Orlando City SC — Nashville SC: Win probabilities, 25.07.2026
Win probabilities
Outcome probabilities after removing the bookmaker margin
Markets
All calculated markets
| Market | Selection | Probability |
|---|---|---|
| Double chance | 1X | 57.7% |
| 12 | 76.4% | |
| X2 | 65.8% | |
| Both teams to score | Yes/No | 65.8% / 34.2% |
| Totals 0.5 | Over/Under | 96.0% / 4.0% |
| Totals 1.5 | Over/Under | 84.8% / 15.2% |
| Totals 2.5 | Over/Under | 64.5% / 35.5% |
| Totals 3.5 | Over/Under | 42.4% / 57.6% |
| Totals 4.5 | Over/Under | 24.1% / 75.9% |
| Totals 5.5 | Over/Under | 12.0% / 88.0% |
Score probability heatmap
Home goals run vertically; away goals run horizontally
Match preview
Orlando City SC and Nashville SC look evenly matched ahead of their MLS meeting. The available assessment gives neither side a clear overall advantage, with a moderate level of confidence in that reading. This points to a contest likely to be decided by small details rather than by a pronounced difference in quality.
The match is expected to offer an open attacking rhythm, with both Orlando City SC and Nashville SC likely to find the net. The most plausible scorelines include 1-1, 1-2 and 2-1, underlining the balance between a draw and a narrow victory for either team. With the scoring outlook rated as high, defensive control may be difficult to maintain throughout, so the game could remain competitive and change direction as it develops.
Other matches
Prediction questions
We remove the bookmaker margin from market odds, estimate each team’s expected goals and build one matrix of possible scores. Outcomes, totals, both teams to score and likely scores all come from that matrix.
Fair odds are one divided by the probability of the main signal. They are a mathematical reference without bookmaker margin, not an offer from a particular bookmaker.
The official prediction is locked before kick-off and is never rewritten after publication. After the final whistle it is checked against the result and added to the public record.
AI does not calculate or change probabilities. It explains the mathematical output in plain language, and the model used is shown next to the analysis.