Orlando City SC vs Nashville SC Sun, Jul 26, 2026 07:30 AM AI Verdict Away Win — 59% probability ★★★★★ S. Surridge (Nashville SC) — Minor Missing Fixture N. Miller (Orlando City SC) — Minor Missing Fixture J. Gerbet (Orlando City SC) — Minor Missing Fixture Confidence: Decisive · Updated: Sun, Jul 26, 2026 07:30 AM AI Prediction Predicted outcome: Away Win (22% probability) Home Win: 22% Draw: 19% Away Win: 59% Most likely scores: 1-1 (12%), 1-0 (11%), 0-1 (11%) Model Confidence Confidence Rating: Decisive (100%) Clear separation between top 2 outcomes Prediction Evolution (10 snapshots) 17:10 — Home 0% / Draw 0% / Away 1% 17:10 — Home 0% / Draw 0% / Away 1% 17:10 — Home 0% / Draw 0% / Away 0% (Δ Home +0.1%, Away -0.2%) 17:10 — Home 0% / Draw 0% / Away 0% 17:26 — Home 43% / Draw 25% / Away 32% (Δ Home +42.5%, Draw +24.4%, Away +32.2%) 17:26 — Home 43% / Draw 25% / Away 32% 17:26 — Home 43% / Draw 25% / Away 32% 17:26 — Home 43% / Draw 25% / Away 32% 17:26 — Home 43% / Draw 25% / Away 32% 17:44 — Home 43% / Draw 25% / Away 32% Advanced Details Match Signals 🩹 S. Surridge (Nashville SC) — Minor Missing Fixture ✅ confirmed [Impact: Home -1%, Away -1%] 🩹 N. Miller (Orlando City SC) — Minor Missing Fixture ✅ confirmed 🩹 J. Gerbet (Orlando City SC) — Minor Missing Fixture ✅ confirmed [Impact: Home -1%, Away -1%] 🩹 P. Yazbek (Nashville SC) — Minor Missing Fixture ✅ confirmed [Impact: Home -1%, Away -1%] 🩹 E. Tagseth (Nashville SC) — Minor Missing Fixture ✅ confirmed [Impact: Home -1%, Away -1%] 🩹 A. Najar (Nashville SC) — Minor Missing Fixture ✅ confirmed [Impact: Home -1%, Away -1%] Frequently Asked Questions Why is Away Win the clear favorite? The AI model assigns 59% probability to Away Win, indicating strong confidence based on historical data, ELO ratings, and recent form analysis. What is the biggest factor affecting this prediction? S. Surridge (Nashville SC) — Minor Missing Fixture How confident is the model in this ranking (Decisive, 100%)? Model Confidence measures how certain the AI is about the order of outcomes, not any single probability. A clear gap between the top two outcomes gives the model high conviction in its ranking. How does the AI prediction model work? Our ensemble combines Gradient Boosting and Random Forest models trained on historical match data, ELO team ratings, recent form, and statistical metrics. Score distributions use Poisson-based simulations for the most likely scorelines.