World Cup: Cape Verde Stage of Elimination

According to the latest prediction market data for the query “World Cup: Cape Verde Stage of Elimination”, traders have formed a strong consensus.

Currently, Round of 32 is dominating the market with an overwhelming 93% chance of winning. Round of 16 follows in second place at 5.3%, while Quarterfinals sits in third with 1.9%. The betting volume for this specific market has already reached $92.4K, reflecting intense industry interest.

To better assess where each potential outcome stands, the market can be segmented into three distinct trading tiers based on implied probability and contract pricing:

🥇 Tier 1: The Dominant Leader

• Round of 32 (93%): Currently commanding the highest probability, Round of 32 is heavily favored by the order book. Traders looking to back this outcome face a “Buy Yes” contract price of 93¢, signaling a high degree of market conviction. This contract alone has generated $35.5K in volume.

🥈 Tier 2: The Primary Challengers

• Round of 16 (5.3%): Positioned as the most viable alternative, Round of 16 maintains a 5.3% chance of resolving true. Its “Buy Yes” shares currently trade at 5¢.
• Quarterfinals (1.9%): Sitting in third place with a 1.9% probability, the market shows measured skepticism toward Quarterfinals, treating it as an outside wildcard unless momentum shifts.

🥉 Tier 3: The Long-Tail Options (Combining for ~0%)

Beyond the top three choices, a wide field of macro variables and long-shot outcomes are being tracked. While their individual probabilities hover low, they represent crucial hedges for speculative traders:

• Alternative Options: This includes Semifinals (0.2%), Champion (0.2%), and Final (0.1%).
• Speculative Volume: Despite low statistical likelihood, certain long-tail contracts like Semifinals are still attracting notable interest.

This market will resolve according to the stage of the 2026 FIFA World Cup at which Cape Verde is eliminated. If Cape Verde wins the tournament, this market will resolve to 'Champion'.

If Cape Verde is disqualified, withdraws, is removed from the tournament, or the tournament is partially completed and not finished for any reason, this market will resolve according to the furthest completed round reached by Cape Verde based on the best available official information.

If the 2026 FIFA World Cup is cancelled in full, postponed after August 2, 2026, 11:59 PM ET, this market will resolve to 'Other'.

The resolution source for this market will be official information from FIFA; however, a consensus of credible reporting may also be used.

While human consensus and speculative volume shape the broader prediction market, our quantitative algorithms offer a data-driven counter-perspective. By analyzing fundamental signals, underlying trends and historical distributions, our AI Valuation model calculates an independent “Fair Value” probability for each outcome.

Comparing this Fair Value against the current Trade Value uncovers major disparities — known as the Expected Value (EV) Gap. Contracts with a positive EV Gap represent statistically underpriced outcomes, whereas a negative EV Gap flags a potential market overreaction.

Top AI Alpha & Mispriced Arbitrage Opportunities

Based on the latest data model run, several key contracts stand out with significant deviations:

• The Most Overvalued Outcome Round of 32 currently trades at 93%, but our AI places its Fair Value at just 63.5%. This creates a large negative EV Gap of -29.5%, suggesting the crowd may be overhyping this outcome and driving the premium too high.
• The Best Value Play (Highest EV) Our model identifies Final as the premium value opportunity on the board. While the market only assigns it a 0.1% trading probability, our AI’s Fair Value assessment sits at 21.3% — yielding an impressive +21.3% EV Gap.
• Under-the-Radar Dark Horses Other notable discrepancies include Semifinals (EV Gap: +14.4%) and Champion (EV Gap: +11.6%). These long-tail opportunities are heavily discounted by the live order books despite stronger statistical backing from our predictive model.