# Data Scientist Predicts Low Odds for Republican Senate Control Northwestern professor Thomas Miller uses prediction markets to forecast shifting Senate election probabilities. - **Source:** [Fortune | FORTUNE](https://brifing.si/source/769282ef-327a-4454-909a-3c7936216004) - **Published:** 2026-10-31 - **Topic:** [Data & AI](https://brifing.si/c/data-ai) - **Original article:** - **On Brifing:** https://brifing.si/s/b75ea3f1-18df-450a-8bb3-0fe0f5e89537 ## Predictive Model Methodology Northwestern University professor Thomas Miller utilizes a non-AI model to forecast Senate outcomes. By aggregating data from prediction markets like Polymarket and Kalshi, Miller calibrates prices into real-time probabilities. He applies time series analysis and economic models to identify underlying factors, claiming this approach outperforms traditional polling methods for election forecasting. ## The NowCast Mechanism Miller’s Virtualtout.io platform features a 'NowCast' tool that updates candidate win probabilities every ten minutes. This ticker-style interface tracks changes over the last 24 hours, providing a dynamic view of political momentum. Miller argues that prediction markets capture voter sentiment more accurately than standard surveys by reflecting actual financial stakes. ## Trump as Market Driver The model identifies Donald Trump’s actions and rhetoric as the primary force influencing betting prices across all states. Miller observes that states do not move independently; when Republican odds fall, they often decline across the board. He estimates that Trump’s influence accounts for 85% to 90% of the observed variance in market prices. ## Declining GOP Senate Prospects Data from October 30 indicates Republicans have a 17.1% chance of retaining control of the Senate, a significant drop from 34.8% on September 17. The model suggests that if current trends hold, Democrats could secure a 52-48 majority, effectively reversing the previous Republican dominance in the upper chamber of the legislature. ## Regional Performance Shifts In key contests like Texas and Ohio, Republican odds have fallen since mid-September. Texas dropped from 46.15% to 31.9%, while Ohio declined from 45.4% to 31.8%. Conversely, Maine shows a slight recovery for Republicans, with Susan Collins rising to 39.9% probability, demonstrating that individual candidate dynamics can occasionally defy broader national trends. ## Trouble in Traditional Strongholds The model highlights unexpected vulnerability in Republican strongholds like Iowa and Kansas. Ashley Hinton in Iowa fell to a virtual tie at 53.4%, while Adam Hamilton in Kansas dropped nearly 19 points to 57.1%. These shifts suggest that the GOP is struggling to defend seats previously considered safe, complicating their path to victory. ## Competitive Landscape Analysis Democrats currently hold better than 60% odds in all five seats they are attempting to flip. Michigan remains a point of concern for Republicans, with their chances of defeating Abdul El-Sayed slipping to 25.4%. Meanwhile, South Carolina remains a focal point, with Darline Graham maintaining a 75% win probability despite recent minor fluctuations. ## Statistical Interpretation Limits Miller emphasizes that his model provides probabilities rather than definitive predictions. While Republicans face steep challenges, candidates with over 30% odds still maintain a statistical path to victory. The GOP must now overcome these odds in multiple states simultaneously, while also defending seats that were not previously expected to be highly contested. ## Sources covering this story - https://fortune.com/2026/10/31/top-data-scientist-tom-miller-midterm-election-model-republicans-one-chance-in-six-senate-control/ — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._