607.
