2026 forecast · Wisconsin Governor
David Crowley is slightly favored to win Wisconsin's governorship.
David Crowley vs Tom Tiffany, an open seat. The model has Crowley ahead by 2.8 points, winning 68 percent of 2,000 simulated elections.
Lean DModel D +2.8Polls D +3.5Updated October 22, 2026
David Crowley
Democrat
50.8%
1,526,134 projected votes
Tom Tiffany
Republican
48.0%
1,442,893 projected votes
68%Crowley
32%Tiffany
Crowley favoredEach square is one simulated election night, Crowley wins about 68 of 100
RatingLean D68% chance for Crowley
Model marginD +2.8Polls D +3.5
80 percent rangeD +11.2 to R +5.42,000 simulations
Projected votes3,006,001Crowley 50.8%
The county map
Four ways to read the state: margin, shift from 2024, vote bubbles and turnout
D +40R +40Click a county to zoom · arrow keys step through counties by size
Where the margin is won
Crowley +424,684 net votes from 13 countiesStatewide D +2.8, a 83,359 vote marginTiffany +341,325 net votes from 59 counties
Vote share
Each candidate's projected share and the range of 80 percent of simulations
David CrowleyDemocrat · 68% to win
3040506070
50.8%
Tom TiffanyRepublican · 32% to win
3040506070
48.0%
Scale runs from 25 to 75 percent. The dot is the forecast, the band is the 80 percent range and the brighter tick marks 50 percent.
Projected statewide vote
3,006,001 votes| Candidate | Votes | Share |
|---|---|---|
| David Crowley D | 1,526,134 | 50.8% |
| Tom Tiffany R | 1,442,893 | 48.0% |
| Other / write-in O | 36,974 | 1.2% |
| Total | 3,006,001 | 100% |
Each candidate's expected vote in the On Point simulation, at the forecast's projected turnout.
Every simulated outcome
2,000 sims80 percent of simulations fall between D +11.2 and R +5.4. Negative margins are Democratic wins.
The trend
Each side's chance of winning over the forecast's recent updates
Polling
Every poll in the average, and how the model reads it
The line is the On Point average: a robust LOWESS fit through the polls, weighted by recency, sample, voter screen and pollster grade, refit three times so outliers count for lessDot size is each poll's weight todayHover or use the arrow keys to read any day
What moves the average today
Platform Communications (R)Aug 13 · 500 LV · NR18%Crowley +4.0
Marquette UniversityAug 20 · 738 LV · NR17%Crowley +5.0
Z to A Research for Rust Belt Rising (D)Oct 1 · 662 RV · NR17%Crowley +5.0
TIPP Insights (R)Aug 18 · 1,199 LV · A17%Crowley +4.0
Marquette UniversitySep 23 · 750 LV · NR15%Crowley +3.0
YouGov for City Forward CollectiveOct 9 · 1,715 A · C15%Crowley +4.0
Every other poll together: 0.6%
This is the same On Point polling average as the full average page. The forecast reads the polls through its own Election Day projection, shown as the On Point average in the table below, and blends it with partisan lean and fundamentals.
Polls of the race
Full average| Pollster | Sample | Age | Margin |
|---|---|---|---|
| On Point average | Weighted average | D +3.5 | |
| YouGov for City Forward Collective | 1,715 RV | 6d | D +3.0 |
| Z to A Research (D) | 662 LV | 14d | D +3.7 |
| Marquette University | 750 LV | 22d | D +2.9 |
| Marquette University | 738 LV | 56d | D +4.9 |
| TIPP Insights (R) | 1,199 LV | 58d | D +3.7 |
| Platform Communications (R) | 500 LV | 63d | D +5.6 |
| GBAO (D) | 800 LV | 73d | D +0.7 |
Model margin
Crowley +2.8
Chance of winning
David Crowley68%
Tom Tiffany32%
Simulated vote
David Crowley50.8%
Tom Tiffany48.0%
Other / write-in1.2%
How the model gets there
Partisan leanR +0.9
FundamentalsR +3.3
With pollsD +2.5
Early vote turnoutD +0.2
With early voteD +2.8
Read from 246,840 ballots cast so far in Wisconsin, against the party mix the forecast expected of them, with similar states and primary turnout. Early vote tracker
Who has endorsed
69 public endorsements in this race, each with where it was reported.
David Crowley47
- Tony EversGovernor of Wisconsinsource
- Barack Obamasource
- Francesca HongState Rep., former primary rivalsource
- Gwen MooreU.S. Representative WI-4source
- Cavalier JohnsonMayor of Milwaukeesource
- Paul SoglinFormer Mayor of Madisonsource
- Gregory MeeksU.S. representative, NY-05source
- Missy HughesFormer CEO of the Wisconsin Economic Development Corporationsource
Tom Tiffany22
- Donald Trumpsource
- JD VanceVice Presidentsource
- Tommy ThompsonFormer Governor, former HHS Secretarysource
- Bryan SteilU.S. Representative WI-1source
- Scott FitzgeraldU.S. Representative WI-5source
- Glenn GrothmanU.S. Representative WI-6source
- Derrick Van OrdenU.S. Representative WI-3source
- Tony WiedU.S. Representative WI-8source
On the air
Hasan Piker: Endorsed Democratic socialist Francesca Hong in the Democratic primary and appeared at her Milwaukee rally. source
How we got here
From the state's partisan lean to the forecast, one stage at a time
Who votes for whom
Estimated vote by group from the model's simulated electorate
Estimated vote by group
model crosstabs| Group | Share | Crowley | Tiffany |
|---|---|---|---|
| GenderMen | 46% | 45.7 | 53.1 |
| Women | 54% | 54.6 | 44.2 |
| Age18 to 29 | 12% | 56.3 | 42.5 |
| 30 to 44 | 20% | 50.9 | 47.8 |
| 45 to 64 | 35% | 47.2 | 51.5 |
| 65+ | 33% | 51.6 | 47.2 |
| RaceWhite | 86% | 46.0 | 52.7 |
| Black | 5% | 90.7 | 8.1 |
| Latino | 4% | 69.5 | 29.3 |
| Asian and other | 5% | 74.7 | 23.8 |
| Race and genderWhite men | 39% | 40.2 | 58.6 |
| White women | 47% | 50.9 | 47.9 |
| Black men | 2% | 89.6 | 9.2 |
| Black women | 3% | 91.7 | 7.2 |
| Latino men | 2% | 67.1 | 31.7 |
| Latino women | 2% | 71.7 | 27.0 |
| All other races | 5% | 74.7 | 23.8 |
Every county
The projected vote in each county, largest first
Projected vote by county
72 counties| County | Crowley | Tiffany | Other | Total | Margin |
|---|---|---|---|---|---|
| Statewide | 1,526,081 | 1,442,722 | 37,198 | 3,006,001 | D +2.8 |
| Milwaukee County | 305,938 | 106,459 | 5,009 | 417,406 | D +48.3 |
| Dane County | 257,655 | 67,837 | 3,288 | 328,780 | D +58.3 |
| Waukesha County | 95,276 | 144,151 | 1,931 | 241,358 | R +19.9 |
| Brown County | 58,135 | 70,745 | 1,697 | 130,577 | R +9.2 |
| Outagamie County | 43,270 | 52,665 | 1,263 | 97,198 | R +9.3 |
| Racine County | 45,253 | 47,694 | 1,224 | 94,171 | R +2.3 |
| Winnebago County | 39,480 | 44,001 | 1,271 | 84,752 | R +5.0 |
| Washington County | 24,558 | 54,099 | 715 | 79,372 | R +37.0 |
| Kenosha County | 37,463 | 39,243 | 1,247 | 77,953 | R +1.9 |
| Rock County | 42,018 | 33,137 | 1,145 | 76,300 | D +11.9 |
| Marathon County | 27,516 | 40,907 | 831 | 69,254 | R +19.0 |
| La Crosse County | 35,824 | 26,255 | 945 | 63,024 | D +15.6 |
| Sheboygan County | 24,147 | 34,931 | 717 | 59,795 | R +17.6 |
| Ozaukee County | 25,064 | 30,300 | 503 | 55,867 | R +9.0 |
| Eau Claire County | 30,115 | 24,501 | 719 | 55,335 | D +10.5 |
| Walworth County | 20,629 | 31,436 | 739 | 52,804 | R +20.2 |
| Fond du Lac County | 18,196 | 32,959 | 569 | 51,724 | R +28.2 |
| St. Croix County | 20,225 | 29,227 | 804 | 50,256 | R +17.3 |
| Dodge County | 15,378 | 28,156 | 529 | 44,063 | R +28.7 |
| Jefferson County | 18,113 | 25,095 | 525 | 43,733 | R +15.7 |
| Manitowoc County | 15,210 | 24,882 | 569 | 40,661 | R +23.4 |
| Portage County | 18,620 | 18,786 | 531 | 37,937 | Even |
| Wood County | 14,966 | 21,406 | 517 | 36,889 | R +17.2 |
| Chippewa County | 13,180 | 19,573 | 465 | 33,218 | R +18.9 |
| Sauk County | 17,082 | 15,211 | 458 | 32,751 | D +6.1 |
| Columbia County | 15,103 | 15,111 | 398 | 30,612 | D +0.4 |
| Calumet County | 11,206 | 16,592 | 309 | 28,107 | R +18.8 |
| Waupaca County | 8,979 | 16,954 | 341 | 26,274 | R +30.1 |
| Polk County | 8,514 | 14,784 | 355 | 23,653 | R +26.3 |
| Grant County | 10,508 | 12,769 | 354 | 23,631 | R +9.2 |
| Barron County | 8,116 | 14,755 | 349 | 23,220 | R +28.4 |
| Oneida County | 9,013 | 12,782 | 332 | 22,127 | R +16.8 |
| Dunn County | 9,383 | 12,206 | 329 | 21,918 | R +12.5 |
| Douglas County | 12,120 | 9,474 | 284 | 21,878 | D +12.4 |
| Oconto County | 6,971 | 14,165 | 257 | 21,393 | R +33.3 |
| Pierce County | 9,094 | 11,829 | 384 | 21,307 | R +12.6 |
| Marinette County | 6,258 | 14,652 | 276 | 21,186 | R +39.2 |
| Shawano County | 6,045 | 14,068 | 244 | 20,357 | R +39.2 |
| Monroe County | 7,958 | 11,842 | 301 | 20,101 | R +19.0 |
| Green County | 10,298 | 8,890 | 273 | 19,461 | D +7.6 |
| Door County | 9,474 | 9,083 | 225 | 18,782 | D +2.4 |
| Lincoln County | 5,791 | 9,002 | 256 | 15,049 | R +21.1 |
| Vernon County | 7,105 | 7,396 | 205 | 14,706 | R +1.7 |
| Vilas County | 5,209 | 9,004 | 173 | 14,386 | R +26.2 |
| Trempealeau County | 5,913 | 7,701 | 179 | 13,793 | R +12.6 |
| Clark County | 4,044 | 9,183 | 201 | 13,428 | R +38.0 |
| Iowa County | 7,399 | 5,295 | 154 | 12,848 | D +16.8 |
| Waushara County | 4,392 | 8,123 | 139 | 12,654 | R +29.2 |
| Juneau County | 4,624 | 7,686 | 187 | 12,497 | R +24.3 |
| Adams County | 4,470 | 6,631 | 192 | 11,293 | R +19.1 |
| Kewaunee County | 3,728 | 7,030 | 131 | 10,889 | R +30.0 |
| Langlade County | 3,096 | 6,798 | 243 | 10,137 | R +36.2 |
| Bayfield County | 5,646 | 4,334 | 111 | 10,091 | D +13.4 |
| Sawyer County | 4,000 | 5,652 | 117 | 9,769 | R +16.6 |
| Taylor County | 2,388 | 7,237 | 137 | 9,762 | R +49.4 |
| Green Lake County | 3,046 | 6,564 | 117 | 9,727 | R +35.9 |
| Washburn County | 3,373 | 5,936 | 132 | 9,441 | R +26.8 |
| Burnett County | 3,230 | 5,931 | 140 | 9,301 | R +28.8 |
| Jackson County | 3,968 | 5,179 | 139 | 9,286 | R +12.7 |
| Marquette County | 3,007 | 5,077 | 106 | 8,190 | R +25.0 |
| Richland County | 3,878 | 4,114 | 114 | 8,106 | R +2.6 |
| Crawford County | 3,677 | 4,155 | 103 | 7,935 | R +5.7 |
| Ashland County | 4,229 | 3,558 | 102 | 7,889 | D +8.7 |
| Price County | 2,732 | 4,928 | 93 | 7,753 | R +28.0 |
| Lafayette County | 3,398 | 4,099 | 83 | 7,580 | R +8.9 |
| Rusk County | 2,353 | 4,715 | 100 | 7,168 | R +32.7 |
| Buffalo County | 2,786 | 4,023 | 110 | 6,919 | R +17.8 |
| Forest County | 1,573 | 2,961 | 69 | 4,603 | R +29.9 |
| Pepin County | 1,345 | 2,353 | 49 | 3,747 | R +26.8 |
| Iron County | 1,398 | 2,155 | 40 | 3,593 | R +20.8 |
| Florence County | 727 | 2,005 | 28 | 2,760 | R +45.8 |
| Menominee County | 1,205 | 285 | 26 | 1,516 | D +59.6 |
Projected 2026 votes from the On Point simulation: each county's expected turnout times its simulated vote share. Totals may differ from the race total by rounding.
Methodology
Every county is rebuilt by simulating voters going to the polls, 2,000 times, from On Point Polling survey data, past results, and the polling average. How the model works.