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World Cup Upsets Keep Coming, the 'Dumb Money' in Prediction Markets Got Me Laughing

The 2026 FIFA World Cup has been marked by frequent upsets, turning prediction markets into a high-stakes game of chance. Odaily Planet Daily examines several high-profile cases where "smart money" bets went disastrously wrong, questioning if these losses offer any contrarian insights. A major upset occurred when underdog Cape Verde held football powerhouse Spain to a 0-0 draw. A trader, betting $1 million on a Spanish victory at 0.92 odds to earn $85,000, instead lost their entire principal. This match set a precedent for underdogs stifling favorites. Similarly, Portugal, despite featuring star Cristiano Ronaldo, was held to a 1-1 draw by debutants DR Congo. A trader with a 49% win rate lost over $243,000 predicting a Portuguese win. The article highlights the case of a notorious "anti-indicator" address, @Zzzz87. After initially losing over $620,000 (with a sub-40% win rate) by betting on underdog upsets, the address switched strategy. It began backing favorites in the knockout stages, reportedly turning a $269,000 profit in a week, despite being down $255,000 over the past month. This exemplifies the market's volatility and the difficulty of establishing a consistent strategy. The core conclusion is that football's inherent unpredictability defies simple logic based on player valuations or national rankings. Whether following "smart money" or betting against "dumb money," the only certainty is uncertainty. The article advises enthusiasts to enjoy the games while remaining adaptable in their approach to the prediction markets.

Odaily星球日报07/02 09:41

World Cup Upsets Keep Coming, the 'Dumb Money' in Prediction Markets Got Me Laughing

Odaily星球日报07/02 09:41

The World Cup has only been played for a few days, but some AI prediction models have already been crowned as oracles, while others have stumbled badly.

The 2026 FIFA World Cup has sparked significant interest not only on the pitch but also in AI-driven match prediction. Major models like Qwen, Copilot, and ChatGPT are being used to forecast outcomes, scores, upsets, red cards, and key player performances. Qwen gained early attention by accurately predicting Mexico's 2-0 win over South Africa (including a red card risk) and South Korea's 2-1 victory over the Czech Republic in the opening matches. Copilot's pre-tournament predictions had notable successes, such as correctly calling the Mexico 2-0 scoreline, South Korea's 2-1 win, and Brazil's 1-1 draw with Morocco. However, it also had clear misses, failing to predict upsets like Australia's 2-0 win over Turkey or Switzerland's draw with Qatar. ChatGPT provided detailed analytical reasoning, correctly predicting Mexico's 2-0 win, but its full-tournament predictions tended to favor favorites, missing several underdog results and draws. Tests pitting multiple models (ChatGPT, Gemini, Grok, Claude) against the same match, like Mexico vs. South Africa, showed varying predictions, with only some hitting the exact score. In summary, while AI models like Qwen have shown promising early results in specific match details, and others have had isolated successes, they collectively struggle to consistently identify upsets and underdog performances. AI is becoming an additional reference tool for prediction markets but is far from a definitive source.

marsbit06/16 03:53

The World Cup has only been played for a few days, but some AI prediction models have already been crowned as oracles, while others have stumbled badly.

marsbit06/16 03:53

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