TOTAL VOLUME:
$134b
24H VOL:
$107,351,958
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,416,970,024
400,720
Markets across
30,097
events
MATCHED EVENTS:
2,633
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 13, 1:39 AM EST
Kalshi
This market tracks whether North Dakota State will win their college football game against Air Force by more than 2.5 points. Currently, Kalshi gives a 98.0% probability to North Dakota State winning by over 2.5 points. The market will resolve based on the outcome of the North Dakota St. vs Air Force college football game, with resolution details found in the provided resolution source. Participants should closely watch the game itself, as the market resolves based on the final score and will be settled by September 13, 2026, representing the end of the betting period for this event.
All markets resolve based on the official final score of the North Dakota St. vs Air Force college football game scheduled for Sep 12, 2026. If North Dakota St. wins, markets resolve to Yes only if the victory margin exceeds the specified point threshold; if Air Force wins, markets resolve to Yes only if their margin exceeds the threshold. For markets where Air Force is the favorite to win by a certain margin, the outcome label reflects Air Force's victory by more than the stated points. If the game is postponed but starts within 48 hours of the original time, all markets remain open and resolve based on the final result. If the game does not start within 48 hours of the scheduled time, all markets resolve to a fair price, ensuring equitable treatment for all participants under these contingency conditions.
Generally, prediction market odds reflect the wisdom of the crowd, often converging towards probabilities that differ from initial sportsbook lines. Sportsbooks set their odds to maximize profit, factoring in biases and public perception. This market, however, allows traders to express their own informed opinions, potentially leading to more accurate predictions as the event approaches. It’s common to see discrepancies between the two, particularly early on, as the prediction market incorporates diverse perspectives and reacts to new information. Over time, the odds on Kalshi may align more closely with sportsbook lines, or diverge if traders believe the sportsbook has mispriced the event.
On Kalshi, this market is priced through a continuous order book where traders buy and sell contracts representing different point spreads for the Air Force vs. North Dakota State game. The price of each contract reflects the market’s collective belief about the probability of that spread occurring. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Traders are incentivized to set prices that accurately reflect their assessment of the game's outcome, as they profit from correctly predicting the final spread. The market dynamically adjusts as new information becomes available and traders update their positions, creating a real-time assessment of the game's likely result.
This market resolves around Sep 13, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. The final spread will be determined by the official result of the Air Force vs. North Dakota State football game. The market will settle based on which side of the spread the actual final point difference falls. Traders holding contracts on the correct spread will receive a payout, while those on the incorrect side will forfeit their investment. The resolution process is designed to be transparent and based on publicly available data.
Several factors could influence the price movement of this market. Any significant news regarding player injuries, coaching changes, or team performance could shift trader sentiment. Unexpected weather forecasts for the game location could also play a role, as weather conditions can significantly impact football game outcomes. Furthermore, major shifts in public opinion, reflected in polls or expert analysis, could lead to changes in the market price. Finally, large trading volume from informed traders could also signal new information or a change in market expectations, potentially causing the spread to move.