MLS · Predictions

2026-10-02 · 6 fixtures

Live matches first, then by kick-off time.

Standings and table positions. Combined with our match predictions and analysis above for full context.

Frequently Asked Questions

Our power ratings measure each team's attacking and defensive strength on a 1-10 scale. Attack power is derived from expected goals (xG) creation, while defense power reflects xG conceded. A rating of 10 means elite, 5 is average, and 1 is weak. These ratings feed into the Poisson model that generates match predictions.

The attack number (ATT) shows how dangerous a team is at scoring — higher means more goals expected. The defense number (DEF) shows how well a team prevents goals — higher means fewer goals conceded. Together they determine the expected goals (xG) for each team in every match, which drives all scoreline probabilities.

Predictions use a Poisson distribution model. For each match, we calculate expected goals for both teams from their attack/defense power ratings. The model then computes the probability of every possible scoreline (0-0 through 5-5) and ranks them by likelihood. The same method applies to over/under, BTTS, and correct score markets.

Expected goals (xG) is a statistical measure that quantifies the likelihood of a shot becoming a goal. A team's cumulative xG across a match estimates how many goals they should score based on chance quality. In MLS, xG data comes from the SSTrader API and reflects pre-match projections from team form and historical performance.

Yes, all MLS predictions on ProSoccer are free. You can see match-by-match predictions including 1X2 probabilities, over/under lines, correct scores, and bet builder suggestions without paying or registering. Bookmaker odds are shown only after you tap to expand, keeping the content search-engine compliant.

Over/Under 2.5 goals is typically the most accurate market for statistical models, with 55-65% accuracy. Correct score predictions are lower-probability by nature but can identify value. 1X2 (match winner) accuracy varies by league competitiveness. Our model performs best on goal-line markets because goal distribution follows a Poisson pattern.

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