Sep 6, 2026 · 1h 15m
Michigan tests Democrats’ coalition and candidate strategy
Poll Me Twice, Shame On Me
The discussion connects one pivotal Senate contest to broader questions about Trump’s midterm impact, Democratic positioning, and the limits of election forecasting.
- 1Michigan’s Senate race exposes the tension between a favorable national environment and candidate-specific liabilities.
- 2Gaza-related turnout, primary baggage, and candidate quality complicate assumptions about Abdul El-Sayed’s coalition.
- 3Nate Silver’s FLIPR model combines polls and fundamentals while treating uncertainty and correlated errors as central features.
Don't miss
Nate Silver explains how FLIPR accounts for correlated polling errors and simulations, then emphasizes why volatile races remain difficult to forecast.
The brief
Nate Silver, Claire Malone, and Galen Druke join Jon Lovett to examine the 2026 midterms, where Trump’s influence collides with the structural disadvantages facing the president’s party.
Michigan becomes the central test: a potentially favorable Democratic environment meets questions about Abdul El-Sayed’s coalition, Gaza-related turnout, opposition spending, and Mike Rogers’s positioning.
The panel warns against turning one primary or poll movement into a sweeping theory of candidate quality, ideology, or progressive performance in a blue-wave environment.
Silver then opens the forecasting model, showing how polls, fundamentals, fundraising, historical data, expert ratings, and simulations interact rather than produce certainty.
The episode’s broader lesson is that election models are structured judgments under uncertainty, especially when polling errors correlate and volatile races resist precise forecasts.
Nate Silver
Abdul El-Sayed
Donald John Trump
Michigan
Crooked MediaBooks & mentions
Still Counting
The new Crooked Media podcast extends the episode’s focus on elections, polling, and forecasting.
Listen to the full episode and explore every guest, topic, and moment on PodLume.