TOTAL VOLUME:

$134.2b

24H VOL:

$134,145,987

24H TRANSACTIONS:

2,388,728,490

OPEN INTEREST:

$1,441,166,947

406,422

Markets across

30,383

events

MATCHED EVENTS:

2,688

PLATFORM COVERAGE:

5

Polymarket:

39%

VS.

Kalshi:

61%

BETA
Dashboards
Tour
All
Sports
Valorant: Chivas Esports vs LYON (BO3) - VCL Latin America North Group Stage
polymarket
kalshi

Valorant: Chivas Esports vs LYON (BO3) - VCL Latin America North Group Stage

Volume:
$37,894

Map Handicap: LYON (-1.5) vs Chivas Esports (+1.5)

 - Polymarket

Map Handicap: LYON (-1.5) vs Chivas Esports (+1.5) - Polymarket

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Feb 25, 2026

Map Handicap: LYON (-1.5) vs Chivas Esports (+1.5)

100%chance
Amount

$

Trade on
polymarket

Trade on Polymarket

At 100¢ buys you 100 shares | Odds: 100% Total Payout: $100 | Net Profit: $0 Multiplier: 1.00x | ROI: 0% | APY: N/A Illiquid market
You will be redirected to the platform to complete this trade.
Outcome
Trade
Chance %
Price
Spread
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
polymarket

Map Handicap: LYON (-1.5) vs Chivas Esports (+1.5)

100%
Yes 100¢No 0¢
—
N/A
$2,083
0%
N/A
N/A
N/A
kalshi

LYON

100%
Yes 100¢No 0¢
—
N/A
$1,392
0%
0%
$1,100
N/A
polymarket

Match Winner

0%
Yes 0¢No 100¢
—
N/A
$14,844
0%
N/A
N/A
N/A
polymarket

Map 2 Winner

0%
Yes 0¢No 100¢
—
N/A
$11,039
0%
N/A
N/A
N/A
polymarket

Map 1 Winner

0%
Yes 0¢No 100¢
—
N/A
$4,742
0%
N/A
N/A
N/A
kalshi

Chivas Esports

0%
Yes 0¢No 100¢
—
N/A
$2,562
0%
0%
$2,035
N/A
polymarket

O/U 2.5 Games

0%
Yes 0¢No 100¢
—
N/A
$1,232
0%
N/A
N/A
N/A
Total markets: 7

Description

This event group covers a best-of-three Valorant match between Chivas Esports and LYON in the VCL Latin America North Group Stage, scheduled for February 24, 2026 at 8:00 PM ET. Markets span match winner, individual map winners, total maps played, and map handicap outcomes across Polymarket and Kalshi platforms.

PredictionHero - Resolution Divergence Alerts (RDA)

Divergence Detected

Issue: Polymarket provides five detailed, interconnected markets with explicit edge-case rules for forfeits, disqualifications, incomplete matches, and delays. Kalshi provides a single binary market with minimal edge-case specification, creating ambiguity on cancellation and delay scenarios.Hero tip: Polymarket offers superior clarity and granularity for traders seeking exposure to specific outcomes (map winners, handicap). Kalshi's binary structure is simpler but leaves cancellation, forfeiture, and delay handling undefined. If you trade Kalshi, request written clarification on how 7+ day delays and pre-match forfeits are handled before settlement.

Critical divergence points:

  • Polymarket: Five interconnected markets (match winner, map 1, map 2, total maps, handicap) with explicit resolution rules. Match winner resolves 50-50 on cancellation, tie, or 7+ day delay without a winner. Forfeits/disqualifications before match start also resolve 50-50. Maps and handicap markets count forfeit/disqualification/walkover maps toward totals if match is completed. Incomplete matches with one team winning by opponent forfeiture resolve to the winning team. Primary source: vlr.gg within 2 hours, fallback to credible reporting and video evidence.
  • Kalshi: Single binary market: resolves Yes if either Chivas Esports or LYON wins the match originally scheduled for Feb 24, 2026. No explicit handling of cancellations, forfeits, disqualifications, incomplete matches, or delay thresholds. Resolution source and fallback procedures not specified.
Our PredictionHero Resolution Divergence Alerts (RDA) are there to help users identify potential differences across platforms. They do not replace or supersede the official rules and description of any prediction market. Users are solely responsible for reviewing and understanding the applicable rules and resolution criteria before placing any trade or bet. If you notice a potential inconsistency, discrepancy, or error in an alert, please report it to our team so we can review and improve the accuracy of our data.