Connecticut Governor 2026Safe
Ned Lamont (D) vs. Ryan Fazio (R)
Precision Combined forecast
98%
Ned Lamont (D) to be Connecticut's next governor
- Ned Lamont (D)
- 97.6% · −4067
- Ryan Fazio (R)
- 2.4% · +4067
- Sources used
- 3 of 5
- Market money behind it
- $17k
As of Oct 13, 7:37 AM ET · refreshes about every 30 minutes
Polymarket
not used- Ned Lamont96.7% ▲0.5
- Ryan Fazio3.2%
Excluded: $9k traded, under the $10k floor
PredictIt
29% weight- Democratic97¢
- Republican3¢
PredictIt publishes no volume, 2¢ spread
Public polls
41% weightD +17.0
Ned Lamont 55% · Ryan Fazio 38%
1 pollster · latest ended Sep 21, 2026
1 pollster, latest ended Sep 21
Precision member poll
not usedNot fielded yet. Joins this number when the Precision member panel launches.
RealClearPolitics
for comparisonRCP doesn’t license its polling averages, so we link to them instead of copying the number.
Compare on RealClearPolling ↗How the Precision Funnel™ weighed this race
Market money behind the number: $17k
- 41%Public polls1 pollster, latest ended Sep 21
- 30%Kalshi$17k traded, 1¢ spread
- 29%PredictItPredictIt publishes no volume, 2¢ spread
- —PolymarketExcluded: $9k traded, under the $10k floor
- —Precision member pollNot fielded yet. Joins this number when the Precision member panel launches.
- —Attention: news volume, news tone, Wikipedia pageviewsClosed: only Wikipedia has enough volume; the gate needs two independent sources. 0% unless the gate opens; 5% to 15% when it does. Signals ↓
Weight = trust × evidence for this race, scaled to 100% across the sources used. The rule ↓
Attention and momentum
Gate closedNo clear movement in news coverage or public interest between Ned Lamont and Ryan Fazio. It is shown here and not blended into the number. Gate closed: only Wikipedia has enough volume; the gate needs two independent sources.
News volume36% of bucket
—
Not enough days of data yet
News tone29% of bucket
—
Not enough days of coverage to score tone
Wikipedia pageviews36% of bucket
+0.02
1.8k views/day last week; Lamont's share 32% → 32%
No news articles a day stored yet.
Last 28 days; shaded = last 7. Source: GDELT.
No average news tone stored yet.
Last 28 days; shaded = last 7. Source: GDELT.
Last 28 days; shaded = last 7. Source: Wikipedia.
● Ned LamontGDELT seriesWikipedia article● Ryan FazioGDELT seriesWikipedia article
Not measured yet: search interest (15%) and social volume and sentiment (15%). Their share is spread over the measured signals until they are wired. News tone is the tone of coverage, not of voters. The gate rule →
Recent public polls
Lamont 55 · Fazio 38
Sep 17 – Sep 21, 2026 · 540 LV
Lamont 52 · Fazio 37
Aug 20 – Aug 24, 2026 · 809 LV
Lamont 49.7 · Fazio 29.5
Jul 21 – Jul 26, 2026 · 1000 RV
Lamont 49 · Fazio 36
Jun 18 – Jun 23, 2026 · 828 LV
How the Precision Funnel™ builds the Precision Combined number
Everything available on a race goes into the top of the funnel. No source has a fixed percentage: each one’s weight comes from how much evidence it carries for this race, by the published rule on the right.
- Public polls. Every public poll of the race, national, state or local, is vetted before it counts: how many people it reached, how recent it is, whether it screened for likely voters, and whether a party or campaign paid for it. Campaign internal polls are left out.
- Prediction markets, priced by money at risk. For each market we add up the dollars traded (contracts times price). A market with under $10k traded, a spread wider than 10¢, or a 15-point jump on under $25k is left out, because one buyer can set that price.
- Local and regional sources. Newspaper, radio and university polls get the same vetting as step 1. Today they arrive through the public poll feed; we are adding the local sources national feeds miss. In races national pollsters skip, such as state cabinet offices, they may be most of what exists.
- Attention and momentum. News volume and tone (GDELT) and Wikipedia pageviews for the two leading candidates, this week against the three weeks before. Attention is not votes, so it counts only through a gate: two independent sources with enough volume, all moving the same way. Then it carries 5% to 15% of the number; otherwise 0%, shown beside the number. Search interest and social platforms join as they are wired.
- our own member poll. Our panel, weighted to the voter file on party, age, sex, education, income and region. It starts with the same trust as outside polls and earns more only through a scored track record.Not live yet
- The number. Market prices are scaled to add to 100%, a poll lead becomes a win chance with a bell curve 6 points wide, and the sources are averaged with their weights. Every race page prints the weights it got and why.
Full methodology →Why blend? Read the research →How we’ll be scored →
The weighting rule
Weight = trust × evidence, then scaled so the sources used add to 100%.
| Source | Trust | Evidence |
|---|---|---|
| Kalshi, Polymarket | 1 | Dollars traded ÷ (dollars traded + $50k). $50k counts half, $1M about 95%. |
| PredictIt | ½ | Fixed at ½, since PredictIt publishes no volume and caps each contract at $850. |
| Public polls | 1 | Grows with each vetted poll: full credit at 600 respondents, half credit every 21 days of age, less for registered voters or all adults, half for a partisan sponsor. |
| Precision member poll | 1 | Effective sample ÷ 800 (max 1) × share of demographic groups that match the voter file. Left out under 200 respondents. |
So a Senate race with deep markets and many polls lands near an even split, while a race no market lists and only one local paper polled leans almost entirely on the polls that exist. The constants above are the same for every race; changing one is a new method version, dated and logged. Trust values will be refit on our own scored history and the change published. RealClearPolitics is linked for comparison but not used: RCP has no public data feed and its terms don’t allow republishing its averages. Market prices reflect traders’ money, not a poll of voters. PredictIt data is shown under its non-commercial license. The Funnel never uses a number we did not measure or a source we cannot name.