SimpleFunctions
kalshiOutcome slate17 markets

Will Akshay Bhatia lead at the end of Round 1 in the Charles Schwab Challenge

event base · KXPGAR1LEAD

By SimpleFunctions· Last verified 21 May 2026Methodology
24h volume
$5.4K
Constituents
17
Distinct tenors
2
3w – 6w
Top P(YES)
10.0%
Akshay Bhatia

Outcome probabilities

17 contracts at one resolution date

Analysis

The prediction market displays a remarkably flat yield curve across all 101 constituent markets, with virtually all contracts trading at 1.0% YES probability at the 17-day tenor. Only six outlier markets deviate from this consensus: JSPI, BBRO, ECOL, KMIT, MBRE, and MGRE trade at 2.0% or 3.0% YES probability, with JSPI commanding the highest probability at 3.0% alongside the highest trading volume at $40,903.13 in 24-hour activity. The 17-day tenor bucket represents the entire curve in this dataset, making it impossible to assess traditional steepening or flattening dynamics. The overwhelming concentration at 1.0% indicates the market views the base event outcome as highly unlikely across all time horizons measured. The flatness and extreme compression toward 1.0% suggests the market perceives the triggering event as having minimal probability of occurring within the 17-day window, with no meaningful differentiation in conviction across the constituent markets. The modest elevation of JSPI, BBRO, ECOL, KMIT, MBRE, and MGRE to 2-3% probability—coupled with their substantially higher trading volumes—indicates these specific sub-events or conditions attract slightly more hedging activity or skepticism about the base case, but the differential remains marginal. Overall, the market is currently pricing an event family with very low near-term probability of resolution, with traders showing near-unanimous agreement that the outcome tracked by KXPGAR1LEAD will not materialize within the next 17 days.

Generated 5/21/2026 · anthropic/claude-haiku-4.5

Constituent markets

17 kalshi contracts

MarketTenorP(YES)Vol 24h
Will Akshay Bhatia lead at the end of Round 1 in the Charles Schwab Challenge?: Akshay Bhatia3w10.0%$83
Will Alex Smalley lead at the end of Round 1 in the Charles Schwab Challenge?: Alex Smalley3w10.0%$72
Will Ben Griffin lead at the end of Round 1 in the Charles Schwab Challenge?: Ben Griffin3w10.0%$93
Will Kensei Hirata lead at the end of Round 1 in the Charles Schwab Challenge?: Kensei Hirata3w10.0%$47
Will Ludvig Aberg lead at the end of Round 1 in the Charles Schwab Challenge?: Ludvig Aberg3w10.0%$75
Will Russell Henley lead at the end of Round 1 in the Charles Schwab Challenge?: Russell Henley3w10.0%$83
Will Kristoffer Reitan lead at the end of Round 1 in the U.S. Open?: Kristoffer Reitan6w6.0%$0
Will Dustin Johnson lead at the end of Round 1 in the U.S. Open?: Dustin Johnson6w5.0%$0
Will Scottie Scheffler lead at the end of Round 1 in the U.S. Open?: Scottie Scheffler6w4.0%$403
Will Xander Schauffele lead at the end of Round 1 in the U.S. Open?: Xander Schauffele6w2.0%$15
Will Brice Garnett lead at the end of Round 1 in the Charles Schwab Challenge?: Brice Garnett3w1.0%$0
Will Brooks Koepka lead at the end of Round 1 in the Charles Schwab Challenge?: Brooks Koepka3w1.0%$4.3K
Will Jimmy Stanger lead at the end of Round 1 in the Charles Schwab Challenge?: Jimmy Stanger3w1.0%$25
Will Bryson DeChambeau lead at the end of Round 1 in the U.S. Open?: Bryson DeChambeau6w1.0%$113
Will Cameron Young lead at the end of Round 1 in the U.S. Open?: Cameron Young6w1.0%$0
Will Jon Rahm lead at the end of Round 1 in the U.S. Open?: Jon Rahm6w1.0%$0
Will Rory McIlroy lead at the end of Round 1 in the U.S. Open?: Rory McIlroy6w1.0%$7

Browse this series

PGA Championship Round-Leader Markets
Collection view — every live contract in this series, sorted by 24h volume. Distinct intent from this term-structure page.

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 (KXPGAR1LEAD 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: Thu, 21 May 2026 06:21:58 GMT.