Evaluating Betting Exchange Software: Why Liquidity and Matching Logic Rule

The landscape of online wagering is evolving rapidly as operators move beyond traditional sports betting into complex market environments. Running a betting exchange today involves far more than just displaying prices; it requires a sophisticated matching engine. This software must pair buy and sell orders from players in real time without the operator taking on the liability typical of a sportsbook. In Great Britain, the Gambling Commission defines these intermediaries as businesses that facilitate betting between parties without taking liability, a distinction that fundamentally dictates the software's architecture.

Prediction markets are a major driver of this change. Users are increasingly interested in wagering on election results, economic shifts, or technological milestones. While platforms like Polymarket handle billions in volume, traditional iGaming operators are still navigating the best entry points. The technical hurdle remains high because liquidity - the availability of tradable bets at competitive prices - is essential. Without it, the system fails as customers cannot find counterparts for their trades.

Numbers and facts

The scale of this opportunity is significant. In the United States, annualized trading volume for prediction markets grew from approximately $300 million in 2024 to an estimated $40 billion to $50 billion in 2025. This explosive growth signals massive potential for global operators. Software providers like Softswiss have responded by launching solutions that can be integrated in just two to three days for existing partners, while new operators can go live in about three weeks.

A critical part of any software procurement test is the matching logic. Operators must verify whether orders are matched based on price and time priority and how the system handles partial fills or volatile price swings. A robust platform must maintain order state and audit trails even when data packets arrive out of sequence or connections are dropped. The path of market data is just as vital as the front-end user experience.

Background

Before selecting a platform, operators must define their liquidity model. Will they rely on their own user base, hire market makers, or tap into shared liquidity pools? Each choice creates different dependencies. Market makers require strict contracts and platform permissions defining which markets they must support and their quoting obligations. Controls against self-matching or coordinated accounts are also necessary to prevent artificial market distortion.

"We are seeing a growing player segment. Prediction markets are not just an extension of sportsbooks – they introduce entirely new audiences who have never engaged with traditional betting products." - Olga Resiga, Chief Business Development Officer at SOFTSWISS

As an alternative to P2P exchanges, fixed-odds models for prediction markets are gaining traction. Companies like Betby use AI-driven content generation to launch hundreds of new markets weekly. However, human oversight remains mandatory to exclude sensitive topics such as geopolitics or human suffering. This approach allows operators to manage risk within familiar sportsbook frameworks rather than managing the variables of a live exchange book.

Why it matters for German players

For players in Germany, the regulatory environment is restrictive. The 2021 State Treaty on Gambling (GlüStV 2021) limits the scope of legal wagering primarily to sports. While international markets offer bets on almost any event, German-licensed operators are generally restricted to the outcome of sporting contests. Prediction markets for politics or finance are currently not approved under the Common Gambling Authority of the States (GGL) framework.

Furthermore, strict player protection rules apply, such as the cross-operator 1,000 Euro monthly deposit limit monitored via the LUGAS system. Slot stakes are capped at 1 Euro per spin. These regulations mean that German players looking for legal options will find very few prediction market products available. Engaging with unlicensed offshore exchanges carries significant risks, including a lack of legal recourse and potential payment blocking.

What it means for GGL-licensed casinos

German operators holding a GGL license must proceed with caution regarding these new technologies. Integrating prediction market tools from providers like Softswiss or Betby would require extensive legal review to ensure compliance with German law, which largely excludes social or political events from the betting catalog. However, the underlying technology - such as AI-driven risk management and automated market creation - could still be used to improve the efficiency of traditional sports betting offerings, provided it meets the transparency requirements of German regulators.