TOTAL VOLUME:
$154.3b
24H VOL:
$228,458,490
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2,984,028,936
OPEN INTEREST:
$1,879,276,037
410,833
Markets across
40,345
events
MATCHED EVENTS:
4,363
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 10, 7:00 PM EST
Kalshi
This market tracks whether Duke will win its college football game against Georgia Tech by a margin exceeding 1.5 points. Currently, the probability of Duke winning by over 1.5 points is 51.0%, while the probability of Duke winning by over 2.5 points is 49.0%. Trading occurs on Kalshi, and the market will resolve based on the final score of the Duke vs Georgia Tech game originally scheduled for October 10, 2026, as reported by official game results. Keep a close watch on the outcome of the game itself on October 10, 2026, as that will determine the final resolution of this market.
All markets resolve based on the official final score of the Duke vs Georgia Tech college football game scheduled for October 10, 2026. For markets where Duke wins by a specified margin, if Duke's point differential exceeds the stated threshold, that market resolves to Yes; otherwise, it resolves to No. Conversely, for markets where Georgia Tech wins by a specified margin, if Georgia Tech's point differential exceeds the stated threshold, that market resolves to Yes; otherwise, it resolves to No. If the game is postponed but commences within 48 hours of its original scheduled start time, all markets remain open and resolve according to the final result. If the game fails to start within 48 hours of its scheduled time, all markets resolve to a fair price, determined under conditions outlined by the event operator. The operator emphasizes no official affiliation with the NCAA, and all trademarks remain property of their respective owners.
Typically, prediction market odds reflect the wisdom of the crowd and can differ from traditional sportsbook odds. Sportsbooks often set initial lines to balance betting action and incorporate a profit margin, while this market allows traders to directly express their beliefs about the probability of different outcomes. If a significant discrepancy emerges between this market and sportsbook odds, it may indicate that prediction market participants have access to information or insights not yet fully incorporated by sportsbooks, or simply disagree with their assessment of the game. It's a fascinating comparison to monitor as the event approaches.
On Kalshi, this market is priced through a continuous order book where traders buy and sell contracts representing different outcomes of the Duke-Georgia Tech spread. The price of each contract reflects the market’s collective assessment of the probability of that outcome occurring. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. As more traders participate and new information becomes available, the prices adjust dynamically, providing a real-time indication of market sentiment. Traders aim to profit by accurately predicting the outcome and capitalizing on price discrepancies, effectively creating a decentralized forecasting system for the game’s spread.
This market resolves around Oct 10, 2026, with the outcome confirmed once the final point spread of the Duke versus Georgia Tech game is verifiable from credible public reporting. The resolution will be based on the official result reported by the governing body of college basketball, ensuring an objective and transparent determination of the winning outcome. Traders will then be able to claim their winnings or fulfill their obligations based on their positions in this market at the time of resolution. The final spread will be the determining factor.
Several factors could influence the price movement of this market leading up to Oct 10, 2026. News regarding key player injuries for either Duke or Georgia Tech would likely have a significant impact. Changes in coaching strategies, unexpected team performance in preceding games, or even weather forecasts could all shift market sentiment. Public opinion, as reflected in polls and expert analyses, can also play a role, though this market represents a distinct, financially-driven forecast. Any significant information that alters the perceived probability of either team covering the spread could cause the market to react.