Major League Soccer: FC Cincinnati (#9) host DC United (#13). Recent form — FC Cincinnati: 1W 1D 3L; DC United: 1W 1D 3L. FC Cincinnati is the model’s favourite.
PickLab model: FC Cincinnati win 49%, draw 24%, DC United win 27%. Expected goals: FC Cincinnati 2.32 – 1.56 DC United (total 3.9). Most likely score: 1–1 (9%). Both teams to score: 71%. Over 2.5 goals: 72%.
Generated automatically from the PickLab statistical model and recent results. Not betting advice.
Match outcome
1X2 · Poisson + Dixon–Coles
49%FC Cincinnati winHighest estimate
=24%Draw
27%DC United win
Estimated probabilities, not betting odds. Rounded to total 100%.
Goals & scorelines
Expected goals and market probabilities
FC Cincinnati2.32xG1.56DC United
Most likely scores1–19.4%2–17.6%2–27.3%
89%Over 1.5
72%Over 2.5
53%Over 3.5
71%Both score
Test your own markets
Tick Over 2.5, Both teams to score, a correct score or any combination and see the probability from the v2 model.
The model projects 3.87 combined goals. Its estimated probability of at least two goals is 89%. It is featured because it ranks among the three highest estimated probabilities in the eligible eight-pick shortlist; this is not a measure of betting value.
★ #288%
FC Cincinnati to score
The model projects 2.32 goals for FC Cincinnati and calculates a 88% chance they score at least once. It is featured because it ranks among the three highest estimated probabilities in the eligible eight-pick shortlist; this is not a measure of betting value.
★ #380%
DC United to score
The model projects 1.56 goals for DC United and calculates a 80% chance they score at least once. It is featured because it ranks among the three highest estimated probabilities in the eligible eight-pick shortlist; this is not a measure of betting value.
More selections
4
FC Cincinnati or Draw
73%
5
Over 2.5 goals
72%
6
Both teams to score
71%
7
FC Cincinnati 2+ goals
64%
8
DC United or Draw
51%
Featured picks may overlap (for example a team scoring and over 1.5 goals). A high probability does not mean good betting value.
League baseline. Expected goals start from this competition’s real scoring averages at home (1.84) and away (1.41) per match.
Attack and defence ratings. Each team is rated against that baseline from the season table and its last 20 matches, with older matches fading (half-life ~90 days).
Opponent adjustment. Goals against weak defences count less, goals against strong ones count more.
Regression to the mean. Small samples are pulled toward the league average so one big result does not distort the estimate.
Poisson + Dixon–Coles. Expected goals generate a probability for every scoreline; a low-score correction fixes the known underestimation of draws and 1-0 / 0-1 / 1-1.
Markets. 1X2, totals and both-teams-to-score are read from that scoreline grid.
1.22 / 1.34FC Cincinnati attack / defence
0.85 / 1.11DC United attack / defence
Ratings are relative to the league average (1.00). Attack above 1 scores more than average; defence above 1 concedes more.
A statistical model, not a trained AI. It does not know about injuries, lineups, motivation or odds. Use it as one more data point.