Will Brandon Nakashima win at least 5.5 more games than Roberto Bautista Agut
Liquidity-weighted aggregate sits at 27% across 10 Kalshi contracts.
Implied probability
Kalshi
27%
10 contracts
Polymarket
—
not bound
Cross-venue gap
—
single venue
24h move
−18pp
23h ago
24h volume
$0
10 contracts
Closes
May 23, 2026
14 days
30-day trend
Bracket families
7 clusters across 10 contracts.
These contracts were grouped by title similarity. The headline aggregate combines all clusters; verify the cluster you actually need before quoting a number.
Cluster 1
Will Jannik Sinner win at least
Will Jannik Sinner win at least 9.5 more games than Sebastian Ofner?: Jannik Sinner -9.5 games
KXATPGSPREAD-26MAY09SINOFN-SIN10
Will Jannik Sinner win at least 3.5 more games than Sebastian Ofner?: Jannik Sinner -3.5 games
KXATPGSPREAD-26MAY09SINOFN-SIN4
Will Jannik Sinner win at least 6.5 more games than Sebastian Ofner?: Jannik Sinner -6.5 games
KXATPGSPREAD-26MAY09SINOFN-SIN7
Cluster 2
Will Joao Fonseca win at least
Cluster 3
Will Thiago Agustin Tirante win at least 1.5 more games than Cameron Norrie
Cluster 4
Will Frances Tiafoe win at least 1.5 more games than Ignacio Buse
Cluster 5
Will Arthur Fils win at least 8.5 more games than Andrea Pellegrino
Cluster 6
Will Hamad Medjedovic win at least 1.5 more games than Joao Fonseca
Cluster 7
Will Andrey Rublev win at least 3.5 more games than Miomir Kecmanovic
Analysis
This probability reflects whether Brandon Nakashima will win at least 5.5 more matches than Roberto Bautista Agut over a defined period. At 45%, markets assess this as slightly less likely than not, suggesting uncertainty about whether Nakashima's recent form and ranking advantage will translate to a substantial win differential. The probability is primarily driven by the players' current rankings, recent match records, and scheduled tournament appearances. Nakashima, generally ranked higher, would need to maintain or improve performance while Bautista Agut shows relative decline—a multi-tournament outcome rather than a single event. The resolution depends on the specific timeframe and which competitions both players enter, making prediction difficult without knowing exact contract terms.
- ›Current ATP rankings and recent 52-week win-loss records for both players
- ›Number and caliber of tournaments each player is scheduled to enter during the resolution period
- ›Head-to-head historical match record and surface preferences
- ›Injury status or fitness concerns affecting either player's tournament availability
- ›Contract resolution date and whether it covers specific events (e.g., Grand Slams only) or all matches in a calendar period
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These markets stopped trading. Last odds and any captured outcome are shown above — full settlement detail lives at the venue.
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How we compute these odds
SimpleFunctions aggregates live prediction-market contracts from Kalshi and Polymarket. Each slug groups contracts that resolve on the same underlying event, identified by venue event_id.
For binary slugs, the headline probability is the liquidity-weighted mid-price across all bound contracts. For multi-outcome slugs (e.g. elections with 3+ candidates), the headline is the leader’s price; we never arithmetically average disjoint outcomes — that would produce a number with no real-world meaning.
Snapshots refresh every 5 minutes during market hours; daily aggregates are computed at 04:00 UTC. The 30-day sparkline is drawn from per-ticker daily means stored in market_indicator_daily; 24h delta and movement events are derived from the same source.
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