Kalshi’s midterm favorites win broadly as prices precede network calls
Kalshi's midterm recap says the candidates its traders favored won 98 percent of the nearly 500 races resolved by 6 AM ET on November 4, including 95 percent of House races, 94 percent of Senate races and 94 percent of governor races, with prices moving hours ahead of network calls.
Candidates favored by Kalshi traders won 479 of 487 resolved midterm contests, according to Kalshi’s recap. The platform put that success rate at 98 percent for the nearly 500 races resolved by 6 AM ET on November 4.
The figures represent Kalshi’s account of its market performance at that cutoff, rather than a tally covering every midterm contest. Its recap also described prices shifting hours before television networks called races.
Results across race categories
According to Kalshi, trader-favored candidates won 95 percent of resolved House races. The corresponding figures were 94 percent for Senate races and 94 percent for governor races.
Those category-level results show favorites winning across all three groups, although each reported percentage was below the 98 percent overall figure. The supplied summary does not provide category-level race counts or details about the price movements preceding network calls.
What it means for prediction markets
- The cutoff matters: The reported 98 percent applies to the 487 contests resolved by 6 AM ET on November 4, not necessarily the complete midterm slate.
- Picking winners differs from calibrating probabilities: The share of favorites that won does not, by itself, establish whether their market prices accurately reflected their chances.
- Timing is a separate claim: Kalshi says prices moved hours ahead of network calls, but the supplied recap does not include race-by-race timing or price data to assess that lead.
Sources & attribution
- Published
- Source
- Kalshikalshi.com
- Publisher
- https://kalshi.com
- Source URL
- The feed did not publish this story's article address.
Full attribution under the Digital Millennium Copyright Act (DMCA), 17 U.S.C. § 512: this article is an original report by Infiniti Intelligence that summarizes the reporting of the publishers named above, links to their original work, and reproduces no protected expression beyond brief factual reference and in-line attribution (“according to Kalshi”). All rights in the underlying reporting remain with the publishers listed; nothing here implies endorsement by or affiliation with them. Rights holders may request correction, update or removal through the contact address published at infiniti.w3ai.io.
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