AI Match Insights
Super League Sep 21, 2025
NAPSA Stars FC
HomeVS
13:00
Mines
AwayAI Predictions 48.5% Confidence
NAPSA Stars FC Win
Draw
Mines Win
Home Win
(49% confidence)
Predicted Score: 3-0
Decision Justification
Validated Rules (80%+ Accuracy from 90-Day Backtest)
M85+S60 (75.3%)
POS_GAP_5+ (67.0%)
xG_ADV (67.5%)
Player Score
40%
Momentum
94%
Standings
67%
Market
50%
Combined: 54%
Draw Risk: 30%
xG: 3.79 - 0.45
Key Insights
xG dominance: 3.8 vs 0.5
Position gap: 6 places
High draw risk (30%) - confidence penalized
Score Prediction Analysis
NAPSA Stars FC Goal Probabilities
0 goals:
1 goals:
2 goals:
3 goals:
4 goals:
Mines Goal Probabilities
0 goals:
1 goals:
2 goals:
3 goals:
4 goals:
Most Likely Scorelines
3-0 (13%)
2-0 (10%)
3-1 (6%)
1-0 (5%)
2-1 (5%)
1-1 (2%)
BTTS (Both Teams Score)
35%
Over 2.5 Goals
61%
Under 2.5 Goals
39%
NAPSA Stars FC Form 6.0%
| Date | Match | Result |
|---|---|---|
| Sep 13 | NAPSA Sta… vs Power Dyn… | 2-0 |
| Aug 30 | NAPSA Sta… vs Red Arrows | 1-1 |
| Aug 23 | NAPSA Sta… vs Mufulira … | 0-0 |
| Aug 16 | NAPSA Sta… vs Green Eag… | 0-2 |
| May 17 | NAPSA Sta… vs Mutondo S… | 0-0 |
| Apr 19 | NAPSA Sta… vs Kabwe War… | 2-2 |
| Apr 03 | NAPSA Sta… vs Power Dyn… | 0-2 |
| Mar 13 | NAPSA Sta… vs Zanaco | 1-0 |
| Feb 23 | NAPSA Sta… vs Red Arrows | 1-0 |
| Feb 15 | NAPSA Sta… vs Mufulira … | 1-0 |
Mines Form 2.5%
| Date | Match | Result |
|---|---|---|
| Sep 13 | Mines vs Green Buf… | 2-0 |
| Aug 31 | Mines vs Power Dyn… | 0-0 |
| Aug 23 | Mines vs Red Arrows | 4-1 |
| Aug 16 | Mines vs Mufulira … | 1-2 |
Key Analysis Factors
- Mines struggling (3L in last 5) Away
Final Verdict
STANDARD: NAPSA Stars FC to win (60% confidence)
STANDARD Tier
Predicted: 1-0
60% Confidence
Rules Passed
POS_GAP_5+ (66.8%)
AWAY_BOTTOM_5 (61.2%)
HOME_ADVANTAGE
Key Factors
- No key factors identified
NAPSA Stars FC Power
0
Mines Power
0
Home Form
N/A
Away Form
N/A
League Standings Context
12
NAPSA Stars FC Position+6
Position Gap18
Mines Position
Home Win Rate: 38%
Away Win Rate: 11%
Disclaimer: These AI predictions are based on historical data and statistical analysis.
Football matches can be unpredictable, and actual results may vary significantly from predictions.