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%

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LG Twins vs Lotte Giants: Spread
kalshi

LG Twins vs Lotte Giants: Spread

Volume:
$4,368

LG Twins wins by over 1.5 runs

 - Kalshi

LG Twins wins by over 1.5 runs - Kalshi

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Jun 27, 2026

Closed: Jun 27, 7:19 AM EST

kalshi

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Join Kalshi and score $25 for your first trade.
Outcome
Trade
Chance %
Price
Spread
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
kalshi

LG Twins wins by over 1.5 runs

View
0%
Yes 0¢No 100¢
100¢
N/A
$2,545
N/A
N/A
$2,508
Settled
No
kalshi

LG Twins wins by over 2.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$1,573
N/A
N/A
$851
Settled
No
kalshi

Lotte Giants wins by over 1.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$242
N/A
N/A
$192
Settled
No
kalshi

Lotte Giants wins by over 2.5 runs

0%
Yes 0¢No 100¢
100¢
N/A
$8
N/A
N/A
$8
Settled
No
Total markets: 4

Description

This event tracks the margin of victory in the LG Twins versus Lotte Giants Korea KBO game on June 27, 2026. Bettors predict whether one team will win by specific run margins.

Kalshi

Resolution is determined by the final margin of victory in the LG Twins vs Lotte Giants game originally scheduled for June 27, 2026 at 4:00 AM EDT. The event contains multiple spread thresholds covering both teams: if the Lotte Giants win by more than 2.5 runs or 1.5 runs, or if the LG Twins win by more than 1.5 runs or 2.5 runs, the corresponding market resolves affirmatively. Each threshold operates independently, allowing bettors to take positions on different victory margin scenarios. The final official box score from the completed game determines all outcomes.

Frequently asked questions

On Kalshi, the dashboard for the LG Twins vs Lotte Giants spread displays real-time odds and price movement for this Korean baseball matchup. You can monitor how traders are pricing the point spread between these two KBO League teams, track 24-hour volume activity, and review historical price charts to understand market sentiment shifts. The interface shows the current implied probability of each outcome, helping you gauge whether the market favors one team's spread advantage over the other as game time approaches.

Prediction market odds and traditional 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 like this one are driven by traders seeking to profit on their forecasts. This market may price the spread differently than major sportsbooks, offering opportunities for bettors who believe the crowd's assessment differs from the bookmaker consensus. Comparing both sources can reveal valuable discrepancies before the game begins.

On Kalshi, this market is priced through a continuous order-book mechanism where traders buy and sell shares representing each possible spread 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 collective belief about the final margin between the Twins and Giants. As new information emerges—injury reports, lineup changes, or recent team performance—traders adjust their positions, moving the price up or down. This dynamic pricing ensures the market continuously incorporates available data until resolution.

This market resolves around Jun 27, 2026, once the LG Twins versus Lotte Giants game concludes and the final score is confirmed. The outcome is determined by the actual point spread between the two teams at the end of regulation play, verified against credible public sources covering KBO League results. Traders holding positions will see their contracts settle based on whether the final margin matches the spread threshold specified in the market terms.

Key catalysts for this market include roster changes such as injuries to star players, lineup announcements, recent team performance streaks, and head-to-head matchup history. Weather conditions at game time can also influence scoring patterns and shift spread expectations. Media reports about team momentum, managerial decisions, or player form may prompt traders to reassess their positions. Additionally, any late-breaking news about player availability or team strategy could trigger significant price movement as the game approaches.