Union Berlin vs Werder Bremen - Predictions, Stats & Odds
Bundesliga Statistics, AI predictions, (Expected) Lineups and Insights for Gameweek 25
AI Match Prediction
Predicted Lineups
Union Berlin
| Pos | Player |
|---|---|
| GK | |
| DEF | |
| DEF | |
| DEF | |
| DEF | |
| MID | |
| MID | |
| MID | |
| FWD | |
| FWD | |
| FWD |
Werder Bremen
| Pos | Player |
|---|---|
| GK | |
| DEF | |
| DEF | |
| DEF | |
| MID | |
| MID | |
| MID | |
| MID | |
| FWD | |
| FWD | |
| FWD |
Preview for the game Union Berlin vs Werder Bremen
Union Berlin and Werder Bremen arrive in Gameweek 25 with almost identical short-term form: both have taken 4 points from their last 5 Bundesliga matches, with Union’s run of one win, one draw and three defeats mirrored by Werder’s single victory, one draw and three losses. Our Plus Minus model leans slightly towards the hosts, giving Union a 44% chance of victory, with a draw at 31% and an away win at 25%. Recent head-to-head data, however, tilts towards Bremen: they won 1-0 at home in October 2025 and 4-1 in December 2024, while Union’s last success in this fixture was a 2-1 home win in March 2024, alongside a 2-2 draw in May 2025. Union’s defensive structure will again be central, with Frederik Rønnow (GAP +0.5%) behind a back line featuring Danilho Doekhi and Stanley Nsoki. In midfield, Rani Khedira (GAP +0.6%) offers stability in front of the defence, while András Schäfer and Jeong Woo-yeong provide running and support for Andrej Ilić up front. Werder’s approach looks more front-foot: Marco Friedl (GAP +2.9%) and Niklas Stark (GAP +1.8%) anchor the back line, with Jens Stage and Romano Schmid tasked with linking play to a pacey attack including Justin Njinmah and Marco Grüll. With both sides struggling for wins but Bremen holding the psychological edge from the last three meetings (two wins and a draw), the model’s narrow home bias underlines how finely balanced this contest appears. Injuries and availability Werder Bremen are without several options. Amos Pieper is sidelined with an injury and is expected to be out for around 1 month and 1 week, while Maximilian Wöber also faces roughly 1 month and 3 weeks out due to muscular problems. Felix Agu is dealing with an adductor muscle injury and is likely to return in about 1 week and 2 days. Wesley Adeh (ankle ligament tear) and Karim Coulibaly (thigh muscle injury) are both set for spells out of around 1 month and 3 weeks and 2 weeks and 3 days respectively. Samuel Mbangula is recovering from a minor thigh muscle tear and could be back in about 6 days. Long-term, Mitchell Weiser is in rehab after a cruciate ligament rupture, with a projected return in 7 months and 2 weeks, while Victor Boniface is also in build-up training following a knee injury, targeting a comeback in roughly 2 months and 3 weeks. For Union Berlin, Diogo Leite is out with a thigh injury for about 1 month, Tom Rothe is expected to miss around 1 month and 3 weeks, and both Robert Skov (calf injury, about 4 months and 3 weeks) and Josip Juranović (unspecified knock, about 1 month and 2 days) remain in build-up training.
League Table before the game
| # | Team | P | W | D | L | GF | GA | GD | Pts | Form |
|---|---|---|---|---|---|---|---|---|---|---|
| 10 | Union Berlin | 24 | 7 | 7 | 10 | 29 | 38 | -9 | 28 | L D L W L |
| 16 | Werder Bremen | 24 | 5 | 7 | 12 | 25 | 44 | -19 | 22 | D L L L W |
Last Games
Head-to-Head
Bundesliga
Gameweek 25
What is GAP?
What is Plus Minus Goals (G±)?
Plus Minus Goals (G±) is the average goal difference per game while the player was on the pitch. A value above 0 indicates that the team rather wins, a value below 0 means his team concedes more goals than they score when the player is on the pitch. As an example, if the player's team is winning 3:1 the goal difference is +2, if the player's team is loosing 0:1, the goal difference is -1. It is a pure metric which is barely adjusted for circumstances to purely show the goal difference.
What is GAP?
GAP (Game Advantage Percentage) shows the percentage gap between a player and the average league player. It answers the question: How much does a player improve or worsen a team's performance? It is based on high level game data with a focus on the impact on the goal difference (G±) from the last 50 games of a player. Besides that, GAP goes further and considers game context by involving data from the player and all other players who are at the same time on the pitch, no matter if teammates or opponents. Football GAP - the individual metric for team players.