The competition in prediction markets is becoming increasingly apparent, with companies like Kalshi, Polymarket, and various newer participants broadening their sports offerings. At the same time, established names such as DraftKings, Flutter, and Robinhood are making significant investments in exchanges, distribution, and market-making capabilities.
Behind these brands, a new sector is rapidly emerging. Data providers, specialist market makers, and technology firms are entering the fray.
According to a report by investment banking and capital markets firm Jefferies issued in September, sports have become the main liquidity driver in prediction markets. The report highlights that combo and parlay-style contracts are responsible for an increasing portion of market activity. However, the analysts noted that prediction markets function as scale businesses with relatively low revenue yields, making them reliant on consistent liquidity, engagement, and trading activity.
The connection between data and liquidity is crucial. James Monk, founder of the sports data and streaming company Catalist Sports, has experienced this firsthand. Catalist supplies data for ITF tennis to Kalshi and Polymarket and maintains an exclusive agreement with Kalshi for US sports streaming.
Catalist must also provide data to market-making firms that operate on these events. Monk explained, "If we just sold the data to Kalshi in order to list the markets but no one was coming in and placing liquidity, there’s no point in them listing the markets. We also need to supply the data to the market makers to inform their models."
Initially, Catalist received a list of fewer than ten potential market makers from Kalshi. Over time, it has successfully established agreements with nearly 20 and is actively engaging with around another 20.
This growth reflects a rise in the number and diversity of sports contracts. ITF tennis, for example, relies heavily on official data, as over 60,000 matches held annually are typically not broadcasted. Monk mentioned that it would be challenging to unofficially monitor a tour that moves between locations as varied as Bogotá and Bali.
The integration of streaming technology is also evolving. Monk noted that the interfaces for prediction markets have transitioned from a focus solely on trading to include streams, player propositions, and combinations similar to sportsbook bet builders. "The actual product offering has come a long way," he stated, referencing Kalshi's early user experience at the start of this year.
The emerging market makers play a pivotal role in this ecosystem. Andrew Gonzalez, founder of ParlayX, a prediction market infrastructure startup, highlighted that even small teams can effectively provide liquidity. He remarked, "Anyone can be a market maker. You have these two- or three-man shops."
Jefferies characterized market makers as the "liquidity backbone" of the prediction market ecosystem. These firms post executable bids and offers, manage their inventory, and ensure balanced pricing when customer activity skews. The analysts estimated that a market operator capturing a one-cent spread while effectively managing exposure could yield net economics of about $1.69 on a $100 trade. However, these returns are not guaranteed; unfavorable price shifts and unresolved inventory can negate or even exceed revenue from spreads, rebates, and liquidity incentives.
Yet, the operational infrastructure for these new market makers is still developing. Gonzalez compared prediction markets to equities, where trading firms can rely on prime brokers, clearinghouses, and standardized systems like FIX. "When it comes to prediction markets, none of that exists," he said, noting that many developers are starting from scratch.
The platforms are generally designed for individual users operating single accounts rather than trading organizations that require multiple permissions and controls. According to Gonzalez, some teams still function with a single login credential.
To address these gaps, ParlayX is implementing features such as individual logins and delegated permissions. Challenges also include inconsistent execution across exchanges, a lack of prime brokerage services, and varying contract resolution standards. A contract bought on Kalshi, for instance, cannot be simply transferred to Polymarket, even if both markets cover the same event outcome, as each exchange defines and resolves contracts differently.
Liquidity can become a self-reinforcing cycle. Market makers are drawn to platforms that offer reliable technology and substantial order flow; their involvement, in turn, enhances pricing and execution for consumers. Sahil Patel, founder of Aldrin AI, a competitive intelligence provider, noted the importance of these dynamics in Kalshi’s success. "A lot of market makers want to go where there’s liquidity," he said, emphasizing the significance of platform stability and Kalshi’s investment in its relationships with market makers.
Aldrin tracks product changes, advertising, social media engagement, app store rankings, and trading volumes across prediction market operators. Patel explained that the aim is to correlate these indicators to demonstrate how advertising-supported product launches influence volume and market share. Beneath the larger exchanges, numerous operators are competing for minimal shares in this fast-growing category. Patel expressed that a 1% market share represents a substantial opportunity, with many vying for that slice.
Jefferies estimated that exchanges can retain around 65% of transaction fees, distributing the remainder to clearinghouses, brokers, and liquidity providers. As a result, it anticipates that more operators will start bringing parts of their infrastructure in-house.
For independent suppliers emerging alongside these developments, each new exchange, contract, and market maker represents an expanding opportunity. Although consumer-focused platforms draw in users, successful trading at scale relies heavily on the data, liquidity, and operational systems operating behind the scenes.
