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: Jul 3, 10:01 PM EST
Kalshi
Francisco Lindor, Juan Soto, and Matt Olson will compete in the New York Mets vs Atlanta Braves game on July 3, 2026. These markets track home runs hit by each player during the game.
If Francisco Lindor records 1+ home runs in New York M vs Atlanta professional baseball game originally scheduled for Jul 3, 2026 at 7:15 PM EDT, then the market resolves to Yes. If Francisco Lindor records 2+ home runs in New York M vs Atlanta professional baseball game originally scheduled for Jul 3, 2026 at 7:15 PM EDT, then the market resolves to Yes. If Juan Soto records 1+ home runs in New York M vs Atlanta professional baseball game originally scheduled for Jul 3, 2026 at 7:15 PM EDT, then the market resolves to Yes. If Juan Soto records 2+ home runs in New York M vs Atlanta professional baseball game originally scheduled for Jul 3, 2026 at 7:15 PM EDT, then the market resolves to Yes. If Matt Olson records 1+ home runs in New York M vs Atlanta professional baseball game originally scheduled for Jul 3, 2026 at 7:15 PM EDT, then the market resolves to Yes. If Matt Olson records 2+ home runs in New York M vs Atlanta professional baseball game originally scheduled for Jul 3, 2026 at 7:15 PM EDT, then the market resolves to Yes.
Prediction market odds and sportsbook odds often diverge because they reflect different participant bases and incentive structures. Sportsbooks set lines to balance action and lock in profit margins, while prediction markets aggregate the collective beliefs of traders risking real capital on outcomes. This market aggregates trader conviction through continuous price discovery, which can reveal edge over traditional sportsbook pricing. Comparing the two can highlight where public perception on home run totals may differ from professional oddsmakers, offering traders a lens into market inefficiencies and alternative viewpoints on game dynamics.
On Kalshi, this market is priced through a continuous order-book mechanism where traders submit bids and asks for shares representing each home run outcome. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price of each share reflects the aggregate probability assigned by the market; higher prices indicate stronger trader conviction in that outcome. As new information emerges—lineup changes, weather updates, or injury reports—traders adjust their positions, moving prices in real time. This dynamic pricing model ensures the market continuously incorporates fresh signals and trader sentiment throughout the pre-game and live windows.
This market resolves around Jul 4, 2026, once the game concludes and the final home run count is confirmed. The outcome is verified against credible public sources to ensure accuracy. Until that point, traders can adjust positions as the game unfolds and new data becomes available. Resolution timing depends on when official statistics are published and validated, which typically occurs shortly after the final out. Early resolution is possible if the outcome becomes mathematically certain before the game ends.
Several catalysts can shift prices in this market before resolution. Lineup announcements, roster changes, or injury updates to key power hitters will influence trader expectations. Weather conditions—wind speed and direction, temperature, and humidity—significantly affect home run distance and frequency. Pitching matchups and bullpen availability can alter game flow and scoring opportunities. Recent performance trends, such as a team's home run rate over their last ten games, provide momentum signals. Real-time game developments like early scoring, pitcher changes, or momentum swings will prompt traders to reassess probabilities and adjust their positions accordingly.