TOTAL VOLUME:
$134.1b
24H VOL:
$133,388,117
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,436,095,462
405,232
Markets across
30,526
events
MATCHED EVENTS:
2,693
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Jun 30, 11:19 PM EST
Kalshi
This event group covers a San Diego Padres vs. Chicago Cubs MLB game with conflicting market structures across platforms. Predict offers a head-to-head winner market, while Kalshi offers team total run thresholds. The underlying game is the same, but the resolution mechanics and settlement values diverge significantly.
Resolution depends on the individual run totals scored by each team in the San Diego vs Chicago C professional baseball game originally scheduled for June 30, 2026 at 8:05 PM EDT. Chicago C outcomes resolve based on runs scored by Chicago C alone, while San Diego outcomes resolve based on runs scored by San Diego alone. Each outcome corresponds to a specific run threshold for the respective team, with resolution occurring when that team's total exceeds the threshold. If the game is postponed or rescheduled, the rescheduled game determines the final run totals.
In the upcoming MLB game between the San Diego Padres and Chicago Cubs, scheduled for July 1 at 2:20PM ET: This market will resolve to "San Diego Padres" if the San Diego Padres win the game. This market will resolve to "Chicago Cubs" if the Chicago Cubs win the game. 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, or ends in a tie, this market will resolve 50-50. The primary resolution source for this market is the official final statistics of the event as recognized by the governing body or event organizers. However, if the governing body or event organizers have not published final match statistics within 24 hours after the event's conclusion, a consensus of credible reporting may be used instead.
Kalshi and Predict can show different odds on the same team total because they serve distinct trader bases, use different market mechanics, and may have varying liquidity pools. Kalshi and Predict can show different implied probabilities for the same outcome because of liquidity, fee structure, participant mix, and how each venue defines the contract. Platform design matters too: one may allow fractional shares while the other uses binary contracts, affecting how traders express conviction. Order flow timing, regional user preferences, and fee structures also influence where each platform's price settles. Savvy traders monitor both to spot arbitrage opportunities or to validate their thesis across independent prediction venues.
Key roster changes—injuries to star hitters or pitchers, trades, or late-game lineup adjustments—can shift expectations for team output significantly. Weather conditions, ballpark factors, and recent offensive trends also drive repricing. Momentum swings during the game itself, such as early runs or a pitching change, typically trigger sharp moves as traders update their models in real time. Pre-game news like lineup announcements or bullpen availability often spark volatility hours before first pitch. Monitor team news feeds and live game updates to stay ahead of market repricing.