SimpleFunctions
kalshiOutcome slate24 markets

Will Iga Swiatek win the US Open Women's Singles

event base · KXWTA

By SimpleFunctions· Last verified 18 Aug 2026Methodology
24h volume
$94.1K
Constituents
24
Distinct tenors
1
Top P(YES)
21.0%
Aryna Sabalenka

Outcome probabilities

24 contracts at one resolution date

Analysis

The yield curve for KXWTA exhibits a distinctly flat structure across both observed tenor buckets, with all 35-day markets (tau=35d) and the 40-day markets (tau=40d) showing minimal differentiation in YES probabilities. The 35-day bucket dominates the dataset with 54 constituent markets, where probabilities cluster heavily at the 1.0% floor, with notable exceptions including SAB at 18.0%, SWI at 14.0%, RYB at 13.0%, and PEG at 6.0%. The 40-day bucket shows comparable probability levels, with ANI and EAL both priced at 4.0% and AND at 7.0%. The cheapest YES probabilities reside at the 1.0% floor across both tenor buckets, representing the vast majority of markets in this event family. The absence of meaningful slope between the 35-day and 40-day tenors indicates no systematic term structure—probabilities remain essentially flat across this narrow five-day window. This flat curve structure suggests the market views the event as either highly unlikely to occur within the near term or as having already largely resolved its uncertainty. The concentration of 1.0% probabilities across most markets, combined with the lack of steepening as tenor extends, indicates that market participants assign minimal probability mass to event occurrence across the entire observable horizon. The few outliers with elevated probabilities (SAB, SWI, RYB) represent specific sub-outcomes that command modest conviction, but the overwhelming prevalence of floor-priced markets signals the market's collective skepticism about the base event materializing. The flat curve offers no evidence of anticipated acceleration or deceleration in event timing.

Generated 8/18/2026 · anthropic/claude-haiku-4.5

Constituent markets

24 kalshi contracts

MarketTenorP(YES)Vol 24h
Will Aryna Sabalenka win the US Open Women's Singles?: Aryna Sabalenka5w21.0%$3.9K
Will Iga Swiatek win the US Open Women's Singles?: Iga Swiatek5w15.0%$3.7K
Will Coco Gauff win the US Open Women's Singles?: Coco Gauff5w14.0%$23.4K
Will Elena Rybakina win the US Open Women's Singles?: Elena Rybakina5w7.0%$15.2K
Will Naomi Osaka win the US Open Women's Singles?: Naomi Osaka5w7.0%$3.2K
Will Mirra Andreeva win the US Open Women's Singles?: Mirra Andreeva5w6.0%$278
Will Jessica Pegula win the US Open Women's Singles?: Jessica Pegula5w5.0%$3.1K
Will Amanda Anisimova win the US Open Women's Singles?: Amanda Anisimova5w4.0%$4.0K
Will Marta Kostyuk win the US Open Women's Singles?: Marta Kostyuk5w4.0%$5.7K
Will Alexandra Eala win the US Open Women's Singles?: Alexandra Eala5w4.0%$11.1K
Will Elina Svitolina win the US Open Women's Singles?: Elina Svitolina5w2.0%$78
Will Karolina Muchova win the US Open Women's Singles?: Karolina Muchova5w2.0%$1.6K
Will Barbora Krejcikova win the US Open Women's Singles?: Barbora Krejcikova5w2.0%$344
Will Maria Sakkari win the US Open Women's Singles?: Maria Sakkari5w2.0%$0
Will Linda Noskova win the US Open Women's Singles?: Linda Noskova5w2.0%$2.7K
Will Qinwen Zheng win the US Open Women's Singles?: Qinwen Zheng5w1.0%$6.7K
Will Madison Keys win the US Open Women's Singles?: Madison Keys5w1.0%$3.7K
Will Jasmine Paolini win the US Open Women's Singles?: Jasmine Paolini5w1.0%$1.0K
Will Iva Jovic win the US Open Women's Singles?: Iva Jovic5w1.0%$1.9K
Will Emma Navarro win the US Open Women's Singles?: Emma Navarro5w1.0%$0
Will Paula Badosa win the US Open Women's Singles?: Paula Badosa5w1.0%$1.4K
Will Victoria Mboko win the US Open Women's Singles?: Victoria Mboko5w1.0%$935
Will Jelena Ostapenko win the US Open Women's Singles?: Jelena Ostapenko5w1.0%$0
Will Maja Chwalinska win the US Open Women's Singles?: Maja Chwalinska5w1.0%$87

How to read this page

An outcome slate is a set of mutually-exclusive contracts that all settle on the same date. Their YES probabilities form a distribution over which outcome the market expects. Probabilities should roughly sum to 100% minus the venue’s overround.

Curve construction: each constituent contract is identified by its venue event_id (KXWTA on kalshi). Tenor is computed from the contract’s close_time minus snapshot time, rounded to days. We do not interpolate between tenors — every plotted point is a real, traded contract. Outcome-slate pages show price-as-probability for mutually-exclusive contracts; term-structure pages show price-as-probability vs days-to-resolution for the same underlying event.

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.

Last updated on this page: Tue, 18 Aug 2026 06:22:49 GMT.