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The Hidden Flaw in Sportsbook Uptime: What the US Open Data Reveals About True Availability

By jili tutorial · October 1, 2026

The Hidden Flaw in Sportsbook Uptime: What the US Open Data Reveals About True Availability

Introduction: Why a 98% Uptime Stat Can Be Dangerously Misleading

In the competitive world of sports betting, operators frequently boast about their platform uptime—the percentage of time a market is live and accepting wagers. A 97% or 98% uptime figure sounds reassuring; it suggests that for nearly the entire match, customers could place bets. But this traditional metric, measured simply by duration, hides a critical blind spot: it treats every minute of a match as equally valuable, even though betting activity is heavily concentrated in the most dramatic and pivotal moments.

The US Open tennis tournament provided a stark demonstration of this gap. Bettormetrics, a data analytics firm specialising in sportsbook performance, analysed 39 in-play men’s singles matches across 18 operators. Their findings challenge the conventional wisdom: a sportsbook can appear nearly flawless on duration-based uptime while being unavailable during the very periods when customers are most eager to bet—and when the operator stands to generate the most revenue.

This guide unpacks what wagering-weighted uptime means, why it matters commercially, and how the US Open data exposes the shortcomings of traditional metrics. It also explores the broader opportunity that prediction-market data offers for benchmarking sportsbook performance across major US sports.

The Core Problem: Duration-Based Uptime Ignores Commercial Reality

What Traditional Uptime Measures (and What It Misses)

Conventional uptime is calculated as the proportion of a match’s total duration during which a sportsbook’s market is live and available. For example, if a tennis match lasts three hours and an operator’s market is live for 2 hours 56 minutes, the uptime is 97.8%. This is a reasonable long-run measure of technical availability, but it treats every stage of the match equally.

The result: a sportsbook can report excellent duration-based uptime while being systematically unavailable during the periods when wagering activity is heaviest. This is not a hypothetical scenario—the US Open analysis found it happening in practice.

Why Wagering Activity Is Not Evenly Distributed

In any live sporting event, betting momentum follows a predictable pattern. Early rounds or sets tend to see lower volumes as bettors assess form and momentum. As the match progresses—especially during tie-breaks, final sets, or moments of high drama—wagering activity surges. The same principle applies across sports: the final minutes of an NBA game, the last quarter of an NFL match, or a penalty shootout in soccer all attract disproportionate betting interest.

A duration-based metric cannot capture this imbalance. It assumes that every minute of the match is equally important for the operator’s bottom line. Commercially, that assumption is false.

Wagering-Weighted Uptime: A More Commercially Relevant Measure

How Bettormetrics Defines and Measures It

Bettormetrics introduces a complementary metric: wagering-weighted uptime. Instead of looking at time alone, this measure asks: What proportion of total betting activity took place while the sportsbook’s markets were live?

To calculate this, Bettormetrics uses exchange wagering data as an independent proxy for when betting concentration occurs. Specifically, they compare operator pricing and availability with exchange pricing and matched wagering activity. The methodology works as follows:

This approach does not directly measure an operator’s actual lost revenue—exchange wagering is not the same as sportsbook wagering. However, exchange data provides an independent, market-derived signal of when betting activity is concentrated. If the exchange sees high wagering volume at a given moment, it is highly likely that sportsbook customers were also trying to bet at that same moment.

Why Exchange Data (and Soon Prediction-Market Data) Is the Right Source

Traditional betting exchanges and prediction markets are both exchange-based environments. They produce market-derived pricing and wagering signals. Provided there is sufficient liquidity, the same methodology can be applied to both. Bettormetrics currently uses exchange data; soon, it will integrate prediction-market data as well, extending the analysis to sports where exchange liquidity is thin but prediction markets are active—particularly across the NFL, NBA, and other US sports.

The key advantage: these independent data sources offer a commercially weighted view of operator performance that is not self-reported by the sportsbooks themselves.

Key Findings from the US Open Analysis

The LeoVegas Case: A 9.5 Percentage Point Gap

The most dramatic example in the dataset is LeoVegas. On a duration basis, its uptime across the 39 matches was 97.8%—solidly in the upper half of the field, nearly identical to Superbet (97.5%), Paddy Power, and Hard Rock. Yet its wagering-weighted uptime was just 88.3%, the lowest of any operator in the sample and the only one below 90%.

The gap between the two figures: 9.5 percentage points—more than double the next-largest gap in the field.

This disparity is not an anomaly. The match between Zverev and Tabilo illustrates it perfectly. LeoVegas was available for 98.5% of that match by duration. However, it was only live during periods that accounted for 61.5% of exchange wagering activity. In other words, while the sportsbook appeared close to flawless on the conventional measure, it was unavailable during periods that represented more than one-third of the betting in that fixture.

The pattern is consistent: LeoVegas’s downtime was concentrated in the moments of heaviest wagering—exactly what a duration-based measure cannot reveal.

Pinnacle: The Outlier in Pricing and Arbitrage

Pinnacle is well-known for offering tight margins. At the US Open, its average overround (the built-in profit margin) was 3.7%, the lowest of any operator tracked. Conventional wisdom suggests that tighter margins increase exposure to theoretical arbitrage—when a sportsbook’s odds move past the exchange’s fair price, creating a profitable back-and-lay opportunity for bettors.

Yet Pinnacle’s theoretical arbitrage exposure was remarkably low:

This combination—tight margins with minimal arbitrage—is not the industry norm. Across the 18 operators, tighter margins were associated with more theoretical arbitrage, not less. For example, DraftKings had the second-tightest overround at 4.5%, but its arbitrage exposure was 14.9% by duration—roughly triple Pinnacle’s figure for a near-identical margin.

The tournament-wide relationship between margin and arbitrage would predict that a book priced as tightly as Pinnacle would have arbitrage closer to 12%–13%, not under 5%. Pinnacle’s outlier status suggests a suspension or repricing approach that works in step with sharp pricing—essentially, they adjust their lines so quickly that they rarely slip into arbitrage, even while maintaining tight margins.

FanDuel and Superbet: Balanced Performers

Neither FanDuel nor Superbet stands out on any single metric, but their combination of attributes makes them strong all-round performers.

Both operators demonstrate that it is possible to price competitively without carrying excessive arbitrage exposure, and that disciplined exposure does not come at the expense of being available when wagering is heaviest.

Bet365 and DraftKings: Standout Figures and Gaps

The most extreme single-fixture figure in the dataset belongs to Bet365 during Mariano Navone’s five-set upset of Novak Djokovic. In that match, Bet365 was in theoretical arbitrage against exchange pricing on at least one selection for 56.5% of match duration—more than double the next-highest operator in that match (Ladbrokes at 27.1%) and roughly 3.5x Bet365’s own tournament-average arbitrage by duration (16%, itself the highest average in the field).

However, the picture looked less extreme when measured by wagering: only 16.7% of exchange wagering in that match occurred while Bet365 was in arbitrage, against a tournament average of 11.1%. The gap between the duration and wagering figures is consistent with the interpretation that much of Bet365’s arbitrage fell in quieter periods of the match. Bet365’s overround in the fixture was 5.1%, close to its tournament average of 4.8%, so the exposure did not appear to reflect unusually wide or tight pricing.

Elsewhere, DraftKings recorded the second-highest theoretical arbitrage exposure in the field by duration and the fifth-highest by wagering. As FanDuel’s key sportsbook rival in the US, this leaves it with significant ground to make up in its tennis offering—especially given FanDuel’s much better combination of tight margins and high wagering-weighted uptime.

The Wider Opportunity: Prediction Market Data

The US Open findings demonstrate what a wagering-weighted view adds to sportsbook benchmarking. Consider again the contrast between LeoVegas and Superbet:

OperatorDuration-Based UptimeWagering-Weighted Uptime
LeoVegas97.8%88.3%
Superbet97.5%97.5%

Two operators with nearly identical traditional uptime—but dramatically different commercial availability. Without the wagering-weighted perspective, an operator like LeoVegas might have been praised for its technical uptime, while in reality it was missing the most valuable betting windows.

Bettormetrics will soon be able to combine exchange data with prediction-market data. This will provide a broader set of independent pricing and wagering signals. The key benefit: commercially weighted performance analysis can be applied much more widely wherever liquidity is sufficient, particularly across the NFL, NBA, and other US sports—where prediction markets are often more liquid than traditional exchanges.

Conclusion: What Operators and Analysts Should Take Away

The Commercial Imperative

Sabin Brooks, CEO of Bettormetrics, summarises the findings succinctly: “What the US Open clearly shows is that traditional uptime alone is no longer enough. It tells an operator how often it was available but not whether it was available when it mattered most.”

For sportsbook operators, the lesson is clear:

For analysts and regulators, the takeaway is equally important: a sportsbook’s headline uptime can look excellent while concealing unavailability during the periods when wagering activity is greatest. The US Open data reveals this gap in vivid detail, and the integration of prediction-market data will only deepen the insight in the future.

A New Benchmark for the Industry

The traditional view of sportsbook performance—measured by simple availability over time—is incomplete. Wagering-weighted uptime, theoretical arbitrage analysis, and margin-arbitrage relationships together paint a far richer picture of how operators truly perform. As Bettormetrics expands its methodology to more sports and markets, the industry will have a new, commercially meaningful standard for evaluating sportsbook reliability and value.

The US Open was just the beginning.