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Susquehanna International Group operates Nellie Analytics, a Dublin-based quantitative sports betting unit established in 2017. The operation focuses primarily on in-game wagering, applying the same statistical modeling techniques SIG uses in options trading to sports markets. Jane Street has also reportedly built specialized teams in this space. The trade isn’t gambling — it’s market making and statistical arbitrage executed on exchange-style order books where information efficiency creates exploitable microstructure.
The Exchange Architecture
Betfair pioneered the betting exchange model in 2000, operating as an order-driven market where bettors trade directly through continuous double auction. Unlike traditional bookmakers who take counterparty risk, the exchange provides only the platform infrastructure, charging 5% commission on net profits (reducible to 2% through reward programs) while offering complete order book transparency.
The market structure mirrors equity exchanges: “back” prices function as ask prices (buying a bet on an outcome), while “lay” prices function as bid prices (selling the bet). This creates genuine price discovery — participants can act as both liquidity providers and takers, with order books displaying depth and volume at each price level.
Market Scale: Horse racing generates the highest volumes on Betfair, with billions in annual matched bets driven by daily event frequency and pre-race market volatility. Total matched volume across all sports approaches significant institutional scale, though individual event liquidity varies dramatically — popular Premier League matches generate millions in matched bets, while smaller markets may see only tens of thousands.
Three Core Trading Strategies
1. Market Making
Traders simultaneously place back and lay orders across all possible outcomes, creating synthetic bookmaking positions. The strategy targets 105–110% total book percentage (overround) by positioning orders 1–2 ticks from mid-market prices.
P&L Mechanics:
Revenue = (Total Matched Volume × Book Percentage Above 100%) — Exchange Commission
On a £50,000 market with 108% book: £4,000 gross, £3,800 net after 5% commission (or £3,920 with 2% discount rate)
Execution risk: unmatched orders leave single-sided exposure
Requires continuous rebalancing as market moves
Technical Implementation: Automated algorithms monitor order flow, adjust quotes based on probability updates, and hedge residual risk across correlated markets. Speed matters — liquidity providers must react within milliseconds to information.
2. Cross-Book Arbitrage
Systematic identification of discrepancies where implied probability sums to less than 100% across different bookmakers or exchanges. Returns are minimal — 98% of opportunities yield below 1.2% profit — requiring substantial capital deployment.
Execution Challenges:
Odds shift within seconds; one leg fills while the other moves
Account limits imposed on consistent winners
Requires simultaneous API access to multiple platforms
Transaction costs and commission can eliminate edge
Risk Management: Position sizing must account for partial fill risk and account closure probability. Most operators identify and restrict arbitrageurs within weeks.
3. In-Play Order Flow Trading
Monitoring order book depth, bet size asymmetry, and price impact patterns to predict short-term odds movements. Similar to high-frequency trading in equities — capturing spread by providing liquidity, then hedging as momentum shifts.
Key Signals:
Large back orders accumulating 3–5 ticks below market indicate institutional positioning
Sudden volume spikes on specific outcomes suggest information flow
Order book imbalances predict imminent price movement
Correlation with live event dynamics (score changes, injuries, momentum)
Third-party analysis of Susquehanna’s approach suggested their real-time models could adjust win probabilities on microsecond timescales — for example, calculating how a single play decision impacts outcome likelihood. This capability demonstrates the sophistication of quantitative modeling in live betting markets.
Event Contracts: The New Instrument
Polymarket and Kalshi introduced prediction market event contracts — binary outcome tokens priced $0-$1 where price represents implied probability. Unlike traditional betting, these platforms use peer-to-peer exchange models where users set prices and trade with each other.
Contract Mechanics:
Buy 100 shares at $0.40 → if outcome occurs, receive $100 (profit: $60)
Exit pre-settlement by selling shares as probability updates
Enables momentum trading and dynamic hedging
Transaction fees replace traditional bookmaker margins
On October 7, 2025, Intercontinental Exchange (ICE) — owner of the New York Stock Exchange — invested up to $2B in Polymarket at an approximately $8–9B valuation, signaling institutional validation of prediction markets as a legitimate asset class. The platform trades binary contracts on sports, politics, economics — any verifiable future event. Unlike sportsbooks, profit comes from transaction fees (typically 1–2%) rather than taking the opposite side of bets.
Revenue Drivers and Risk Factors
Primary Revenue Sources:
Bid-ask spread capture (2–8 ticks depending on liquidity)
Book percentage premium above 100% in market making
Arbitrage edge (0.5–1.2% per opportunity when available)
Momentum scalping on in-play volatility
Transaction rebates on exchanges for liquidity provision
Critical Risks:
Account Restrictions: Bookmakers and exchanges systematically identify and limit winning traders. Susquehanna’s investment in PointsBet (12.8% stake for $65.2M USD / A$94M in June 2022) was partially strategic — securing a partner willing to accept sharp money and stand by pricing rather than limiting accounts.
Liquidity Fragmentation: Unlike financial markets with consolidated liquidity, sports betting spreads across thousands of independent events. Even horse racing — the largest category — averages only ~£500k matched per race. This prevents institutional-scale capital deployment beyond £10–20M per strategy.
Execution Risk: Centaur Galileo, an early sports betting hedge fund, collapsed in 2012 after losing $2.5M investor capital. Likely cause: over-leveraging position sizes beyond Kelly criterion constraints and inadequate risk management during losing streaks.
Market Efficiency: Research shows betting exchanges exhibit higher informational efficiency than traditional bookmakers. Unlike financial assets with volatility clustering, sports markets demonstrate light-tailed return distributions with rapidly decaying autocorrelations — information incorporates within minutes, not hours. This creates opportunity for microsecond latency arbitrage but limits slower strategy alpha decay.
The Successful Model: Priomha Capital
Priomha Capital, established in 2009 as The Cloney Multi-Sport Investment Fund, exemplifies successful institutionalization. The Australian fund achieved 118% returns by end of 2011 (versus S&P 500/ASX 200 losing 17.4% over the same period), then delivered consistent 17% average annual ROI from 2010–2015 after fees.
Operational Structure:
Computer models for Premier League soccer, cricket, horse racing, golf, tennis
Bets entire capital base up to twice monthly
Quarterly audits and stringent risk management
30% performance fee + management fees
Relocated to Gibraltar to expand beyond Australian regulatory limits
The fund’s success demonstrates that systematic, quantitatively-driven sports betting can generate uncorrelated alpha. However, performance fees (30%) and bet size limitations remain structural constraints — even Priomha managed only A$5M AUM initially, expanding slowly.
Why This Matters for Quant Finance
True Portfolio Diversification: Sports betting returns show zero correlation to traditional asset classes, providing genuine beta-neutral exposure. Market crashes don’t affect sports outcomes.
Transferable Microstructure Skills: Order book dynamics, market making, and statistical arbitrage concepts transfer directly from financial markets. The alpha exists in microstructure, not prediction.
Scale Constraints Define Opportunity: Fragmented liquidity across thousands of events creates persistent inefficiencies that institutional capital cannot arbitrage away. Individual UK horse races average ~£500k matched volume; even major Premier League matches rarely exceed single-digit millions in pre-match liquidity. Small, specialized teams maintain edge specifically because markets can’t support large-scale capital deployment — the very constraint that caused hedge fund structures to fail while proprietary trading shops succeeded.
Technology Convergence: As event contract platforms (Polymarket, Kalshi) scale and regulatory frameworks mature, sports betting increasingly resembles financial market infrastructure. Susquehanna’s SIG Sports division explicitly states they “provide liquidity for sports markets” using “advanced statistical forecasting models” — identical language to options market making.
The Bottom Line
Hedge funds profit from sports betting markets through the same mechanisms that drive financial market trading: market making spread capture, arbitrage execution, and order flow analysis. Susquehanna didn’t hire sports analysts — they deployed options traders and quant developers to apply existing statistical models to a new asset class.
The constraint isn’t strategy sophistication but market capacity. Liquidity fragmentation prevents whale-scale capital deployment, maintaining opportunity for specialized teams. As PointsBet executive stated when explaining Susquehanna partnership: “Our real strength is in in-play. That is the most mathematical part of sports betting, and it’s very complicated.”
Translation: the edge comes from processing large amounts of real-time data and computing confident pricing — exactly what quantitative trading firms do in options markets. Sports betting is options trading with different underlying assets.
Sources
Primary Research Sources:
Susquehanna/Nellie Analytics:
eFinancialCareers: Sports betting: the new niche for quants at Jane Street, SIG and Jump Trading (Oct 2024)
Bloomberg: A Well-Known Quant Firm Is Looking for Traders Who Want to Bet on Sports (Oct 2017)
Susquehanna Official: SIGSports | Sports Analytics
Sports Business Journal: Susquehanna Invests $65.2 Million in PointsBet (Jun 2022)
Legal Sports Report: PointsBet Stock Jumps After Susquehanna Partnership (Jun 2022)
Sportico: Susquehanna Bets $65M That Superior Pricing Will Win (Jun 2022)
Sports Handle: PointsBet Stock Jumps After Susquehanna Investment (Jun 2022)
Wikipedia: Susquehanna International Group
2. Betting Exchange Mechanics:
LUISS University Thesis: Betting Exchanges: A Market Maker Process (PDF)
Betfair Official: Betfair Charges
Wikipedia: Betfair
Matched Betting Blog: Betfair 2% Commission Details
Caan Berry: Using Matched Volumes on Betfair (Dec 2018)
3. Priomha Capital Performance:
Bloomberg: Hedge Fund Returning 17% on Sports Bets Moving to Europe (Apr 2015)
Ivey Business Review: Over / Under — Sports Betting Funds Analysis (Aug 2021)
Medium: Priomha Capital: A Sports Betting Hedge Fund (Jan 2023)
4. Market Failures:
Financial Times: Investors Offered a Gamble on Sports Betting Fund (May 2017)
Business Insider: Sports Betting Hedge Fund Collapses (Jan 2012)
HuffPost: Centaur Galileo Sports Betting Hedge Fund Failure (Feb 2012)
5. Arbitrage & Market Structure:
Wikipedia: Arbitrage Betting
Arbitrage Calculator: How Arbitrage Betting Works
OddsJam: Arbitrage & Hedge Calculator
6. Polymarket/Event Contracts:
ICE Press Release: ICE Announces Strategic Investment in Polymarket (Oct 7, 2025)
Wikipedia: Polymarket
Sportico: What Are Sports Prediction Markets? (Nov 2024)
Covers: Polymarket Launches U.S. Prediction Markets (Dec 3, 2025)
Investopedia: NYSE Owner ICE Commits $2B to Polymarket (Oct 2025)
Gaming Today: Polymarket Relaunches in the US (Oct 2025)
7. Academic Research:
SSRN: Algorithmic Trading in Financial and Sports Exchanges (Aug 2024) (PDF)
ResearchGate: Betfair Order Book Analysis
8. Additional Context:
Sports Betting Dime: Why Are Hedge Funds Betting on Sports (Jul 2024)
Finsmes: Hedge Funds in the Sports Sector (Feb 2024)
Betting Websites UK: Sports Betting Hedge Funds Overview (Feb 2025)
eFinancialCareers: Are Quant Firms Too Snobby About Sports Betting? (Dec 2024)
Statistics and performance figures verified through multiple independent sources. ICE/Polymarket data reflects October 2025 developments; other market data current through December 2024.
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Cover photograph: Alex Kinney, CC BY-SA 2.0, via Wikimedia Commons.
Cover photograph: Alex Kinney, CC BY-SA 2.0, via Wikimedia Commons.