What a safe-bet candidate’s loss means for Democrats’ odds in November

Why Progressive Candidates’ Narrow Wins Signal Caution for November

Qwenews.com – A segment of this report was originally published in CNN’s What Matters newsletter. Readers can subscribe at no cost through the provided link.

Two consecutive weeks of primary elections delivered unexpected outcomes for left-leaning contenders across competitive states, offering a crucial insight for political observers: the current landscape is far more unpredictable than it appears. Without robust polling data in either Michigan or Wisconsin, the substantial leads attributed to progressive hopefuls stemmed primarily from partisan surveys. Prediction market participants mirrored this sentiment, placing heavy bets on these candidates. Together, these factors produced an illusion of inevitability before voting began.

Francesca Hong, a democratic socialist serving in the Wisconsin state assembly, held a 95 percent probability of winning the Democratic gubernatorial primary until Tuesday’s election day, according to Kalshi. CNN maintains a partnership with Kalshi and incorporates its data for major event coverage, though editorial staff members cannot participate in prediction markets. Other platforms like Polymarket similarly backed Hong’s candidacy.

Hong ultimately fell short in an extremely close contest against David Crowley, the establishment-aligned Milwaukee County executive who surprisingly withdrew from the race before re-entering. By Wednesday morning, the margin between them remained under 5,000 votes. Neither contender surpassed 40 percent of the total vote share. Two additional well-known figures—Mandela Barnes and Sara Rodriguez—exited the race before Election Day but failed to remove their names from ballots, collectively capturing approximately 8 percent of all votes cast.

Tracking the Shift in Voter Sentiment

By 9 p.m. Eastern Time, the contest appeared destined for a tight finish, prompting Kalshi traders to forecast a Crowley triumph. Throughout the evening, probability estimates fluctuated dramatically. CNN did not officially project Crowley’s victory until 3 a.m. Eastern Time.

One week prior in Michigan, Abdul El-Sayed emerged as another confident progressive favorite. Recent polls showed him leading, though none satisfied CNN’s reporting thresholds. These surveys may have influenced prediction site participants nonetheless. On Kalshi’s platform, El-Sayed’s victory probability exceeded 97 percent on the eve of the primary. His odds never dipped below 94 percent during vote counting. While El-Sayed secured the win, he received less than 49 percent of the vote, edging his moderate opponent by a single percentage point.

In both scenarios, bettors’ near-certainty on Kalshi likely resulted from surveys indicating advantages for Hong and El-Sayed. However, the most recent polling came predominantly from partisan organizations. Lacking comprehensive high-quality data, public sentiment dominated social media discussions and generated momentum specifically for progressive contenders.

The final independent poll meeting CNN’s criteria in Wisconsin occurred in late July through Marquette University. That survey showed Hong leading by double digits, with 46 percent support among registered voters planning to participate in the state’s Democratic primary. Crucially, the contest remained fluid at that time. The Democratic establishment had not yet voiced concerns about Hong or consolidated behind Crowley. Approximately one-third of respondents expressed uncertainty about their selection when Marquette conducted its survey. Barnes occupied second place in those results before withdrawing just one day after publication.

Accurately measuring voter preferences proves challenging when candidates continuously alter their positions. Crowley, the eventual victor, had only recently returned to the race. Meanwhile, public examination of several of Hong’s previously controversial stances was beginning.

“Sometimes what polling tells you is that there’s a lot of uncertainty and room for shifts in a race,” noted CNN’s polling editor, Ariel Edwards-Levy.

Essentially, the campaign remained highly active when the last reliable polling took place. Hong’s 95 percent probability on prediction markets never indicated she would receive 95 percent of the vote or even approach that figure. Rather, it reflected that most bettors believed she would prevail based on available information—polling results, trends from recent elections, their assessments of candidate momentum, and other elements contributing to collective wisdom.

Beyond these limitations, the situation may worsen when executives from Polymarket and Kalshi promote their platforms as “truth machines,” despite the considerably more complex reality. Kalshi’s founders have emphasized this positioning, though the actual mechanics of prediction markets reveal greater nuance than such marketing suggests.