Stephen F. Austin Lumberjacks vs. Texas-Rio Grande Valley Vaqueros (W)
Volume:
$9,692
Markets
Outcome
Chance %
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Volume
24h
7d
Open Interest
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Description
This event group covers the women's college basketball matchup between Stephen F. Austin Lumberjacks and Texas-Rio Grande Valley Vaqueros scheduled for February 14, 2026 at 3:00 PM ET. The market resolves based on which team wins the game, with provisions for postponement and cancellation scenarios.
Kalshi's binary Yes/Yes structure is logically incoherent and makes the market unresolvable to No. Polymarket uses a categorical outcome model (team name) that correctly captures a head-to-head matchup. The two platforms are fundamentally incompatible in their resolution architecture.
Hero Tip:
Avoid Kalshi until clarification is provided. The market cannot resolve to No regardless of outcome, indicating a critical data or logic error. Polymarket's structure is sound; trade there if you have conviction on either team.
Critical Divergence Points:
Kalshi: Binary Yes/Yes logic: both possible game outcomes (Rio Grande Valley wins OR Stephen F. Austin wins) are mapped to Yes. No path to No resolution exists. Quote: 'If UT Rio Grande Valley wins...then the market resolves to Yes. If Stephen F. Austin wins...then the market resolves to Yes.'
Polymarket: Categorical outcome model: market resolves to the winning team's name. Postponement keeps market open; cancellation with no makeup resolves 50-50. Quote: 'If the Stephen F. Austin Lumberjacks win, the market will resolve to Stephen F. Austin Lumberjacks. If the Texas-Rio Grande Valley Vaqueros win, the market will resolve to Texas-Rio Grande Valley Vaqueros.'
Our PredictionHero Resolution Divergence Alerts (RDA) are there to help users identify potential differences across platforms. They do not replace or supersede the official rules and description of any prediction market. Users are solely responsible for reviewing and understanding the applicable rules and resolution criteria before placing any trade or bet. If you notice a potential inconsistency, discrepancy, or error in an alert, please report it to our team so we can review and improve the accuracy of our data.
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