TOTAL VOLUME:
$154.6b
24H VOL:
$323,326,361
24H TRANSACTIONS:
2,984,640,614
OPEN INTEREST:
$1,969,435,260
419,363
Markets across
40,411
events
MATCHED EVENTS:
4,612
PLATFORM COVERAGE:
5
Polymarket:
37%
VS.
Kalshi:
63%
Closed: Oct 25, 11:29 PM EST
Kalshi
This event tracks the performance of two key players in an upcoming football game, focusing on how many times they successfully catch the ball. The outcome depends on the exact number of receptions each player achieves during the match. Payouts vary depending on whether the actual receptions meet or exceed specific thresholds.
The event features two separate markets, each tied to the number of receptions achieved by a specific player in the Kansas City vs Seattle Pro Football game scheduled for October 25, 2026. For each market, Yes contracts pay out an amount that increases with the number of receptions, following a cubic scaling formula based on receptions up to a maximum of 14. The payout schedule is structured such that the payout grows non-linearly, with the maximum payout capped at $1.00 for 14 or more receptions. No contracts pay the difference between $1.00 and the Yes payout. Both markets resolve to Yes if the specified player achieves at least one reception, with the exact payout determined by applying the formula floor(10000 x (min(s, 14) / 14)^3) / 10000, where 's' represents the official number of receptions. The structure ensures that payouts are proportional to performance but limited to a maximum value, creating a clear, formula-driven resolution mechanism for each player’s market.
Generally, prediction market odds often reflect a more accurate forecast than traditional sportsbook odds, as they aggregate the knowledge and insights of a diverse group of traders. Sportsbooks may incorporate biases or limitations in their modeling, while this market benefits from the 'wisdom of the crowd.' However, discrepancies can occur due to differing risk appetites and market dynamics. Sportsbooks often adjust odds to balance their liabilities, whereas this market is driven purely by supply and demand for contracts representing different outcomes. It’s common to see prediction markets move faster to incorporate new information.
On Kalshi, this market is priced through a continuous order book, where traders buy and sell contracts representing different reception totals for the Kansas City vs Seattle game. The price of each contract reflects the market’s 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, the prices adjust to reflect the collective intelligence of the group. This dynamic pricing mechanism ensures that the market efficiently incorporates new information and updates its predictions as the event approaches. The goal is for the market price to converge towards the true probability of each outcome.
This market resolves around Oct 26, 2026, with the outcome confirmed once the event is verifiable from credible public reporting. The final reception totals for both the Kansas City and Seattle teams will be sourced from official game statistics. The market will settle based on the combined total receptions achieved by players on both teams during the game. Any overtime periods will be included in the final reception count. The resolution process is designed to be objective and transparent, relying on publicly available data to determine the winning contracts.
Several factors could influence trading activity in this market. News regarding injuries to key wide receivers or tight ends on either team would likely cause significant shifts in the odds. Changes in weather forecasts, particularly conditions that favor passing or running, could also impact the market. Unexpected coaching decisions or strategic adjustments announced before the game might also lead to price movements. Finally, any late-breaking news related to player availability or team dynamics could trigger increased trading volume and volatility in this market as traders react to the new information.