Prediction market traders are betting on who could be the next member of Donald Trump’s Cabinet to leave office, after correctly forecasting Democratic victories in both chambers of Congress at the midterm elections.
A Polymarket market has attracted almost $190,000 in trading, with Defence Secretary Pete Hegseth, White House chief of staff Susie Wiles and Secretary of State Marco Rubio among the leading names.
As of Friday morning, Hegseth had the highest implied chance of departure, at about 31 per cent. Wiles was next on 24 per cent, followed by Rubio on 8 per cent, while traders put the odds of no Cabinet departure before 2027 at roughly 27 per cent.
Hegseth’s position at the top of the market follows criticism of his role in the war in Iran. Republican Congressman Thomas Massie plans to revive an effort that could see the House vote as early as next week on articles of impeachment accusing Hegseth of waging the war without congressional approval.
Massie’s move comes after the Republican Party’s losses in the midterms, with the incoming Democratic majorities promising investigations into several aspects of the Trump administration, including the conflict and allegations of corruption.
Wiles has also faced scrutiny as Republicans look for someone to blame for the election result. Caroline Sunshine, a former Trump aide, called for her resignation in an interview with Fox News on Wednesday, saying: “Her campaign skills have not translated into governing.”
Rubio’s future has also become a subject of speculation, including whether he might pursue a presidential bid in 2028. He has discussed stepping down with White House officials, who asked him to remain in the administration, Bloomberg reported.
Rubio rejected the suggestion this week, telling The New York Times that serving until the end of Trump’s term has “always been my plan”.
The market activity comes after traders on Kalshi and Polymarket were credited with accurately predicting the Democratic wins in both chambers and several important Senate races, strengthening the platforms’ reputation for forecasting political outcomes.
