TOTAL VOLUME:
$154.5b
24H VOL:
$271,200,656
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,922,627,141
420,368
Markets across
40,352
events
MATCHED EVENTS:
4,484
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 3, 6:40 PM EST
Kalshi
This market tracks the total number of fourth down conversions—over or under 0.5—in the Eastern Michigan versus UMass college football game. Currently, the consensus probability of Eastern Michigan vs. UMass: Total 4th Down Conversions O/U 0.5 is 100.0%. This aggregation combines data from Polymarket and Kalshi, with resolution based on data reported at https://www.ncaa.com/. Keep an eye on the game itself, scheduled for October 3rd, as the final fourth down conversion statistics will determine the outcome of this market.
In the upcoming college football game between Eastern Michigan and UMass, scheduled for October 3 at 3:30PM ET: This market will resolve to "Eastern Michigan" if Eastern Michigan win the game. This market will resolve to "UMass" if UMass win the game. Overtime is included if played. If the game ends in a tie, this market will resolve 50-50. If the game is postponed, this market will remain open until the game has been completed. If the game is canceled entirely, with no make-up game, this market will resolve 50-50.
The market resolves to Yes if either Eastern Michigan or UMass wins the college football game scheduled for October 3, 2026. If the game is postponed but begins within 48 hours of its originally scheduled start time, the market will remain open and resolve based on the official final result. If the game is cancelled or not started within 48 hours of its originally scheduled start, the market will resolve to a fair price.
Prices on Polymarket and Kalshi can diverge for several reasons. Polymarket and Kalshi can show different implied probabilities for the same outcome because of liquidity, fee structure, participant mix, and how each venue defines the contract. Each platform attracts a different pool of traders with varying levels of expertise and access to information regarding the EMU vs. UMass game. Trading volume also plays a role; lower volume on one platform can lead to greater price volatility and wider spreads. Furthermore, the specific market structures and fee schedules on each platform can influence trading behavior and, ultimately, the prices observed. These factors contribute to the dynamic pricing you see across different prediction markets.