TOTAL VOLUME:
$134.2b
24H VOL:
$130,522,377
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,438,389,636
404,028
Markets across
30,214
events
MATCHED EVENTS:
2,681
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Sep 14, 2:46 PM EST
Polymarket
This group encompasses prediction markets on the total number of corners taken in a Serie A match between Torino FC and AS Roma, as well as markets on corners taken by individual teams and in specific halves. Markets range from over/under totals to predicting which team will take the first corner.
Total corners markets for the Serie A game between Torino FC and AS Roma, scheduled for September 14, 2026 at 12:30 PM ET.
Total corners markets for the Serie A game between Torino FC and AS Roma, scheduled for September 14, 2026 at 12:30 PM ET.
Prediction market odds, like those found on Polymarket and Predict, often reflect a different kind of wisdom than traditional sportsbooks. Sportsbooks set lines to balance action and guarantee profit, factoring in a ‘vig’ or commission. This market, however, is driven by traders directly predicting the outcome, creating a more direct expression of collective belief. While sportsbook odds are influenced by public perception, prediction markets can sometimes offer more accurate forecasts, especially when significant information asymmetry exists. The current volume of $67,459 suggests growing interest in this market compared to traditional betting venues.
Polymarket and Predict can show different implied probabilities for the same outcome because of liquidity, fee structure, participant mix, and how each venue defines the contract. Differences in pricing between Polymarket and Predict for the Torino vs. Roma corners market can arise from several factors. Each platform has its own user base with varying levels of expertise and information. Trading volume, currently at $66,997 over the last 24 hours, can also influence price discovery. Furthermore, different platforms may have varying liquidity and risk tolerance among their traders. These factors contribute to the possibility of discrepancies, even when both platforms are assessing the same underlying event. The differing probabilities reflect the unique dynamics of each market.