预测市场平台Polymarket和Kalshi允许用户以1至99美分的合同价格对市长、州长和美国参议员等各级选举结果进行交易1，随着2026年选举临近，这类交易量的激增正引起全国选举管理部门的广泛关注。美国选举管理协会主任Jared DeMarinis指出："这是一个令人困扰的趋势，全国各地的选举管理部门都必须应对"1。
各州政府担心高额赌注可能对选举过程造成负面影响。根据全国州立法会议的统计，已有半数州制定了广泛禁止对选举下注的法规1。这些担忧并非无实例支撑——Kalshi曾在8月31日披露，因北卡罗来州共和党众议院候选人Laurie Buckhout在自己的选举上交易，该平台对其处以三年禁赛和罚款1。此外，威斯康星州州长初选中，预测市场曾严重看好一位最终失败的候选人，而洛杉矶市长初选中，有网红指责选举官员作弊，并指向支持共和党候选人Spencer Pratt的市场赔率1。
关于市场的预测准确性，Kalshi声称其研究表明其市场与结果高度相关——被给予60%概率的事件最终发生近60%的时间1。但专家警示潜在风险。Columbia Law School教授Joshua Mitts表示存在可能的操纵风险："突然间，他们就成了领跑者，只因为局外人对他们下了大赌注"1。
As the 2026 U.S. elections approach, trading activity on prediction market platforms has surged, prompting widespread concern among election officials and state governments.1 Platforms including Polymarket and Kalshi allow users to trade contracts on election outcomes at prices ranging from one to ninety-nine cents, with markets covering races for mayors, governors, and U.S. senators across multiple jurisdictions.1
Election administrators view this trend with alarm. Jared DeMarinis, director of the American Election Association, described it as "a troubling trend that election officials across the country are having to grapple with."1 The primary concern centers on whether substantial betting volumes could manipulate election results and erode public confidence in democracy. According to the National Conference of State Legislatures, roughly half of all U.S. states maintain broad prohibitions on wagering on elections.1 Some states have moved toward enforcement; Kalshi disclosed in late August that it had imposed a three-year ban and fine on Republican House candidate Laurie Buckhout of North Carolina for trading on her own race.1
Prediction market operators defend their platforms by citing accuracy. Kalshi contends its research demonstrates strong correlation between market probabilities and actual outcomes—events assigned a sixty percent likelihood occur approximately sixty percent of the time.1 However, documented cases raise questions about market reliability and potential manipulation. In Wisconsin's gubernatorial primary, prediction markets heavily favored a candidate who ultimately lost.1 Similarly, in Los Angeles's mayoral primary, a social media influencer accused election officials of fraud and pointed to market odds supporting Republican candidate Spencer Pratt.1 Columbia Law School professor Joshua Mitts has articulated the manipulation risk plainly: "Suddenly, they become the frontrunner, just because outsiders have placed large bets on them."1
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