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An Election Day Special With Nate Silver

Odd Lots

Hosted by Joe Weisenthal and Tracy Alloway

42m
Transcript

Original podcast

Summary

Written by a model from the transcript; not yet reviewed.

This election-day special features data analyst and Silver Bulletin founder Nate Silver discussing the state of the 2026 midterm elections, presidential unpopularity, and the accuracy of modern polling and prediction markets. Joe Weisenthal, Tracy Alloway, and the guest explore why President Trump's approval rating sits around 37% amid voter frustration over gas prices and broken promises, and how those national tailwinds are driving Democratic advantages in the House and Senate. The conversation also examines why systemic polling errors primarily occur during presidential years with Trump on the ballot rather than midterms, the limitations of synthetic AI respondents, and how large language models are transforming quantitative modeling and software development.

  • President Trump's approval rating sits around 37%, which is among the worst for a president at a midterm since Harry Truman in 1946. 4:12
  • Systematic polling errors that underestimated Trump occurred in presidential years when he was on the ballot, but have not appeared in midterm or off-year elections. 8:44
  • Artificial intelligence tools can dramatically accelerate coding workflows and data modeling tasks, effectively serving as an expert programming assistant for technical projects. 46:33

Chapters

  1. 0:00
  2. 2:30
    Episode Introduction and Host Greeting

    Joe and Tracy introduce the Odd Lots podcast and set the stage for the Election Day special.

  3. 3:23
    Election Day Special Announcement

    Hosts announce the special focus on the upcoming election and introduce Nate Silver as the guest.

  4. 7:51
    Polling Errors and Correlation

    Silver explains how polling errors are correlated across states and the challenges they pose to accurate forecasts.

  5. 9:21
    AI’s Role in Modeling and Forecasting

    Silver talks about how AI tools have transformed data modeling and election forecasting.

  6. 10:04
    Turnout Dynamics in Midterms

    The conversation turns to differential turnout, especially among unlikely voters, and its significance for the midterm elections.

  7. 12:28
    Closing Reflections and Takeaways

    The episode wraps up with final thoughts on the election’s implications and future political trends.

  8. 27:43
    Gerrymandering and Its Effects

    Silver and hosts analyze how gerrymandering can backfire on Republicans and influence seat outcomes.

  9. 29:44
    Governor Races and Their Significance

    Discussion focuses on the importance of gubernatorial contests and how they could shape the political landscape.

  10. 42:23
    Prediction Markets vs. Models

    Hosts compare prediction markets to statistical models, exploring their strengths and weaknesses.

  11. 48:00
    Nate Silver on Modeling and Productivity

    Nate Silver discusses his modeling approach, the role of initiative, and how his models inform election predictions.

  12. 49:29
    Polls Becoming Models and Self-Correction

    Hosts explore how modern polls are evolving into models and the impact of self-correction on accuracy.

Highlights

  • 4:12

    Historical Unpopularity of the Presidentdata

    The guest explains that President Trump's approval rating sits at approximately 37%, representing one of the worst marks for a president at a midterm since Harry Truman in 1946.

  • 8:44

    Absence of Polling Errors in Midtermsinsight

    The guest notes that while systemic polling errors underestimated Trump in presidential cycles, those same errors do not appear in midterm elections where Trump is not on the ballot.

  • 12:51

    Senate Probability Discrepanciesdata

    The hosts and guest discuss prediction market probabilities versus internal models, noting that platforms like Polymarket and Kalshi show Democrats leading significantly in Senate control odds.

  • 14:57

    Generic Ballot Headwindsinsight

    The guest explains that a nine-point Democratic lead on the generic ballot creates severe headwinds that make it mathematically difficult for Republicans to hold key seats.

  • 22:00

    Rational Actors in Polling Adjustmentsinsight

    The guest analyzes how pollsters apply likely voter models to raw numbers, illustrating that pollsters act as rational agents trying to avoid systematic misses.

  • 24:34

    Limitations of AI Synthetic Respondentsinsight

    The guest argues that polling cannot be outsourced to AI digital twins because synthetic models tend to reproduce generic stereotypes rather than capture complex human diversity.

  • 46:33

    Accelerating Code with AIstrategy

    The guest shares how utilizing AI tools for complex programming and auditing has dramatically increased his productivity when building statistical models and sports simulators.

Quotes

  • “Trump is kind of, well, people are bored of him and tired of him, right?”
    Unnamed speaker · 11:16
  • “I think people are just like, he's been president for, I guess, six years, right?”
    Unnamed speaker · 11:21
  • “The background conditions like couldn't be better for Democrats, right?”
    Unnamed speaker · 4:38
  • “You either have to lie and say it's a toss-up.”
    Unnamed speaker · 5:35
  • “The markets were actually overconfident relative to my model in 2016 on Hillary Clinton, right?”
    Unnamed speaker · 43:24
  • “I feel like I'm getting two days of work done in, in a 10-hour day sometimes.”
    Unnamed speaker · 48:20
  • “And, and I feel like that some of the time, but, but again, I'm probably in the 99.9th percentile of like,”
    Unnamed speaker · 48:24
  • “These crazy American voters, we're done trying to understand anything about them because we have nothing, we have no usable information on them.”
    Joe Weisenthal · 51:02
  • ChatGPT 0:16–0:26
  • ChatGPT 1:32–1:37
  • Boomi 1:52–2:11
  • Bloomberg Media Studios and the Dubai Department of Economy and Tourism 17:24–17:29
  • Delta Sky Miles Reserve Business American Express Card 18:49–19:57
  • IBM 34:40–35:08
  • Odd Lots 51:13–52:10
  • Empower 52:43–53:14
  • ChatGPT 53:15–54:01
  • Pandora 53:56–54:11

About this episode

Nate Silver tells us he is calling this midterms the “rock and a hard place election” — the background conditions are great for Democrats to win both the House and the Senate, but for that to come to pass, the party has to pull off some things that haven't happened in generations, like winning Texas. To believe that will happen requires a certain leap of faith, which is anathema to pollsters. Still, the polls generally believe Democrats are favored, but many professional pollsters would end up with egg on their face if the night does not go that way. Silver — the founder of Silver Bulletin — joins us today to discuss why popular narratives around polling error are wrong, prediction markets, why he doesn't think AI will replace pollsters, and what he is paying attention to tonight as the polls close. Read more: When Will We Know Who’s Won the Midterm Elections? https://www.bloomberg.com/news/articles/2026-11-02/when-will-we-know-who-s-won-the-midterm-elections?utm_medium=referral&utm_source=podcast&utm_campaign=odd_lots&utm_content=article Trump’s DOJ Turns to Supreme Court in California Ballot Case https://www.bloomberg.com/news/articles/2026-11-02/trump-s-doj-turns-to-supreme-court-in-california-ballot-clash?utm_medium=referral&utm_source=podcast&utm_campaign=odd_lots&utm_content=article Only http://Bloomberg.com subscribers can get the Odd Lots newsletter in their inbox each week, plus unlimited access to the site and app. Subscribe at bloomberg.com/subscriptions/oddlots https://www.bloomberg.com/subscriptions/oddlots?in_source=oddlotspodcast Subscribe to the Odd Lots Newsletter http://bloomberg.com/subscriptions/oddlots Join the conversation: discord.gg/oddlots https://discord.gg/oddlots See omnystudio.com/listener https://omnystudio.com/listener for privacy information.

Transcript

0:00
42:59

10,042 words · 8 speakers

Speaker names marked are inferred from speaking time and the show’s known hosts — they are not voice-verified.

Topics

  • Bloomberg

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