The competition in prediction markets has become increasingly evident as companies like Kalshi and Polymarket expand their offerings, particularly in sports. Meanwhile, major players such as DraftKings, Flutter, and Robinhood are investing in exchange capabilities, distribution, and market-making resources.
This burgeoning market has given rise to an emerging sector comprising data providers, streaming services, specialized market makers, and tech firms.
According to a September report by investment banking and capital markets firm Jefferies, sports have emerged as the primary liquidity driver in prediction markets. Notably, combo and parlay contracts are capturing a larger share of market activity. However, analysts point out that prediction markets operate with relatively low revenue yields and depend heavily on consistent liquidity, user engagement, and trading volume.
James Monk, founder of Catalist Sports—a provider of sports data and streaming—has observed this reliance firsthand. Catalist supplies International Tennis Federation (ITF) tennis data to platforms like Kalshi and Polymarket, in addition to holding an exclusive agreement for U.S. sports streaming with Kalshi. As a data provider, Catalist must also fulfill the needs of market makers who rely on accurate data to inform their models.
"If we just sold the data to Kalshi but no one was placing liquidity, there would be no value in listing those markets," Monk stated. “We need to ensure that market makers have the necessary information to operate effectively.”
Initially, Catalist had a list of fewer than ten potential market makers from Kalshi but now has agreements with nearly 20 and is in talks with around 20 more. This growth aligns with the rising variety of sports contracts available. Notably, ITF tennis needs official data because of the more than 60,000 annual matches that are rarely televised. Tracking events across various global locations, such as Bogotá and Bali, would pose challenges without reliable data, Monk explained.
Streaming functionality is also being incorporated into prediction markets. Monk commented that earlier interfaces focused heavily on trading elements, but are now evolving to include data streams and player options similar to sportsbook bet builders. "At the beginning of the year, Kalshi’s product was still very much trading-focused. Now, the product offerings have developed significantly,” he noted.
Andrew Gonzalez, who founded ParlayX, a prediction market infrastructure startup, views the ability of small teams to supply liquidity as a defining trait of the sector. "Anyone can be a market maker," he pointed out, emphasizing how even two- or three-person teams can operate in this arena.
Jefferies described market makers as integral to the ecosystem, serving as the "liquidity backbone" by providing executable bids and managing their inventory to balance pricing during customer activity fluctuations.
The analysis indicates that if a market maker captures a one-cent spread and manages exposure effectively, it could yield approximately $1.69 on a $100 trade. However, results are not guaranteed, as adverse price shifts and unresolved inventory can diminish earnings from spreads, rebates, and liquidity incentives.
Despite these opportunities, market infrastructure is still developing. Gonzalez contrasts prediction markets with equities, where established systems such as prime brokers and clearinghouses are in place. "In prediction markets, none of that exists," he noted, pointing out that many new market players are starting from scratch.
The current platforms typically cater to individual users rather than to trading organizations that require distinct permissions and controls. Gonzalez explained that some teams still operate with shared logins, which is inefficient for larger funds.
ParlayX aims to address these issues by designing distinct login structures, delegated permissions, and subaccounts. There are also critical challenges to unify execution across exchanges, prime brokerage services, and universal resolution standards.
For instance, a contract on Kalshi cannot be transferred to Polymarket, even if both platforms address the same outcome, due to differing definitions and resolutions by each market.
Liquidity can foster itself, drawing market makers to stable platforms with robust order flows, which in turn enhances pricing and execution for users. Sahil Patel, founder of Aldrin AI, remarked that such dynamics are key to understanding Kalshi's competitive edge. "Market makers gravitate towards liquidity," he added, noting Kalshi's investments in the financial aspects of its relationships with market makers as significant.
Aldrin AI analyzes product developments, advertising impact, social media presence, app-store rankings, and trading volume across prediction markets, seeking to correlate these factors with market performance. Patel indicated that in the competitive landscape, even a 1% market share represents a significant opportunity, as many players vie for a slice of this fast-evolving segment.
Jefferies estimates that exchanges can retain about 65% of explicit transaction fees, with the remainder allocated to clearinghouses, brokers, and liquidity providers. As a result, more firms are likely to integrate infrastructure elements in-house.
Independent suppliers benefiting from this trend will continue to grow with each new exchange, contract, and market maker. While consumer-facing platforms attract users, the essential elements of data, liquidity, and operational support behind the scenes remain critical to enable trading at scale.
