14 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 |
|---|---|---|---|---|---|---|---|---|---|
Germany
2. Bundesliga
5 ›
|
|||||||||
|
16. Jul
13:00
Full-time
Greuther Furth
2
Holstein Kiel
2
|
2,22 / 3,37 / 3,19 | 🔒 | 🔒 | 0,5 1,5 |
-13 +1 |
2,7 2,9 |
🔒 | 🔒 | 🔒 |
|
16. Jul
13:00
Full-time
Regensburg
2
Darmstadt
0
|
3,55 / 3,84 / 1,93 | 🔒 | 🔒 | 1,1 1,3 |
-3 +3 |
2,3 3,5 |
🔒 | 🔒 | 🔒 |
|
16. Jul
13:00
Full-time
Sandhausen
2
Bielefeld
1
|
3,15 / 3,24 / 2,29 | 🔒 | 🔒 | 1,5 0,3 |
+2 -16 |
2,8 2,8 |
🔒 | 🔒 | 🔒 |
|
16. Jul
13:00
Full-time
St Pauli
3
Nurnberg
2
|
2,38 / 3,51 / 2,81 | 🔒 | 🔒 | 1,3 0,9 |
+1 -4 |
2,5 3,4 |
🔒 | 🔒 | 🔒 |
|
16. Jul
20:30
Full-time
Magdeburg
1
Fortuna Dusseldorf
2
|
2,77 / 3,47 / 2,43 | 🔒 | 🔒 | – 1,7 |
– +5 |
– 2,7 |
🔒 | 🔒 | 🔒 |
Sweden
Allsvenskan
2 ›
|
|||||||||
|
16. Jul
15:00
Full-time
Norrkoping
0
Malmo FF
2
|
– | 🔒 | 🔒 | 1,5 1,6 |
+2 +1 |
2,6 3,3 |
🔒 | 🔒 | 🔒 |
|
16. Jul
17:30
Full-time
Djurgarden
5
Varnamo
0
|
– | 🔒 | 🔒 | 2,3 1,1 |
+22 -6 |
3,2 2,6 |
🔒 | 🔒 | 🔒 |
Poland
Ekstraklasa
3 ›
|
|||||||||
|
16. Jul
15:00
Full-time
Lech Poznan
0
Stal Mielec
2
|
– | 🔒 | 🔒 | 2,2 0,8 |
+4 -7 |
2,8 2,9 |
🔒 | 🔒 | 🔒 |
|
16. Jul
17:30
Full-time
Jagiellonia
2
Piast Gliwice
0
|
– | 🔒 | 🔒 | 1,3 2,0 |
-1 +3 |
2,5 2,3 |
🔒 | 🔒 | 🔒 |
|
16. Jul
20:00
Full-time
Korona Kielce
1
Legia
1
|
– | 🔒 | 🔒 | – 1,3 |
– +2 |
– 3,2 |
🔒 | 🔒 | 🔒 |
Norway
Eliteserien
2 ›
|
|||||||||
|
16. Jul
16:00
Full-time
Jerv
1
Sandefjord
2
|
– | 🔒 | 🔒 | 1,0 1,7 |
-1 +1 |
3,3 3,9 |
🔒 | 🔒 | 🔒 |
|
16. Jul
18:00
Full-time
Ham-Kam
0
Bodo/Glimt
2
|
– | 🔒 | 🔒 | 1,6 2,1 |
+8 +13 |
3,0 3,3 |
🔒 | 🔒 | 🔒 |
Switzerland
Super League
2 ›
|
|||||||||
|
16. Jul
18:00
Full-time
Young Boys
4
Zurich
0
|
– | 🔒 | 🔒 | 1,8 1,4 |
+10 +1 |
3,8 3,3 |
🔒 | 🔒 | 🔒 |
|
16. Jul
20:30
Full-time
Winterthur
1
Basel
1
|
– | 🔒 | 🔒 | – 1,3 |
– +2 |
– 2,0 |
🔒 | 🔒 | 🔒 |
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.