Austin
vs
San Diego
Major League Soccer prediction
Our model says: Austin 1–0 San Diego
The model makes it 45% Austin, 29% draw, 26% San Diego — fair odds of 2.22, 3.45 and 3.85. Fair odds are simply 100 ÷ the probability; they are the model's own number, not a bookmaker's price.
Most likely scoreline: 1-0.
Expected goals: Austin 1.70, San Diego 1.00.
Both teams to score: 52%. Over 2.5 goals: 51%, under 2.5: 49%.
Model confidence: Medium.
Published · updated
Live win probability
From kick-offThese update every few seconds once the match kicks off, as the model re-reads the score, the clock and any red cards. The second figure is fair odds — 100 ÷ probability, the price with no margin in it.
Model insights: Austin vs San Diego
Every scoreline the model considered
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 7 | 6 | 3 | 1 | ||
| 1 | 11 | 12 | 6 | 2 | ||
| 2 | 10 | 10 | 5 | 2 | ||
| 3 | 6 | 6 | 3 | |||
| 4 | 2 | 2 | 1 | |||
| 5 |
Each cell is one exact result, shaded against the likeliest one; figures below 1% are left blank rather than rounded to zero. Blue cells are Austin wins, grey are draws, red are San Diego wins — the three shaded areas ARE the 1/X/2 split above, which is the sum of the cells in each. The most likely scoreline is simply the darkest cell inside whichever area the model favours.
Has the model earned this number?
It puts Austin at 45% here. Across 2437 settled matches, 1092 forecasts have landed in the 40–50% band; those outcomes actually happened 44.3% of the time, against an average forecast of 43.8%. In this range the two line up, so the figure above can be read literally.
Every settled prediction on this site is scored against an uninformed baseline, band by band, and published whether or not it flatters the model — see the full record.
Form going into Austin vs San Diego
Austin
- W2-1away to Vancouver Whitecaps13 September 2026
- D1-1Colorado Rapids10 September 2026
- D1-1San Jose Earthquakes6 September 2026
- W2-1away to Portland Timbers30 August 2026
- D1-1Philadelphia Union23 August 2026
San Diego
- L0-5Philadelphia Union14 September 2026
- L2-3San Jose Earthquakes10 September 2026
- L0-1away to Orlando City SC5 September 2026
- W3-1Los Angeles Galaxy30 August 2026
- W3-0Colorado Rapids23 August 2026
Up to 5 matches before kick-off, most recent first. The model works from each side's rolling expected-goals ratings rather than from these results directly, so read them as context — how the ratings are built.
Major League Soccer table
| # | Team | P | W | D | L | GF | GA | GD | Pts |
|---|---|---|---|---|---|---|---|---|---|
| 13 | Austin | 25 | 7 | 8 | 10 | 32 | 44 | -12 | 29 |
| 9 | San Diego | 25 | 8 | 6 | 11 | 42 | 42 | 0 | 30 |
Where the two sides stand. Full table
Leading scorers: Austin and San Diego
Austin
No player in Major League Soccer's leading scorers — 32 league goals as a side.
San Diego
- M. Ingvartsen11 goals3 assists
Top 3 by league goals this season. Player availability is not part of the model — injuries and suspensions are a planned improvement.
Two sides the ratings cannot separate
Austin carry a model rating of 6.55 against 6.44 for San Diego. The scale is anchored so that an average side in one of Europe's big five leagues sits at 6.85, and it is adjusted for the strength of each team's league, so the two numbers are comparable even across borders.
A gap that small is inside the noise of the rating itself — treat the two as level.
What the model expects
Under the hood the model expects 1.70 goals for Austin and 1.00 for San Diego. Those two numbers, not the scoreline, are what the model actually estimates; everything else is derived from them.
Austin rate 0.74 in attack and 1.34 in defence, where 1 is league average and a lower defensive number is better; San Diego rate 0.62 and 1.41.
Where the model differs from the table
The table and the model disagree here: the standings favour San Diego, while our numbers lean the other way. The model weights recent expected goals rather than results already banked, so it moves before the table does.
How this was produced
Publicly tracked record so far: 1151 correct results out of 2437 settled predictions (47%), with 230 exact scorelines (9%). That log is updated automatically after every match and is never edited.
Full method: how the model works.
From the first whistle this page keeps going: the win probabilities at the top are recalculated as the match plays out, reading the score, the clock and any sendings-off. The same model, asked how many goals are left rather than how many there will be.
Team comparison
Bars show each side's share of the two-team total, based on the model's attack/defence ratings and expected goals for this fixture.
Why the model favours this side
The model gives Austin the highest probability at 45%, based on each side's rolling attack and defence ratings estimated from recent match data. The model projects 1.7 expected goals for Austin against 1 for San Diego. Austin's attack/defence rating is 0.74/1.34 versus the league average (1.00 = average), compared with 0.62/1.41 for San Diego.