15 matches · model numbers, form and value in one matrix
| Match | 1X2 odds | Model % | xGoals | PPG L10 |
Goal diff L10 |
Goals/game L10 |
xG L10 |
xG-diff L10 |
Value |
|---|---|---|---|---|---|---|---|---|---|
Denmark
Superligaen
3 ›
|
|||||||||
|
21. Jul
14:00
Full-time
Silkeborg
1
Sonderjyske
0
|
– | 🔒 | 🔒 | 1,3 – |
-5 – |
2,5 – |
🔒 | 🔒 | 🔒 |
|
21. Jul
16:00
Full-time
Vejle
2
Randers FC
3
|
– | 🔒 | 🔒 | 1,4 1,5 |
+1 +0 |
2,7 2,6 |
🔒 | 🔒 | 🔒 |
|
21. Jul
18:00
Full-time
Viborg
3
Brondby
3
|
– | 🔒 | 🔒 | 1,5 1,3 |
+1 +0 |
2,7 3,4 |
🔒 | 🔒 | 🔒 |
Sweden
Allsvenskan
3 ›
|
|||||||||
|
21. Jul
14:00
Full-time
Norrkoping
1
Halmstad
0
|
– | 🔒 | 🔒 | 0,7 0,9 |
-15 -6 |
3,7 3,6 |
🔒 | 🔒 | 🔒 |
|
21. Jul
16:30
Full-time
Elfsborg
3
Mjallby
1
|
– | 🔒 | 🔒 | 2,1 1,9 |
+17 +4 |
4,1 3,2 |
🔒 | 🔒 | 🔒 |
|
21. Jul
16:30
Full-time
Goteborg
1
Vasteras SK
1
|
– | 🔒 | 🔒 | 1,4 0,9 |
-3 -3 |
2,7 2,3 |
🔒 | 🔒 | 🔒 |
Switzerland
Super League
3 ›
|
|||||||||
|
21. Jul
14:15
Full-time
Young Boys
1
Sion
2
|
– | 🔒 | 🔒 | 2,2 – |
+12 – |
3,0 – |
🔒 | 🔒 | 🔒 |
|
21. Jul
16:30
Full-time
Lausanne
3
Basel
2
|
– | 🔒 | 🔒 | 1,3 1,6 |
+0 +3 |
2,4 1,9 |
🔒 | 🔒 | 🔒 |
|
21. Jul
16:30
Full-time
Luzern
1
Servette
2
|
– | 🔒 | 🔒 | 1,0 1,3 |
-3 +0 |
2,5 2,2 |
🔒 | 🔒 | 🔒 |
Norway
Eliteserien
3 ›
|
|||||||||
|
21. Jul
14:30
Full-time
Stromsgodset
0
Tromso
1
|
– | 🔒 | 🔒 | 0,9 1,4 |
-4 -2 |
2,8 2,4 |
🔒 | 🔒 | 🔒 |
|
21. Jul
17:00
Full-time
Ham-Kam
0
Fredrikstad
1
|
– | 🔒 | 🔒 | 1,5 1,8 |
+4 +6 |
3,0 2,8 |
🔒 | 🔒 | 🔒 |
|
21. Jul
17:00
Full-time
Haugesund
1
Viking
0
|
– | 🔒 | 🔒 | 1,1 1,9 |
-3 +6 |
2,1 3,4 |
🔒 | 🔒 | 🔒 |
Poland
Ekstraklasa
3 ›
|
|||||||||
|
21. Jul
14:45
Full-time
Cracovia
1
Piast Gliwice
1
|
– | 🔒 | 🔒 | 1,2 1,5 |
+0 +7 |
2,8 2,1 |
🔒 | 🔒 | 🔒 |
|
21. Jul
17:30
Full-time
Lech Poznan
2
Gornik Zabrze
0
|
– | 🔒 | 🔒 | 1,2 1,4 |
+0 -3 |
2,2 2,7 |
🔒 | 🔒 | 🔒 |
|
21. Jul
20:15
Full-time
Motor Lublin
0
Rakow
2
|
– | 🔒 | 🔒 | – 1,1 |
– -3 |
– 2,1 |
🔒 | 🔒 | 🔒 |
Number of recent matches behind the PPG, goal diff, goals/game and xG columns.
All numbers are statistical estimates from our model. The Value column shows the model's largest deviation from the odds — history shows the market is usually right when the gap is large. Click a row for the full match analysis.