Model: history/v2-w1460-r150. Probabilities are produced by our own model from public match data. They are not odds and not betting advice.
Why — recent form
"—" means the number is not available in our data; we never fill gaps with zeros. Recent form covers only matches with expected-goals data, which may be fewer than the team's actual recent fixtures.
| Metric | Paderborn | Hamburger SV |
|---|---|---|
| Recent xG (attack, per-match avg) | 1.01 | 1.0 |
| Recent xGA (defence, per-match avg) | 2.04 | 1.98 |
| Sample size (matches with xG data) | 5 | 5 |
| Rest days since last match | 7 | 7 |
| Season pressing (PPDA, lower = more intense) | 15.4 | 16.5 |
| Matches in the last 7 days | 2 | 2 |
| Matches in the next 7 days | 1 | 2 |
| Travel to this match (km) | 149 | 221 |
What the data says
Paderborn vs Hamburger SV: what the data says
Home last five: 0.80 points, 1.17 xG for, 2.25 against per game. Away: 1.80 / 1.20 / 2.29.
What is worth noting before kickoff?
What could go against this prediction
Injuries & suspensions
Latest pre-match snapshot from our data source; availability varies by league.
Paderborn
- injured Marcel Hoffmeier return: A few weeks
- injured Nyamekye Awortwie-Grant return: Late October 2026
- injured Oliver Batista Meier return: Mid November 2026
- injured Sebastian Klaas return: Late October 2026
- injured Timur Gayret return: Early January 2027
Hamburger SV
- injured Nicolai Remberg return: Late June 2027
- injured Patson Daka return: doubtful
- suspended Mario Vušković return: Early November 2026
Head to head
All-time (per our source): Paderborn 6 · 2 2 draws · 7 Hamburger SV
| Date | Home | Score | Away |
|---|---|---|---|
| 2025-03-02 | Paderborn | 2 - 0 | Hamburger SV |
| 2024-09-28 | Hamburger SV | 2 - 2 | Paderborn |
| 2024-05-10 | Paderborn | 1 - 0 | Hamburger SV |
| 2023-12-09 | Hamburger SV | 1 - 2 | Paderborn |
| 2023-05-05 | Hamburger SV | 2 - 2 | Paderborn |
Answers are generated from the model probabilities and the published evidence on this page only — the AI cannot see anything else and cannot change the probabilities.
Probabilities are generated by our own statistical model from public match data. AI is used only to explain the evidence and analysis.
Data coverage