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political forecasts
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Polymarket vs Polls: When to Trust Which

Polls measure stated intent; prediction markets price outcomes. When they diverge, the divergence tells you something. Here's our framework.

The structural difference

A poll is a snapshot of "if the election were today, who would you vote for." A prediction market is a bet on who wins on Election Day. These are different questions.

In a well-functioning market, implied probability should equal the integrated forecast over all possible paths from now to Election Day — weighted by likelihood. That integration captures:

  1. The current polling average (an input, not the whole picture)
  2. Fundamentals: economy, approval, incumbency, state partisanship
  3. Forward-looking uncertainty: debates, scandals, economic data, geopolitical shocks
  4. Historical base rates: how often the polling favorite wins at this point in the cycle

Polls capture #1 only. That's why a single poll swing might not move the market much — the market has already integrated over possible poll paths.

2024 as case study

In the final week of the 2024 US presidential race:

  • Polling average (538, RCP): essentially a coin flip between Trump and Harris
  • Polymarket: Trump at 62%, rising through the week
  • Nate Silver's Silver Bulletin model: Trump at 53%
  • Result: Trump won decisively

Markets got closer to the truth. But it's worth being careful about the lesson. One race isn't proof; it's suggestive. Markets also got 2016 "right" (Trump was priced higher than polls implied, though still below 50%) and 2020 "wrong" in interesting ways (Biden was priced correctly directionally but markets briefly spiked for Trump on election night as early results came in).

When markets and polls diverge

Our editorial rule: report the divergence. Don't pick a side.

Typical patterns:

  • Markets > polls for a candidate: traders think fundamentals, fundraising, or emerging events favor that candidate more than polls imply
  • Markets under polls: traders suspect a polling error (e.g., social-desirability bias for Trump, late-breaking undecideds)
  • Markets steady while polls swing: market has already integrated over poll-path uncertainty
  • Markets move while polls steady: news or non-polling fundamentals are changing

When we see a >5-point gap between Polymarket implied probability and a reputable polling average, we write about it. That's the signal worth surfacing.

What polls do better

  • Demographic cross-tabs: who within the electorate is shifting
  • Issue polling: what voters say they care about
  • Short-term intent: if the election were literally today

Markets do not substitute for good polling; they're a complementary signal.

What markets do better

  • Aggregating disparate information: markets can incorporate fundraising data, court rulings, and scandal potential that polls can't capture in a single question
  • Reducing idiosyncratic poll noise: any single poll has a ±3-4 point margin of error; markets smooth over many polls
  • Pricing long-term outcomes: "Who wins in 18 months" is not a meaningful polling question but is a meaningful market question
  • Responsive to news: markets move within minutes of major news; polls take days

Our framework for election coverage

For each race, we show:

  1. Current Polymarket implied probability (primary)
  2. Current Kalshi implied probability where available
  3. Polling average from 538 / RCP (cited, linked)
  4. Expert ratings: Cook Political Report, Sabato's Crystal Ball, Inside Elections

When all four agree, we describe the state of the race with high confidence. When they diverge materially, we describe the divergence and hypothesize the causes without picking a side.

Further reading