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Compare Minnesota vs San Diego

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

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

Minnesota Minnesota Home Team
San Diego San Diego Away Team
Minnesota
42.0
W L D D D L D L L D

Last 10 Matches

San Diego
52.8
W L W D W L L D W D

Performance Radar

Minnesota
San Diego

Categories Won

2

Minnesota

4

Draw

9

San Diego

Statistical Comparison

Win Percentage
10%

1W, 5D, 4L

40%

4W, 3D, 3L

Goals Scored / Match
1.3

13 / 10 matches

1.8

18 / 10 matches

Goals Conceded / Match
1.3

13 / 10 matches

1.3

13 / 10 matches

Goal Difference
0

0

+5

+5

Clean Sheet
10%

1 / 10 matches

40%

4 / 10 matches

Over 2.5 Goals
50%

5 / 10 matches

50%

5 / 10 matches

Both Teams to Score
80%

8 / 10 matches

50%

5 / 10 matches

Top Scorer
K. Yeboah (3 goals)
M. Ingvartsen (4 goals)
Most Goals by Half
1st Half: 5 / 2nd Half: 8
1st Half: 7 / 2nd Half: 11
Home Win Rate
0%

0W / 6 matches

60%

3W / 5 matches

Away Win Rate
25%

1W / 4 matches

20%

1W / 5 matches

Schedule Strength (SoS)
50.7

League Difficulty: 55.0, Opponent Quality: 47.9

52.4

League Difficulty: 55.0, Opponent Quality: 50.6

Elite Opponent Record
0%

0W / 0 matches

0%

0W / 0 matches

Expected Goals (xG)
1.35

Actual: 1.3 | Diff: -0.05

1.69

Actual: 1.8 | Diff: +0.11

Adjusted Power Rating
42.0

Attack: 43.6, Defense: 57.1, Form: 10.1

52.8

Attack: 61.4, Defense: 58.0, Form: 41.0

Goal Timing Analysis

2

0-15'

1
1

16-30'

3
2

31-45'

2
1

46-60'

4
3

61-75'

3
4

76-90+'

5
Minnesota
San Diego
Minnesota

Power Rating Breakdown

42.0

Overall

Attack 43.6
Defense 57.1
Form 10.1
Consistency 77.2
San Diego

Power Rating Breakdown

52.8

Overall

Attack 61.4
Defense 58.0
Form 41.0
Consistency 50.5

Strength of Schedule

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

League Difficulty

55.0 vs 55.0

Opponent Quality

47.9 vs 50.6

Elite Opponent Record

0% vs 0%
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%)
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%)

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
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%
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%

AI Analysis

While the data leans decisively toward one side, dismissing the underdog would be premature. Adjusting for strength of schedule brings the margins closer together, yet the broader trend holds firm throughout the analysis.

With comparable strength of schedule figures (50.7 vs 52.4), 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.

The defensive records are closely aligned, with Minnesota giving up 1.3 and San Diego giving up 1.3 per fixture.

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

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

Statistical modeling projects 2.9 goals in this fixture. The data points Over 2.5 as the value threshold, while BTTS stands at likely based on both sides' scoring records.

❄️ 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.

📈 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.

📊 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.

While San Diego holds a measurable edge in the adjusted standings, the 10.8-point differential in power ratings indicates a competitive matchup rather than a clear-cut outcome.

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

Minnesota

Minnesota

VS
San Diego

San Diego

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.

Minnesota

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

San Diego

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

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