Bernard Marantelli gives a straightforward explanation of what’s unfolding in US sports prediction markets, cutting through the jargon of contracts and trading. "Kalshi is a sportsbook that’s just not allowed to have an in-house risk team," says the founder of White Swan Data, a firm now active in market-making on prediction exchanges.
The core distinction lies in risk management. While traditional sportsbooks have traders who price bets and manage risk, an exchange operates by providing an API where various firms can compete to set prices and ensure liquidity.
"Here’s an API. Bernard and 88 other people can market-make all these request-for-quotes (RFQs)," explains Marantelli. Market participants may specialize in different areas; some focus solely on esports, while others cover a broader spectrum or specialize in same-game parlays. Nonetheless, it fundamentally operates like a sportsbook.
For the average customer, the complex institutional framework remains largely hidden behind a peer-to-peer model. Although retail users can trade among themselves, the liquidity needed to support a mass-market product cannot rely solely on infrequent customers. Professional firms need to continuously quote prices and allocate significant capital.
White Swan Data claims it constitutes about 40% of the activity on various secondary exchanges, with a significant focus on the RFQ and parlay markets. Marantelli outlines why they prioritize this sector: "Just better margins. I think it’s more defendable. It’s the area that fewer people can do well. So I think it’s more defendable margin, more ability to get long-term contracts and beneficial positions."
While betting on single outcomes can be lucrative, pricing parlays demands a market maker to compute the correlations between multiple results and respond nimbly to individual queries. This capability is developed through years of experience in the more intense realms of the existing sports betting framework.
Marantelli highlights both White Swan and Susquehanna as major players in the parlay market, with other potential leaders including Jump Trading, Mojo, and DL Trading. Beneath them, many smaller syndicates manage between $5 million and $10 million, alongside specialists in certain sports.
The movement of substantial UK and European sharp-betting groups into US prediction markets has been rapid, according to Enda Kendrick, CEO of service provider Veltium. He estimates that over 100 smaller entities, ranging from lone traders to teams of ten, are keen to enter the regulated US market.
However, the involvement of these professional counterparty firms complicates the notion that prediction markets are merely platforms for users to trade opinions. Kendrick points out that two average users are unlikely to place large bets like $10 million or $20 million on teams such as the Philadelphia Eagles. Institutional participation is essential for markets to function at such scales.
Marantelli warns that customers might experience faster losses in exchanges compared to traditional sportsbooks. The chance to enter and exit positions can create a false sense of flexibility, leading users to risk a larger portion of their bankroll. For instance, one might buy a bet on a team at 55 or 56 cents, expecting a rise to 58 or 59 cents. Should the price drop to 45 cents, the trader often holds onto the bet instead of realizing the loss.
"People will lose money faster on exchanges for lots of reasons," Marantelli explains. "It inherently increases spend, volatility, lots of things. And you’re playing against a sharper audience than you’re playing against at the DraftKings sportsbook." He compares this with sportsbook cash-out options which, while appearing to grant customers more control, may also encourage increased spending. The key difference lies in the fact that exchange customers may face specialists who excel at identifying inaccurately priced contracts.
Kendrick signals caution, recalling the early days of betting exchanges. Initially, there was enough retail liquidity for numerous market makers to thrive. As that retail pool declined, sharper firms ended up competing against one another. He draws an analogy to a poker table, where the weaker players sustain the game; if they leave, even the next best player can find themselves at a disadvantage.
Despite these challenges, the potential customer base in the US remains vast, bolstered by strong recruitment efforts. Marantelli reveals that Kalshi expanded its client base fivefold during the World Cup. White Swan estimates that NFL prediction markets could lead to liabilities of between $5 billion and $7 billion within a single week.
However, Marantelli does recognize that quicker customer losses could challenge the model's sustainability. "They lose quicker, dry up quicker, recruitment or re-recruitment," he states. "If the recruitment of players dries up, then what are you going to do? Definitely there can be components like that."
For the moment, the growth of the prediction market space allows multiple market makers to coexist. Marantelli predicts that margins will remain favorable during this growth phase before potentially tightening due to increased competition. More complex RFQ and parlay markets may offer some protection against margin compression.
The landscape appears more like an outsourced sportsbook trading room than a scenario where millions of customers casually exchange predictions. Exchanges facilitate the platform and customer acquisition, while specialist firms assume the risk and supply the necessary capital to maintain market functionality. As Marantelli puts it succinctly, "Let’s call a spade a spade."
