Political forecasting in Arizona has long been treated as a losing proposition — a state where phone surveys routinely miss the mark and mail-in ballots scramble any early read on the electorate. A new data point is complicating that reputation.
As reported by the Arizona Herald, Andy Biggs captured Arizona’s Republican gubernatorial primary with 73.3% of the vote — a result that G Ratings, a Miami-based political research firm, had projected at 73.7% weeks before ballots were counted. The gap between forecast and outcome came in at just four-tenths of a percentage point, a margin that would be notable in any state and is especially so in one where polling has historically struggled.
A Track Record Across the Full Ballot
The accuracy wasn’t confined to the top of the ticket. Runner-up David Schweikert finished with 14.7% of the vote against a G Ratings projection of 14.3%, again landing within 0.4 percentage points. Further down the ballot, Scott Neely and Ken Miceli posted official totals of 7.1% and 4.7%, compared to projections of 3.5% and 2.6% — wider misses than the top two races, but still directionally consistent. Averaged across all four contested candidates, the model’s margin of error came out to 1.45%, with a net directional bias of only -0.2%, suggesting the projections weren’t systematically inflating or deflating any single candidate’s support.
The tool behind those numbers is Odysseus, a proprietary AI platform G Ratings has been testing ahead of the broader 2026 midterm cycle. The firm chose Arizona as a proving ground precisely because of its reputation as one of the harder states to poll accurately — a mix of rural conservative voters wary of pollsters, border communities with distinct turnout patterns, and a mail-in ballot system capable of shifting outcomes by several points in the final stretch before Election Day.
Why Arizona Breaks Traditional Polling Models
The state’s electorate doesn’t behave uniformly, and that’s the core challenge for any single statewide survey. Turnout patterns in rural counties can diverge sharply from what’s happening in Maricopa County’s suburban precincts, and because so much of the vote arrives early or by mail, a poll conducted weeks before the election can capture a very different electorate than the one that ultimately casts ballots.
Rather than treating that volatility as statistical noise to be smoothed over, Odysseus is designed to track it in real time. The platform pulls in sentiment data from local media coverage and digital discourse, cross-references it against historical turnout records and daily ballot-return figures by county, and applies economic and demographic clustering to distinguish a candidate’s firm base of support from voters who remain persuadable or undecided.
That distinction appears to have mattered most in the down-ballot contests, where the gap between projection and result was largest. G Ratings’ data identified inflation, job growth, and tax policy as the dominant concerns driving voters statewide, with healthcare, border security, and trust in election administration following close behind — but the firm notes that mix looks different depending on geography, with priorities in a city like Yuma diverging from those in Scottsdale. Rather than collapsing those differences into a single statewide average, the model was built to hold both realities simultaneously.
A G Ratings spokesperson framed the approach as a deliberate departure from conventional survey methodology: the goal wasn’t to capture what voters told a pollster on the phone weeks earlier, but to model which voters would actually show up on Election Day — a distinction the firm argues is the only one that ultimately determines a result.
Setting Up the General Election
With Biggs now the Republican nominee and Governor Katie Hobbs advancing unopposed on the Democratic side, Arizona moves into what’s expected to be one of the more closely watched general election races of the 2026 midterm cycle. The primary result leaves a specific marker in place: in a state where rural turnout, border-region dynamics, and heavy mail-in volume have historically made accurate forecasting difficult, a model combining real-time data streams with AI-driven analysis was able to track the outcome with unusual precision.
Whether that level of accuracy carries over to a general election — with a far larger and more diverse electorate, additional variables, and a longer campaign runway — remains an open question. For now, the primary has given G Ratings a concrete benchmark, and set expectations for what data-driven forecasting in a historically unpredictable state might be capable of heading into November.
