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The Tech Providers Behind the Prediction Markets Boom: A Comprehensive Guide

By jili tutorial · September 20, 2026

The Tech Providers Behind the Prediction Markets Boom: A Comprehensive Guide

The consumer-facing battle in prediction markets is becoming increasingly visible. Platforms like Kalshi, Polymarket, and newer entrants are aggressively expanding their sports offerings, while established players such as DraftKings, Flutter, and Robinhood invest in exchanges, distribution, and market-making capabilities. Yet behind these brands, a less visible but equally critical ecosystem is taking shape: a network of data and streaming suppliers, specialist market makers, and technology companies that power the entire industry.

This guide dives deep into the infrastructure that supports prediction markets, explaining how data, liquidity, and operational technology work together, and why this behind-the-scenes sector is becoming the backbone of the boom.

The Growing Importance of Prediction Markets

Prediction markets allow users to trade contracts on the outcomes of future events—sports matches, election results, economic indicators, and more. They have evolved from niche speculative platforms into a multibillion-dollar industry, with sports contracts now acting as the primary liquidity driver.

In a September report, investment bank Jefferies noted that sports had become prediction markets’ “most important liquidity driver,” with combo and parlay-style contracts accounting for an increasing share of activity. However, the analysts warned that prediction markets are scale businesses with relatively low revenue yields. Their economics depend on sustained liquidity, high engagement, and continuous trading activity. This makes the role of tech providers—who supply data, make markets, and build operational systems—absolutely crucial.

The Data and Streaming Layer: Fuel for Markets and Makers

Why Official Data Matters

James Monk, founder of Catalist Sports, a sports data and streaming provider, has witnessed this dependency firsthand. Catalist supplies official ITF tennis data to both Kalshi and Polymarket and holds an exclusive US sports-streaming agreement with Kalshi. But the company’s role goes beyond simply feeding contract prices; it also supplies data to the market makers who provide liquidity on those events.

“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,” Monk explained. “We also need to supply the data to the market makers to inform their models.”

Monk noted that ITF tennis is particularly dependent on official data because its more than 60,000 annual matches are rarely televised. Unofficially monitoring a tour that moves between locations such as Bogotá and Bali would be nearly impossible.

Streaming as a Product Feature

Streaming is also becoming part of the prediction market product. Monk observed that user interfaces have moved beyond the earlier trading-led presentation. They now incorporate live streams, player propositions, and combination bets resembling sportsbook “bet builders.” The shift began in early 2024, when Kalshi still had a trading-heavy UX. “The actual product offering has come a long way,” Monk said.

Catalist initially received a list of fewer than 10 potential market makers from Kalshi. Since then, it has completed agreements with close to 20 and is engaging with approximately another 20. This growth mirrors the expanding number and variety of sports contracts listed across platforms.

The New Market Makers: Small Teams, Big Impact

Anyone Can Be a Market Maker

Andrew Gonzalez, founder of ParlayX, a prediction market infrastructure startup, believes that the ability of small teams to provide liquidity is one of the sector’s defining features. “Anyone can be a market maker,” he said. “You have these two- or three-man shops.”

Jefferies describes market makers as the ecosystem’s “liquidity backbone.” They post executable bids and offers, manage inventory, and provide prices when customer activity is heavily weighted to one side. According to the analysts, an operator capturing a one-cent spread and managing exposure successfully could generate net economics of approximately $1.69 on a $100 trade. However, returns are not guaranteed: adverse price movements and unresolved inventory can offset or exceed income from spreads, rebates, and liquidity incentives.

Operational Infrastructure Gaps

Despite the opportunity, the operational infrastructure available to these new firms remains underdeveloped. Gonzalez draws a contrast with equities markets, where trading businesses can rely on prime brokers, clearinghouses, and standardized systems such as FIX (Financial Information Exchange).

“When it comes to prediction markets, none of that exists,” he said. “Everyone that’s building in the prediction market space mostly starts from ground zero.”

Most platforms were designed for a single user operating a single account, not for trading organizations that require separate permissions and controls. According to Gonzalez, some teams still share a single login. “Whether it’s a 10-person or 100-person fund, they log in through the same Google email and share the same login credentials, which makes no sense,” he said.

ParlayX is addressing this gap by developing individual logins, delegated permissions, and subaccounts for such teams.

Structural Challenges Across Exchanges

Other infrastructure gaps include:

These issues increase operational complexity and cost, especially for market makers who want to arbitrage price differences or manage risk across platforms.

The Liquidity Flywheel

Why Market Makers Follow the Flow

Liquidity can become self-reinforcing. Market makers gravitate toward platforms that offer dependable technology and substantial order flow, while their participation improves pricing and execution for consumers. This dynamic helps explain Kalshi’s market position.

Sahil Patel, founder of Aldrin AI, a competitive intelligence provider that monitors prediction market operators, said:

“A lot of market makers want to go where there’s liquidity. Kalshi is a freight train that’s just kind of running away with it.”

He also noted the importance of platform stability and Kalshi’s investment in the financial side of its market-maker relationships. Aldrin tracks product changes, advertising, social media activity, app-store rankings, and trading volume across operators. The goal is to connect these indicators and show how a product launch supported by advertising affects volume and market share.

The 1% Opportunity

Below the largest exchanges, Patel sees numerous operators competing for relatively small shares of a fast-growing category. “If you get 1% of this market, I think it’s a huge opportunity. There are a lot of people fighting to get 1%,” he said.

Jefferies estimates that exchanges can retain approximately 65% of explicit transaction fees, with the balance distributed across clearinghouses, brokers, and liquidity providers. As a result, the analysts expect more operators to bring parts of the infrastructure in-house.

The Future: In-House vs. Independent Providers

For the independent suppliers growing alongside the exchanges, the opportunity expands with every new exchange, contract, and market maker. The consumer-facing platforms may attract the users, but their products cannot trade at scale without the data, liquidity, and operational machinery developing behind the screen.

As prediction markets continue to mature, we can expect:

Conclusion

The prediction market boom is not just a story of consumer platforms competing for attention. It is also a story of the tech providers building the rails beneath them—data companies like Catalist Sports, infrastructure startups like ParlayX, and intelligence firms like Aldrin AI. Understanding this hidden ecosystem is essential for anyone looking to participate in or invest in the future of prediction markets.