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$134.2b

24H VOL:

$126,590,312

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2,388,728,490

OPEN INTEREST:

$1,439,516,703

404,175

Markets across

30,277

events

MATCHED EVENTS:

2,685

PLATFORM COVERAGE:

5

Polymarket:

39%

VS.

Kalshi:

61%

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North Carolina Tar Heels vs. North Carolina State Wolfpack
polymarket
kalshi

North Carolina Tar Heels vs. North Carolina State Wolfpack

Volume:
$3,474,581

North Carolina St.

 - Kalshi

North Carolina St. - Kalshi

1W

News

Positive

Negative

Neutral

Hover marker for details

Vol.

·

Resolved Feb 18, 2026

Closed: Feb 17, 10:00 PM EST

kalshi

Kalshi

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

North Carolina St.

View
100%
Yes 100¢No 0¢
—
$1,726,003
$624,416
N/A
N/A
$478,889
Settled
Yes
kalshi

North Carolina

View
0%
Yes 0¢No 100¢
—
$1,729,902
$2,596,090
N/A
N/A
$1,971,037
Settled
No
polymarket

Spread -7.5

100%
Yes 100¢No 0¢
—
N/A
$18,333
0%
N/A
N/A
N/A
polymarket

Spread -6.5

100%
Yes 100¢No 0¢
—
N/A
$12,781
0%
N/A
N/A
N/A
polymarket

Spread -5.5

100%
Yes 100¢No 0¢
—
N/A
$3,299
0%
N/A
N/A
N/A
polymarket

North Carolina Tar Heels vs. North Carolina State Wolfpack

0%
Yes 0¢No 100¢
—
N/A
$138,902
0%
N/A
N/A
N/A
polymarket

O/U 158.5

0%
Yes 0¢No 100¢
—
N/A
$48,471
0%
N/A
N/A
N/A
polymarket

O/U 155.5

0%
Yes 0¢No 100¢
—
N/A
$15,173
0%
N/A
N/A
N/A
polymarket

O/U 157.5

0%
Yes 0¢No 100¢
—
N/A
$10,068
0%
N/A
N/A
N/A
polymarket

O/U 156.5

0%
Yes 0¢No 100¢
—
N/A
$7,050
0%
N/A
N/A
N/A
Total markets: 10

Description

This event group covers a college basketball game between the University of North Carolina Tar Heels and North Carolina State University Wolfpack scheduled for February 17, 2026 at 7:00 PM ET. Markets span moneyline (winner), multiple spread variations, and over/under total points across Polymarket and Kalshi platforms.

PredictionHero - Resolution Divergence Alerts (RDA)

Divergence Detected

Issue: Kalshi moneyline market contains a logical contradiction: both possible game outcomes (NC wins or NC State wins) are stated to resolve to the same outcome (Yes), making the market fundamentally unresolvable and creating a data integrity failure.Hero tip: Avoid trading the Kalshi moneyline until the platform issues a clarification or correction. The Polymarket moneyline, spreads, and over/unders are all logically sound and resolvable. If you must trade Kalshi, focus only on markets with clear binary logic (Yes/No or Over/Under with distinct thresholds).

Critical divergence points:

  • Polymarket: Moneyline: Clean binary resolution to either 'North Carolina Tar Heels' or 'North Carolina State Wolfpack' based on game winner. Spreads: NC State -6.5 (win by 7+), -5.5 (win by 6+), -7.5 (win by 8+) resolve to NC State if threshold met, else UNC. Over/Unders: 159, 158, 157, 156 thresholds resolve Over if combined score meets or exceeds threshold, else Under. All markets: postponement keeps market open; cancellation with no makeup resolves 50-50. Key Quote: 'If the North Carolina Tar Heels win, the market will resolve to North Carolina Tar Heels.'
  • Kalshi: Moneyline: Stated as 'If North Carolina wins... resolves to Yes. If North Carolina St. wins... resolves to Yes.' Both outcomes map to identical resolution (Yes), creating logical impossibility. No clear No outcome is defined. This is a critical data integrity failure. Key Quote: 'If North Carolina wins the North Carolina at North Carolina St. men's college basketball game originally scheduled for Feb 17, 2026, then the market resolves to Yes. If North Carolina St. wins... then the market resolves to Yes.'
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.