Football Fixed Matches
| DATE | HOME – AWAY | TIP | ODDS | RESULT |
| 01.01.2026 | Auckland-Newcastle Jets | 2 | 4.50 | 1:3 |
| 02.01.2026 | Al Nasr-Sohar | X | 3.00 | 0:0 |
| 03.01.2026 | Brisbane Roar-Wellington Phoenix | 2 |
6.10 |
0:3 |
| 04.01.2026 |
UD Ibiza-Eldense |
2 | 3.30 |
0:1 |
| 05.01.2026 | Vizela-Torreense | 2 | 3.90 | 0:1 |
| 06.01.2026 | Dinamo – Hajduk | X |
3.30 |
1:1 |
| 07.01.2026 | Adelaide United – Brisbane Roar | 2 | 4.00 | 0:1 |
| 08.01.2026 | Lokomotiva – Kapfenberg |
X |
5.50 | 1:1 |
| 09.01.2026 | Preston – Wigan | 2 | 4.80 | 0:1 |
| 10.01.2026 | Udinese – Pisa | X | 3.20 | 2:2 |
| 11.01.2026 | WhatsApp:+389 76 456 875 | |||
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Time:16:10
Match:Al Hazem – Al Najma
PICK: 1 ODD : 1.80 FT : ? : ?
WhatsApp:+389 76 456 875
Free Football Prediction for 11.01.2026
Time:20:00
Match:Barcelona – Real Madrid
PICK: 1 ODD : 2.00 FT : 3 : 2 WIN
Free Football Prediction for 10.01.2026
Time:15:30
Match:Frieburg – HSV
PICK: 1 ODD : 1.90 FT: 2 : 1 WIN
Free Football Prediction for 08.01.2026
Time:20:00
Match:Atl.Madrid – Real Madrid
PICK: BTTS-yes ODD : 1.60 FT:1 : 2WIN
Free Football Prediction for 07.01.2026
Time:20:00
Match:Barcelona – Atl.Bilbao
PICK: 1 ODD : 1.50 FT : 5 : 0 WIN
Free Football Prediction for 06.01.2026
Time:18:30
Match:Fenerbahce – Samsunspor
PICK: 1 ODD : 1.80 FT : 2 : 0 WIN
Free Football Prediction for 05.01.2026
Time:18:30
Match:Galatasaray – Trabzonspor
PICK: 1 ODD : 1.60 FT : 5 : 1 WIN
Free Football Prediction for 04.01.2026
Time:17:15
Match: Brest – Auxerre
PICK: 1 ODD : 1.90 FT : 2 : 0 WIN
Free Football Prediction for 03.01.2026
Time:21:00
Match:Espanyol – Barcelona
PICK: 2 ODD : 1.50 FT : 0 : 2 WIN
Free Football Prediction for 02.01.2026
Time:16:50
Match:Al Seeb – Saham
PICK: 1 ODD : 1.60 FT : 3 : 2 WIN
Free Football Prediction for 01.01.2026
Time:16:00
Match:Bristol City – Portsmouth
PICK: 1 ODD : 1.60 FT : 5 : 0 WIN
Statistical Football Prediction: Methods and Limitations
What Is Statistical Football Prediction?
Statistical football prediction is a technique used in sports betting and analytics to forecast the outcomes of football matches through mathematical and statistical tools. The primary goal is to generate more accurate predictions than bookmakers, who often use similar models when setting odds.
Ranking Systems as a Common Method
One of the most widely used methods is the ranking system. These systems assign a numerical rank to each team based on past match results, where higher ranks indicate stronger performance. By comparing the ranks of two teams, analysts can estimate the likely outcome of a match. Examples include the FIFA World Rankings and the World Football Elo Ratings.
Key Limitations of Ranking-Based Models
Despite their popularity, ranking-based models have several important limitations:
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Lack of Detail: These systems do not differentiate between offensive and defensive strengths, which are essential for accurate match predictions.
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Outdated Data: Rankings typically rely on long-term averages, which might overlook recent changes in a team's form or important factors like player injuries.
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Different Objective: While rankings are designed to measure general team strength over time, they are not specifically built to predict the outcomes of individual matches with high precision.
Conclusion
In summary, while ranking systems offer a quick and intuitive way to compare teams, they lack the depth and adaptability required for high-accuracy football predictions. Therefore, more sophisticated models that incorporate dynamic team statistics and real-time data are often necessary to improve predictive accuracy.
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