2026 midterm prediction markets and election polls can sometimes appear to tell different stories about the same race. A candidate may hold a narrow lead in the latest polling while the prediction market gives them a significantly higher or lower probability of winning.
That does not necessarily mean that either the poll or the market is wrong. The two are measuring different things. Polls provide a snapshot of voter preferences at a particular point in time, while prediction markets provide a constantly evolving probability of an eventual outcome based on the latest information traders have available.
The difference can become particularly notable when polling is close but a prediction market gives one candidate a clear advantage. Traders may be incorporating the wider polling picture, candidate factors, the political environment, turnout expectations and other information that is not captured by a single survey.
So, why do prediction markets sometimes disagree with polls, and what can the differences tell us about the 2026 midterm races?
For the latest prices across individual Senate, House and Governor races, see iPredicta's US Midterms prediction markets page, or read our broader 2026 midterm election prediction markets analysis for an overview of the markets for control of Congress.
What these contracts actually pay on. Both venues settle on the winning PARTY, not on a named person. Polymarket.com asks "Will the Democrats win the Michigan Senate race in 2026?" and names the candidates, in its own words, "for the convenience"; Kalshi resolves Yes "if a representative of the Democratic party is sworn in". The tables below are labelled with candidate names because those people are their parties' nominees today, and the price would not follow either of them to a different party or off the ballot. The two venues also settle on slightly different events: Polymarket on the winner of the election inclusive of any run-offs, Kalshi on who is sworn in for the term beginning in 2027. Prices shown are each venue's best bid at a stated reading time, which is the price a seller could actually accept.
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Polls and prediction markets measure different things
The simplest explanation for a difference between prediction markets and polls is that they are not answering the same question.
An election poll asks voters which candidate they currently support. A prediction market asks traders to assess the probability of an eventual election outcome. That means a candidate can be ahead in a poll without necessarily being priced as the most likely winner in a prediction market.
Polls are also a snapshot of a moment in time. A survey conducted several weeks before an election captures voter preferences when respondents were interviewed, while a prediction market can continue to move as new polls, campaign developments, economic data and other information emerge.
As such, prediction market prices can reflect a much broader set of factors than the results of the latest individual poll. Traders will likely consider a set of polling results, looking for any patterns or trends, alongside the historical voting preferences of a state or district, candidate strength, turnout expectations and the wider political environment when assessing the outcome probability.
This is particularly important in closely contested 2026 races. A poll showing a candidate with a small lead does not mean traders automatically assign that candidate the same probability of winning. The size of the polling lead, other survey results, uncertainty around turnout and several other factors can all affect how the available evidence is interpreted.
The reverse can also happen. A candidate may lead a prediction market despite trailing in a recent poll if traders believe the wider body of evidence available points towards a different eventual outcome.
That is why comparing prediction markets vs polls is more useful when it goes beyond asking which number is higher. The more interesting question is what information might explain the difference.
Michigan shows why a small polling lead can produce a higher market probability
The 2026 Michigan Senate race provides a useful example of why a polling margin should not be treated as a direct measure of a candidate's probability of winning.
RealClearPolitics (RCP) averages the polls conducted in Michigan between 10 August and 24 September, and that average has Democrat Abdul El-Sayed ahead of Republican Mike Rogers by 3.0 percentage points, with El-Sayed on 47.5% and Rogers on 44.5%.
RCP does not carry out polls itself, but publishes an average based on multiple surveys to provide an indication of where the race stands.
The individual polls within that average produced a broad range of results. A New York Times/Siena College poll conducted from September 15-22 put El-Sayed five points ahead, 49% to 44%, while a co/efficient poll conducted from September 21-23 had the race tied at 50% each.
Other recent surveys also showed varying margins, including a seven-point El-Sayed lead in a Suffolk University poll conducted September 16-20 and a two-point Rogers lead in a Detroit News/Glengariff poll conducted August 31 to September 3.
Both prediction markets, however, have assigned a considerably higher probability to a Democratic win in Michigan than the polling margin alone might suggest. These prices can change as trading continues.
| 2026 Michigan Senate race | Polling average | Polymarket.com | Kalshi |
|---|---|---|---|
| Abdul El-Sayed (D) | 47.5% | 70% | 72% |
| Mike Rogers (R) | 44.5% | 29% | 27% |
Polling: RealClearPolitics average of polls conducted 10 August to 24 September 2026. Prediction-market prices: each venue's best bid, read at 07:45 UTC on 26 September 2026. Best bids do not sum to exactly one hundred per cent because each venue quotes a spread.
So why is a 3.0-point polling lead associated with a market probability around 70%?
The first reason is polling uncertainty. A polling average is an estimate of current voter support, not a prediction that the final result will match that percentage. Individual surveys can differ because of sampling, methodology, turnout assumptions and normal statistical variation. In Michigan, recent polls have ranged from a seven-point El-Sayed lead to a two-point Rogers lead, with several other surveys falling between those extremes.
Traders therefore do not have to interpret the RCP average of +3.0 as meaning the candidates have a fixed 3.0-point gap. They can instead consider the range of plausible outcomes around that estimate. If a series of polls places one candidate ahead, even by a relatively small margin, traders may assign that candidate a considerably higher probability of winning than the headline polling margin would suggest.
Timing also matters. The polling average incorporates surveys conducted over several weeks and stops on 24 September, while the prediction market can react as soon as new information becomes available. Other information not directly captured by polling, including campaign developments, candidate activity, fundraising and spending, turnout considerations and other factors also come into the equation.
There is also an important distinction between a market price and a formal statistical forecast. A contract trading at seventy cents can be interpreted as the market implying roughly a seventy per cent probability of that outcome, but the price is produced through trading between market participants. Liquidity, the balance of buying and selling and the information available to traders can all affect where the price settles.
For a fuller explanation of how prediction-market prices translate into probabilities, see iPredicta's How Prediction Market Odds Work: Cents to Probability guide.
Michigan shows why a polling margin and a prediction market probability should not be expected to converge. The poll provides an estimate of current voter support, while the market price reflects traders' assessment of how likely that evidence is to translate into an eventual election victory.
North Carolina shows why consistent polling can matter to prediction markets
The North Carolina Senate race provides a different example of how polling and prediction markets can interact.
RealClearPolitics averages the polls conducted in North Carolina between 31 August and 22 September, and that average has Democrat Roy Cooper ahead of Republican Michael Whatley by 8.2 percentage points, with Cooper on 49.5% and Whatley on 41.3%.
The individual polls behind those average figures have generally pointed in the same direction, too. A Quantus Insights poll conducted September 22 had Cooper ahead 48.4% to 43.3%, while an InsiderAdvantage survey from September 16-17 gave Cooper a 48.4% to 42.5% lead. A High Point University/YouGov poll conducted September 9-16 had Cooper ahead 50% to 42%.
Both prediction markets are considerably more confident than the polling margin implies, as the table below shows.
| 2026 North Carolina Senate race | Polling average | Polymarket.com | Kalshi |
|---|---|---|---|
| Roy Cooper (D) | 49.5% | 94% | 93.6% |
| Michael Whatley (R) | 41.3% | 6% | 6.4% |
Polling: RealClearPolitics average of polls conducted 31 August to 22 September 2026. Prediction-market prices: each venue's best bid, read at 07:45 UTC on 26 September 2026. Kalshi quotes this market in increments below one cent, which is why its figures carry a decimal place.
North Carolina illustrates a slightly different point from Michigan. Here, multiple recent surveys have consistently placed Cooper ahead, giving traders a broader body of evidence from which to assess the race.
That consistency can matter because a single poll can produce an unusual result, while repeated surveys pointing in the same direction provide more evidence about the underlying state of the race. Traders can therefore assess not only the size of a candidate's polling lead, but how consistently that lead has appeared across different surveys.
The market is not simply converting Cooper's 8.2-point polling lead into an equivalent probability. It is assessing how the wider body of evidence, including the consistency of the polling, translates into the likelihood of an eventual election victory.
What to look for when prediction markets and polls disagree
A gap between a prediction market price and the latest poll is most useful when it prompts a closer look at the evidence behind both figures.
Start with the wider polling picture rather than a single survey. Check how many recent polls are available, when they were conducted and whether they broadly point in the same direction. Check also when the average stops: a polling average that closed several days ago cannot contain news the market has already traded on.
It is also worth considering where the market price sits and whether it has moved significantly over time. A small difference between the polling picture and market probability may simply reflect normal uncertainty, while a larger or persistent gap can provide a more interesting signal to investigate.
Market activity provides another piece of context. Prediction market prices are generated through trading, so the level of activity and liquidity behind a market provides useful context when interpreting the price. Prices from markets with limited activity should be interpreted with appropriate context rather than treated in the same way as prices from heavily traded markets.
Finally, compare Polymarket.com and Kalshi as well as the polling, and check that the two contracts settle on the same event before reading anything into a gap between them. If both markets are producing similar prices despite a different polling picture, the divergence from polls is potentially more telling than if the two platforms are themselves far apart.
Conversely, a substantial difference between the trading platforms introduces another question: why are participants on the two platforms assessing the same race differently? Our guide to Polymarket vs Kalshi explores some of the structural differences between the two platforms.
Why do prediction markets disagree with polls?
Prediction markets and election polls can appear to disagree because they are measuring different aspects of the same race. Polls provide a snapshot of voter preferences, while prediction markets are looking ahead at the eventual outcome.
The 2026 Michigan and North Carolina Senate races demonstrate how that difference can play out in practice. A relatively narrow polling lead can correspond with a significantly higher market probability, while a more consistent polling advantage can be reflected in an even stronger market price.
For prediction market watchers, the gap between the two can therefore be more interesting than either figure in isolation. A divergence can prompt questions about how traders are interpreting the polling, whether new information has yet to appear in surveys and why different markets may be assigning different probabilities to the same outcome.
iPredicta's analysis, 'Are Prediction Markets More Accurate Than Polls?', explores the broader question of how the two approaches compare.
For the latest prices across individual Senate, House and Governor races, see iPredicta's US Midterms prediction markets page, or read our broader 2026 midterm election prediction markets analysis for an overview of the markets for control of Congress.
