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%

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UFC Fight Night: Gillian Robertson vs. Amanda Lemos (Women's Strawweight, Main Card)
polymarket
kalshi

UFC Fight Night: Gillian Robertson vs. Amanda Lemos (Women's Strawweight, Main Card)

Volume:
$1,005,485

Gillian Robertson vs. Amanda Lemos

 - Polymarket

Gillian Robertson vs. Amanda Lemos - Polymarket

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Mar 15, 2026

Closed: Mar 14, 11:59 PM EST

polymarket

Polymarket

View
Outcome
Trade
Chance %
Price
Spread
Liquidity
Volume
24h
7d
Open Interest
Ends in
Result
polymarket

Gillian Robertson vs. Amanda Lemos

View
100%
Yes 100¢No 0¢
—
N/A
$727,121
N/A
N/A
N/A
Settled
Yes
kalshi

Gillian Robertson

100%
Yes 100¢No 0¢
—
N/A
$103,881
N/A
N/A
$92,488
Settled
Yes
polymarket

Robertson to win by KO/TKO?

0%
Yes 0¢No 100¢
—
N/A
$1,045
N/A
N/A
N/A
Settled
No
polymarket

Fight to Go the Distance?

100%
Yes 100¢No 0¢
—
N/A
$8,795
N/A
N/A
N/A
Settled
Yes
polymarket

O/U 2.5 Rounds

100%
Yes 100¢No 0¢
—
N/A
$2,128
N/A
N/A
N/A
Settled
Yes
polymarket

O/U 1.5 Rounds

100%
Yes 100¢No 0¢
—
N/A
$297
N/A
N/A
N/A
Settled
Yes
polymarket

O/U 0.5 Rounds

100%
Yes 100¢No 0¢
—
N/A
$151
N/A
N/A
N/A
Settled
Yes
kalshi

Amanda Lemos

0%
Yes 0¢No 100¢
—
N/A
$156,833
N/A
N/A
$154,925
Settled
No
polymarket

Lemos to win by KO/TKO?

0%
Yes 0¢No 100¢
—
N/A
$4,680
N/A
N/A
N/A
Settled
No
polymarket

Fight won by submission?

0%
Yes 0¢No 100¢
—
N/A
$503
N/A
N/A
N/A
Settled
No
polymarket

Fight won by KO/TKO?

0%
Yes 0¢No 100¢
—
N/A
$51
N/A
N/A
N/A
Settled
No
Total markets: 11

Description

This event group covers a UFC Fight Night main card matchup between Gillian Robertson and Amanda Lemos in the women's strawweight division, scheduled for March 14, 2026. Markets span fight outcome (winner), method of victory (KO/TKO, submission, distance), and round duration thresholds. Resolution depends on official UFC fight results and timing.

PredictionHero - Resolution Divergence Alerts (RDA)

Divergence Detected

Issue: Kalshi market structure is tautological (Yes if either fighter wins) while Polymarket offers granular winner and method differentiation. The platforms measure different aspects of the same event.Hero tip: Kalshi's binary structure makes it unsuitable for directional fighter bets. Use it only to hedge against event cancellation. All meaningful fight outcome trading should occur on Polymarket's winner, KO/TKO, submission, and distance markets. Coordinate resolution timing: both platforms use March 28, 2026 as the cancellation cutoff.

Critical divergence points:

  • Polymarket: Eight distinct markets covering winner (Robertson vs Lemos vs 50-50), method (KO/TKO by either fighter, submission, distance), and round duration (O/U 0.5, 1.5, 2.5 rounds). Each resolves independently based on official UFC outcome. Key Quote: 'This market will resolve to Gillian Robertson if Gillian Robertson is officially declared the winner... If the fight is declared a draw or technical draw, ruled a No Contest, not scored, canceled, or postponed beyond March 28, 2026, this market will resolve 50-50.'
  • Kalshi: Single binary market: 'If Amanda Lemos wins... then resolves to Yes. If Gillian Robertson wins... then resolves to Yes.' No differentiation by method, no distance markets, no explicit edge case handling. Logically resolves Yes in all competitive outcomes regardless of winner or method.
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.