Prediction Markets Challenge EBITDA at Caesars, Penn, DraftKings

Prediction markets pose a threat to more-established US gaming companies, with aggressive newcomers jockeying to shift popular event-contracts away from Caesars, Penn, MGM and others. The risks to Ebitda and credit profiles are concentrated among operators with higher digital exposure and capital needs. While Caesars and Penn have more skin in the game when it comes to online revenue, MGM's diversification mitigates risk. Regulatory rulings are a swing factor that could support online players of DraftKings and Flutter. Bloomberg Intelligence Senior Credit Analyst Jody Lurie joins Paul Sweeney and Scarlet Fu on "Bloomberg Intelligence" to talk about the weigh of prediction markets on gaming bonds. It was the fourth quarter of the Pinstripe Bowl at Yankee Stadium on Dec. 27 when Penn State defensive end Dani Dennis-Sutton darted between two hapless blockers and sacked Clemson quarterback Cade Klubnik. Or as the game announcer described it: “Dennis-Sutton wraps him up and turfs him!”

This was good news for Penn State fans, en route to a 22-10 win. It might have been even better for the traders on prediction market platform Kalshi who’d wagered that the announcer would say the word “turf.” At 3:18 p.m., right after Dennis-Sutton’s sack, the market’s odds on “Yes” surged from 25% all the way up to 99%, indicating a surefire win.

But Kalshi ultimately resolved the turf market to “No,” ruling that the announcer’s utterance didn’t count. Many traders complained, but the rules were the rules: According to Kalshi’s policy at the time for so-called mention markets such as this one, “tense inflections” on verbs didn’t count. (For the market to have paid out, the announcer would have had to use “turf” as a noun or say something like, “He sure did turf him.”)

There’s a term in the prediction market community for a bet that resolves unfairly on a technicality: a “rulescuck.” (We’ll tell you the full etymology when you’re older.) The turf rulescuck — one influential trader classified it in the subcategory of “verbcuck” — was just one of many disputes Kalshi users have debated on the platform’s Discord channel in recent months. Should homophones count? What about words spoken as part of proper nouns or URLs? How about mispronunciations, acronyms, abbreviations, compound words and foreign-language terms?

In early March, Kalshi tried to clear up the confusion by releasing a new set of rules for mention markets. The guidelines, which stretch to seven pages, settled some long-running disputes: Verbs that are spelled the same as plural nouns do count. (Too little, too late for the “turfs” gang.) Acronyms (“AI”) count except when uttered in their expanded form (“artificial intelligence”). Plurals count if the given word is singular, but singulars don’t count if the given word is plural. Numbers count only when spoken exactly, not as part of a larger number.

On the surface the rules document is a curious, even amusing, glimpse into a flavor of lawyerly hairsplitting. But it also reflects the broader challenge prediction market platforms face in their attempt to reduce reality to a series of yes-or-no bets: Kalshi and its rival Polymarket pitch themselves as sources of truth, but the truth is often hard if not impossible to establish. Many of the best-known disputes involve angels-on-a-pinhead-type debates: Did Cardi B “perform” at the Super Bowl? Did Ukrainian President Volodymyr Zelenskiy wear a suit? Did the US “invade” Venezuela?

The language disputes are even narrower, and Kalshi’s new rules are its latest attempt to set the terms. But linguists interviewed for this story say the English language isn’t easily wrangled to such ends. To them, Kalshi’s rules lacked consistency and foundation, all but guaranteeing more Discord debate.

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