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Compare San Diego vs Minnesota

San Diego vs Minnesota Head-to-Head Stats and Form Comparison

Compare San Diego vs Minnesota: head-to-head stats, recent form, goals, defensive record and strength indicators from last matches.

San Diego San Diego Home Team
Minnesota Minnesota Away Team
San Diego
52.8
W L W D W L L D W D

Last 10 Matches

Minnesota
42.0
W L D D D L D L L D

Performance Radar

San Diego
Minnesota

Categories Won

9

San Diego

4

Draw

2

Minnesota

Statistical Comparison

Win Percentage
40%

4W, 3D, 3L

10%

1W, 5D, 4L

Goals Scored / Match
1.8

18 / 10 matches

1.3

13 / 10 matches

Goals Conceded / Match
1.3

13 / 10 matches

1.3

13 / 10 matches

Goal Difference
+5

+5

0

0

Clean Sheet
40%

4 / 10 matches

10%

1 / 10 matches

Over 2.5 Goals
50%

5 / 10 matches

50%

5 / 10 matches

Both Teams to Score
50%

5 / 10 matches

80%

8 / 10 matches

Top Scorer
M. Ingvartsen (4 goals)
K. Yeboah (3 goals)
Most Goals by Half
1st Half: 7 / 2nd Half: 11
1st Half: 5 / 2nd Half: 8
Home Win Rate
60%

3W / 5 matches

0%

0W / 6 matches

Away Win Rate
20%

1W / 5 matches

25%

1W / 4 matches

Schedule Strength (SoS)
52.4

League Difficulty: 55.0, Opponent Quality: 50.6

50.7

League Difficulty: 55.0, Opponent Quality: 47.9

Elite Opponent Record
0%

0W / 0 matches

0%

0W / 0 matches

Expected Goals (xG)
1.69

Actual: 1.8 | Diff: +0.11

1.35

Actual: 1.3 | Diff: -0.05

Adjusted Power Rating
52.8

Attack: 61.4, Defense: 58.0, Form: 41.0

42.0

Attack: 43.6, Defense: 57.1, Form: 10.1

Goal Timing Analysis

1

0-15'

2
3

16-30'

1
2

31-45'

2
4

46-60'

1
3

61-75'

3
5

76-90+'

4
San Diego
Minnesota
San Diego

Power Rating Breakdown

52.8

Overall

Attack 61.4
Defense 58.0
Form 41.0
Consistency 50.5
Minnesota

Power Rating Breakdown

42.0

Overall

Attack 43.6
Defense 57.1
Form 10.1
Consistency 77.2

Strength of Schedule

Measures the difficulty of opponents faced. Higher = tougher schedule.

League Difficulty

55.0 vs 55.0

Opponent Quality

50.6 vs 47.9

Elite Opponent Record

0% vs 0%
San Diego logo San Diego
W
Colorado (49%)
L
Portland (58%)
W
LAFC (58%)
D
Minnesota (50%)
W
Dallas (53%)
L
Colorado (54%)
L
Whitecaps (55%)
D
Cincinnati (56%)
Minnesota logo Minnesota
W
Earthquakes (38%)
L
Atlanta United (44%)
D
Salt Lake (54%)
D
San Diego (54%)
D
Whitecaps (55%)
L
Sporting KC (46%)
D
Salt Lake (49%)
L
New England (53%)

Opponent Quality: Quality blends league strength, recent points form, goal difference, and home/away context. It is not only club size or reputation.

Opponent Breakdown
Opponent Breakdown
Score
Opp. Quality
Colorado H
3 - 0 W
49%
Portland A
1 - 3 L
58%
LAFC A
1 - 0 W
58%
Minnesota A
1 - 1 D
50%
Dallas H
1 - 0 W
53%
Colorado A
0 - 1 L
54%
Whitecaps H
2 - 4 L
55%
Cincinnati H
3 - 3 D
56%
Austin H
5 - 0 W
37%
Sounders A
1 - 1 D
36%
Opponent Breakdown
Opponent Breakdown
Score
Opp. Quality
Earthquakes A
5 - 1 W
38%
Atlanta United H
1 - 2 L
44%
Salt Lake A
1 - 1 D
54%
San Diego H
1 - 1 D
54%
Whitecaps H
0 - 0 D
55%
Sporting KC A
1 - 2 L
46%
Salt Lake H
1 - 1 D
49%
New England A
1 - 2 L
53%
Colorado H
0 - 1 L
49%
Austin H
2 - 2 D
37%

AI Analysis

A statistical edge is evident here, but the trailing side carries enough threat to keep this competitive. Once opponent quality is accounted for, the differential softens somewhat without fundamentally altering the overall outlook.

With comparable strength of schedule figures (52.4 vs 50.7), the opposition quality faced by both sides has been largely equivalent, giving these head-to-head stats greater analytical validity.

San Diego leads the attacking statistics, averaging 1.8 goals per game compared to Minnesota's 1.3 — a meaningful but far from decisive advantage.

Defensively, San Diego and Minnesota are evenly matched, allowing 1.3 and 1.3 goals per game respectively.

San Diego has not faced any elite-level opponents in their recent matches, making it difficult to assess their ceiling.

Minnesota has not faced any elite-level opponents in their recent matches, making it difficult to assess their ceiling.

Based on the combined statistics, expect 2.9 total goals. Over 2.5 goals is the statistical lean, with BTTS (Both Teams to Score) being likely.

📈 Form Momentum: San Diego has been remarkably consistent, maintaining a steady 1.5 points per game over their last 10 matches. This stability makes them a predictable but reliable force.

❄️ Form Momentum: Minnesota is struggling for form, winning just 1 of their last 10 matches. Teams in this state often lack the confidence to compete in tight moments.

📊 Key Trend: The form trajectories are diverging. San Diego is on the rise with 4W in last 10, while Minnesota shows signs of decline with 1W in last 10.

💡 Why This Matters: The 10.8-point power rating gap between these teams translates to approximately a 77% win probability for San Diego. In practical terms, San Diego would win 8 out of 10 such matchups.

San Diego has the edge based on adjusted metrics, but this is far from a foregone conclusion. The 10.8-point power gap suggests an advantage without guaranteeing victory.

These two teams drew 1-1 in the Major League Soccer (2026-08-02). The stalemate suggests these sides are closely matched, and another tight contest could be on the cards. With the previous match ending in a draw, neither side holds a psychological edge. Both teams will feel they have a genuine chance of winning.

Match Simulator

AI-powered match simulation based on real statistics

San Diego

San Diego

VS
Minnesota

Minnesota

In H2H (head-to-head) matchups, to eliminate momentary fluctuations and coincidences, we limit our analyses to an optimal depth of exactly 10 matches. Neither less, nor more. This focused approach is our undisputed gold standard, revealing the tactical and psychological supremacy teams hold over each other in its purest form. We do not dwell on the noise of the past; we concentrate on the millimetric precision of current form.

Compare Another Pair

Comparison Summary

This head-to-head comparison analyzes the last 10 matches of each team, evaluating attack power, defensive strength, form consistency, and overall performance metrics. The power ratings are calculated using a weighted algorithm that considers goals scored, goals conceded, win rate, and recent form trends.

San Diego

4W 3D 3L · 18 goals scored · 13 conceded

Minnesota

1W 5D 4L · 13 goals scored · 13 conceded

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