At least 6 teams in the Big Ten win at least 10 games in the 2026 college football regular season
6+ teams is priced at 10¢ on Kalshi. Current book: 0¢ bid, 11¢ ask, 11¢ spread. This outcome ranks #3 of 5 inside Will at least.
Price history
10¢ current
Contract brief
If at least 6 teams in the Big Ten win 10+ games in the 2026 college football regular season, then the market resolves to Yes.
Outcome
6+ teams
Rank
#3 of 5
Leader
3+ teams 71¢
Range
5¢-71¢
Family volume
$223
Identifier
KXNCAAFBIGTENWINS-26W10-6
Sep 17, 2026, 2:38 AM UTC · 19m ago
Implied probability
Bid
0¢
Ask
11¢
Spread
11¢
Reported volume
$1
Family rank
#3 of 5
5 outcomes · Will at least
Closes
Jan 7, 2027
Family volume
$223
Orderbook snapshot
0 / 11¢
Contract terms
What resolves this market.
YES condition
If at least 6 teams in the Big Ten win 10+ games in the 2026 college football regular season, then the market resolves to Yes.
Venue
Kalshi
Closes
Jan 7, 2027
Identifier
KXNCAAFBIGTENWINS-26W10-6
Event family
Will at least.
The same race as a probability stack: rank, volume, and where this contract sits against the other outcomes.
Total volume
$223
Outcomes
5
Highest price
3+ teams 71¢
Current share
0%
Indicators
Yield, cliff risk, volatility, and regime.
Regime
neutral
Score
0.5
Full indicator table
Odds pages
Related prediction questions
Related readings
Matched from SimpleFunctions blog, opinions, technical guides, concepts, and learn pages.
Kalshi vs Polymarket: Which Prediction Market Should You Trade?
In-depth comparison of Kalshi and Polymarket for prediction market traders. Regulatory structure, liquidity, fees, API tooling, and cross-venue trading with SimpleFunctions.
Kalshi vs Polymarket: Mechanics, Fees, Regulation, Liquidity (2026)
Side-by-side comparison of Kalshi and Polymarket in 2026. Fee math, calibration data, withdrawal speed, and a decision tree for picking the right venue.
Prediction Market Orderbook Analysis: Reading Depth, Spread, and Liquidity
How to read prediction market orderbooks. Binary settlement, spread-as-percentage, depth asymmetry, executable edge calculation, and cross-venue arbitrage analysis.
Kalshi vs Polymarket: A Developer's Comparison of APIs, Orderbooks, and Liquidity
Data-driven comparison of Kalshi and Polymarket APIs, orderbooks, rate limits, and liquidity. Code examples for building on both prediction markets.
Liquidity Availability Is the Real Edge in Prediction Markets
Implied yield, cliff risk, and overround all describe what to trade. Liquidity Availability Score describes whether the orderbook can absorb the trade. Why LAS is the indicator that decides who actually books P&L.
Implied Yield vs Raw Probability: Why Bond-Adjacent Prediction Markets Need a Different Lens
Why fixed-income-adjacent prediction-market contracts need to be priced in implied yield, not raw probability, with two real Kalshi Fed-decision contracts as a case study.
SimpleFunctions context
Index, screen, query, and monitor.
Prediction Market Index
Market-wide volatility, geo risk, breadth, and activity around this contract.
Market Screener
Filter adjacent contracts by volume, expiry, IY, CRI, venue, and theme.
Event Probability API
Read 10% as a structured event probability object for agents and apps.
Realtime Data API
Prices, orderbooks, movement, heat, and liquidity indicators across venues.
World State API
Compact market-aware context packets for agent sessions and scheduled refresh.
Hedging Workflows
Map a thesis or exposure to candidate event markets and monitoring paths.
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.