San Jose mayor behind in polls but ahead on prediction markets - San Jose Spotlight
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San Jose mayor behind in polls but ahead on prediction markets - San Jose Spotlight
"While polls by Emerson College, UC Berkeley and the Public Policy Institute of California have all put Mahan under 5% favorability in the race, the largest betting pools on Kalshi and Polymarket have put him above bigger names such as former Congresswoman Katie Porter and billionaire Tom Steyer. That's despite the fact that Steyer and Porter have fared better than Mahan in polls."
"On Friday afternoon, Mahan's odds reached 13% on a $4 million governor's race betting pool on Kalshi, ranking him higher than Steyer at 10%, former Fox News host Steve Hilton at 8% and Porter at 3%. Compare that to traditional polling by Emerson College, where survey respondents gave Mahan a 3.2% favorability rating while Steyer got 11%, Hilton got 13% and Porter got 8.4%"
"The Emerson, Berkeley and Public Policy Institute polls are scientific. They capture political opinions at one moment in time, surveying sample sizes that range between 500 and 1,600 respondents with a roughly 3% margin of error. Favorability trends on online betting markets are shaped differently. The sample size depends on how many traders buy in - and can affect the direction of candidates' odds."
San Jose Mayor Matt Mahan ranks significantly higher on online betting markets like Kalshi and Polymarket than in traditional scientific polls for California's gubernatorial race. While Emerson College, UC Berkeley, and the Public Policy Institute of California polls place Mahan below 5% favorability, betting pools rank him above candidates like Katie Porter and Tom Steyer who perform better in polls. On Kalshi's $4 million pool, Mahan reached 13% odds compared to his 3.2% in Emerson polling. Polymarket similarly shows Mahan at 8% versus his poll numbers. Scientific polls survey 500-1,600 respondents with consistent methodology, while betting market odds fluctuate based on trader participation and financial incentives, creating divergent predictions between these two forecasting industries.
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