Traditionally, sportsbook uptime data simply measures the duration for which betting markets are available during a match. In contrast, wagering-weighted uptime shifts the focus to the critical question: were sportsbooks accessible during those high-activity moments when betting interest peaks? Bettormetrics’ analysis of the US Open reveals that understanding wager volume can shed light on sportsbook availability when it counts the most. New prediction market data complements their existing exchange data, allowing for a more thorough evaluation of operator performance across a broader array of sports and betting markets, particularly in the US.
The limitations of conventional uptime metrics are apparent. Uptime is often presented as a percentage of total match duration—indicating how long betting was available—without considering the volume of money flowing through markets at any given time. While this may serve as an overall gauge of efficiency, it incorrectly assumes that every stage of a match holds equal significance for bettors. A sportsbook that experiences downtime during a high-stakes tie-break is penalized the same as one that is unavailable during a quieter first set, despite the latter being less consequential in terms of betting activity.
This misalignment means a sportsbook may report a seemingly impressive uptime while not being accessible during peak wagering moments. Strong uptime numbers do not alone affirm that operators were present during the most critical betting windows.
Bettormetrics conducted a comparative analysis of operator pricing and availability alongside exchange pricing and matched wagering activity during 39 in-play men's singles matches at the US Open, covering 18 different operators. Performance metrics are calculated in two ways: by duration, representing the total match time for which a market was active, and by wagering, indicating how often the exchange matched wagering coincided with operator availability.
To clarify, traditional exchange wagering is not directly translatable to sportsbook revenue estimates but offers an independent view of concentrated betting activity, highlighting crucial times for sportsbooks to be available. This analysis distinguishes between pricing on sportsbooks and exchanges by relying on market-derived data, a methodology applicable across various betting environments.
In this context, ‘theoretical arbitrage’ signifies at least one sportsbook offering that is favorably priced against exchange values, although it does not guarantee that every such opportunity is realizable.
Focusing on LeoVegas, it achieved a duration-weighted uptime of 97.8%, ranking it favorably with peers like Superbet, Paddy Power, and Hard Rock. However, its wagering-weighted uptime came in at 88.3%, marking it as the lowest among those analyzed and the only operator below the 90% threshold. The disparity of 9.5 percentage points in these two metrics highlights a significant issue, as LeoVegas experienced downtime during crucial wagering times, specifically allowing for its uptime to appear strong, despite unavailability during vital periods.
The match featuring Alexander Zverev and Alejandro Tabilo exemplified these findings: LeoVegas maintained 98.5% uptime by duration, yet its service was only available for periods corresponding to 61.5% of exchange wagering activity—a clear instance of misleading uptime statistics.
Looking at overall pricing performance within the US Open, Pinnacle exhibited the lowest average overround at 3.7%, and its theoretical arbitrage exposure was notably modest at 4.8% by duration and 6.4% by wagering—both figures considerably below the median in the field. This distinction positions Pinnacle as abnormal since tighter margins usually correlate with heightened arbitrage exposure.
In contrast, FanDuel and Superbet demonstrate that operators can maintain competitive pricing while exhibiting lower-than-expected arbitrage exposure relative to their margins. Both operators showed strong wagering-weighted uptime: Superbet at 97.5% and FanDuel at 98.7%, reinforcing their performance despite aggressive pricing strategies.
Bet365 presented strikingly high figures during the Novak Djokovic match, registering profitable arbitrage opportunities for a remarkable 56.5% of the match duration—significantly outpacing its competitors. While Bet365 had a high percentage of arbitrage exposure in that fixture, its pricing was aligned with the overall average, implying that pricing realignment rather than competitive anomalies drove this arbitrage exposure. In comparison, DraftKings found itself trailing behind in key performance metrics, reflecting its need to enhance its tennis offerings relative to its chief competitor.
As Bettormetrics plans to incorporate prediction market data alongside exchange data, the implications for performance analysis across various sports and markets are promising. The ability to assess sportsbook uptime through a wager-weighted lens is crucial for understanding actual market presence when betting activity peaks. The limitations of conventional metrics can mask essential insights about sportsbook operations, as emphasized by CEO Sabin Brooks, who notes the importance of measuring sportsbook performance during critical wagering periods. With these developments, Bettormetrics aims to refine the industry’s approach to performance insights, ensuring operators remain aware of operational efficacy when it is needed most.
