Luxembourg's domestic football competitions are known for their balance and competitiveness. The Bgl Ligue continues to attract interest for its competitive balance and structure. We focus on relevant data points to help you understand how teams are performing.
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 30 | ||||
| Bissen Differdange 2026-05-23 |
WWWDL
WWWDW |
X2 | 1:0 |
70.87%
|
| FC Mamer Jeunesse Canach 2026-05-23 |
DWLDL
LLWLL |
1X | 0:0 |
84.12%
|
| Kaerjeng Jeunesse Esch 2026-05-23 |
LWWLW
WLDWD |
X2 | 0:2 |
53.88%
|
| Niedercorn Dudelange 2026-05-23 |
LLLLW
DLLWD |
2 DNB | 2:4 |
64.44%
|
| Racing Luxembourg Rodange 2026-05-23 |
WLLWL
DLLLL |
1 | 6:1 |
52.53%
|
| UNA Strassen Mondorf 2026-05-23 |
DWDWL
WLWWD |
1X | 0:0 |
50.7%
|
| Victoria Rosport Hostert 2026-05-23 |
LWWWL
LWWLL |
1X | 2:4 |
77.49%
|
| Form | Prediction | Result | Confidence % | |
|---|---|---|---|---|
| Round 29 | ||||
| Hostert Racing Luxembourg 2026-05-17 |
WWLLL
LLWLD |
X2 | 0:1 |
77.54%
|
| Jeunesse Canach Bissen 2026-05-17 |
LWLLL
WWDLW |
2 | 0:5 |
93.5%
|
| Mondorf Union Titus Petange 2026-05-17 |
LWWDD
WDLWW |
1 | 1:0 |
68.52%
|
| Rodange FC Mamer 2026-05-17 |
LLLLW
WLDLD |
1X | 1:1 |
75.23%
|
| Jeunesse Esch Niedercorn 2026-05-17 |
LDWDD
LLLWW |
X2 | 2:1 |
68.4%
|
| Round 27 | ||||
| Differdange UNA Strassen 2026-05-03 |
WWWWL
WLWWD |
1 DNB | 0:0 |
78.77%
|
| Dudelange Victoria Rosport 2026-05-03 |
WDWWD
LWLWL |
1 | 1:2 |
81.42%
|
| Hostert FC Mamer 2026-05-03 |
LLLLW
DLDLW |
X2 | 4:2 |
82.57%
|
| Jeunesse Canach Niedercorn 2026-05-03 |
LLLLL
WWDDL |
2 DNB | 1:0 |
76.53%
|
| Jeunesse Esch Union Titus Petange 2026-05-03 |
WDDLL
LWWDL |
1X | 1:1 |
80.91%
|
| Mondorf Hesperange 2026-05-03 |
WDDWW
LDLWL |
1 | 1:0 |
87.31%
|
| Racing Luxembourg Bissen 2026-05-03 |
WLDLD
DLWWW |
X2 | 0:5 |
79.14%
|
| Rodange Kaerjeng 2026-05-03 |
LWWLW
LWLWD |
X2 | 0:3 |
66.08%
|
Our methodology
Our system generates Bgl Ligue predictions through data analysis and performance tracking. Models like Linear Regression are used to identify relationships within performance data. Team form, scoring efficiency, and defensive organization are key inputs. This supports a more informed evaluation of upcoming fixtures.
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