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San Diego vs Philadelphia Union 0-5 Score & Prediction Review
Major League Soccer - Season 2026
0–5
On these chances San Diego would usually take 0.9 points and Philadelphia Union 1.9; they took 0 and 3. Bookmakers' favourite: Philadelphia Union.
Calculated by MyGameOdds · xG: our own model
How it works
Chances (xG): every shot gets a value for how likely it was to go in, and we add them up (our own model). Points their chances were worth: how many points teams usually get from chances like these.
Smash-and-grab: the winner created at least 0.8 xG less than the loser. Robbed: a draw where one side created at least 0.8 xG more. Anything else is a fair result. No verdict after extra time or when there's no xG.
Can you trust it? In these games, SportMonks' own xG agreed on who created more in 95% of the wins and 98% of the draws, and Flashscore agreed in 16 of the 20 games we checked by hand.
How we measure →San Diego vs Philadelphia Union stats: how the match was played
Major League Soccer
Whether the result matched the chances each side created, measured with our own xG.
Level on shots on target
San Diego
Philadelphia Union
5
Shots on target
5
2
Big chances
5
11
Corners
4
2
Yellow cards
2
58%
Possession
42%
San Diego vs Philadelphia Union — Our Model vs the Bookmakers
Market check · Major League Soccer
How our model’s pick did in each market, next to the bookmakers’ last odds before kick-off (margin removed): what was correct, what was wrong, and how often our predictions like this one came true over the last 12 months.
How to read it
Our model’s pick
San Diego to win
WrongThe bookmakers’ favourite was correct: Philadelphia Union to win.
Our track record
In 1,064 matches over the last 12 months where our model gave the same pick a 40–45% chance but the bookmakers favoured a different outcome, it came true 30.4% of the time: closer to the bookmakers’ 30.3% than to our 40–45%.
Our model’s pick
Yes, both score
WrongOur track record
In 406 matches over the last 12 months where our model gave the same pick a 65–70% chance and the bookmakers agreed, it came true 62.1% of the time (bookmakers said 65.2%).
Our model’s pick
Over 2.5 goals
CorrectOur track record
In 1,157 matches over the last 12 months where our model gave the same pick a 65–70% chance and the bookmakers agreed, it came true 68.0% of the time (bookmakers said 66.8%).
Our model’s pick
Under 3.5 goals
WrongOur track record
In 937 matches over the last 12 months where our model gave the same pick a 55–60% chance and the bookmakers agreed, it came true 60.1% of the time (bookmakers said 60.1%).
Our model’s pick
Draw at half-time
WrongOur track record
In 2,043 matches over the last 12 months where our model gave the same pick a 35–40% chance and the bookmakers agreed, it came true 40.3% of the time (bookmakers said 41.2%).
Our model’s pick
San Diego 2+ goals
WrongOur track record
In 2,827 matches over the last 12 months where our model gave the same pick a 50–55% chance and the bookmakers agreed, it came true 59.4% of the time (bookmakers said 58.6%).
Our model’s pick
Philadelphia Union 0–1 goals
WrongThe bookmakers’ favourite was correct: Philadelphia Union 2+ goals.
Our track record
In 632 matches over the last 12 months where our model gave the same pick a 55–60% chance but the bookmakers favoured a different outcome, it came true 45.1% of the time: closer to the bookmakers’ 44.7% than to our 55–60%.
Odds: the last ones before kick-off. Picks are marked on the result after 90 minutes. The track record uses closing odds.
San Diego vs Philadelphia Union 0-5 — How Our Predictions Performed
The prediction cards below show the pre-match probabilities our AI model generated for San Diego vs Philadelphia Union. Correct predictions are highlighted in green, so you can quickly see where the model read this match well.
Winner
1X 67%
BTTS*
Yes 67%
Correct Score
1-1 09%
Over/Under 2.5 goals
over 67%
Over/Under 3.5 goals
over 54%
Winner
1X 67%
BTTS*
Yes 67%
Correct Score
1-1 09%
Over/Under 2.5 goals
over 67%
Over/Under 3.5 goals
over 54%
Full Time
Goals Over/Under
| <1.5 | >1.5 | <2.5 | >2.5 | |
|---|---|---|---|---|
| FT | 14% | 86% | 33% | 67% |
| <3.5 | >3.5 | <4.5 | >4.5 | |
|---|---|---|---|---|
| FT | 46% | 54% | 72% | 28% |
Team Goals Over/Under
| <0.5 | >0.5 | <1.5 | >1.5 | |
|---|---|---|---|---|
| 21% | 79% | 48% | 52% | |
| 29% | 71% | 58% | 42% |
| <2.5 | >2.5 | <3.5 | >3.5 | |
|---|---|---|---|---|
| 74% | 26% | 89% | 11% | |
| 81% | 19% | 93% | 7% |
1st Half
1st Score
Half Time/Full Time
1-1
26%
2-2
17%
X-1
16%
X-X
13%
X-2
9%
2-X
6%
1-X
5%
1-2
3%
2-1
3%
Correct Score
1-1
9.3%
2-1
9.0%
1-2
7.9%
2-2
7.5%
1-0
5.8%
2-0
5.5%
3-1
5.2%
0-1
4.8%
3-2
4.1%
0-0
3.8%
1-3
3.8%
2-3
3.7%
3-0
3.6%
0-2
3.6%
*Probability of each predicted outcome is expressed in percentage (%)
*BTTS - Both teams to score