Borussia Dortmund v Hamburger SV
How the SharpXI model rated this Bundesliga fixture — every call it made on shots, cards and fouls, set against what actually happened on the day.
Before Borussia Dortmund beat Hamburger SV 2–0, the SharpXI model made 14 confident calls on the player markets and 10 landed — the strongest being Serhou Guirassy for 1+ shots total (94%, had 2). Its clearest miss: Albert Grønbæk for 1+ tackles (92%, had 0). Every probability here was published before kick-off, priced the same way as every other fixture — one game is noise, not a verdict.
Player markets — the model's calls
Each probability is the model's own number for the headline (1+) line, before any bookmaker margin. The result column is what the player actually recorded.
| Player | Market | Line | Model | Actual | Result |
|---|---|---|---|---|---|
| Serhou Guirassy | shots total | 1+ | 94% | 2 | ✓ |
| Albert Grønbæk | tackles | 1+ | 92% | 0 | ✗ |
| Nicolás Capaldo | tackles | 1+ | 92% | 3 | ✓ |
| Terem Moffi | shots total | 1+ | 91% | 1 | ✓ |
| Otto Stange | shots total | 1+ | 88% | 0 | ✗ |
| Maximilian Beier | shots total | 1+ | 88% | 5 | ✓ |
| Patson Daka | shots total | 1+ | 88% | 3 | ✓ |
| Martin Adeline | tackles | 1+ | 86% | 1 | ✓ |
| Waldemar Anton | tackles | 1+ | 86% | 0 | ✗ |
| Jobe Bellingham | tackles | 1+ | 83% | 4 | ✓ |
| Jordan Torunarigha | tackles | 1+ | 83% | 1 | ✓ |
| Louis Lemke | tackles | 1+ | 83% | 2 | ✓ |
| Serhou Guirassy | shots on target | 1+ | 83% | 2 | ✓ |
| Nicolai Remberg | tackles | 1+ | 80% | 0 | ✗ |
How these are modelled: Shots total Tackles Shots on target
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match goals | O2.5 | 70% | 2 goals | ✗ |
| BTTS | Yes | 59% | No | ✗ |
| Match cards | O4.5 | 50% | 4 cards | ✗ |
How these are modelled: Match goals Match cards
Dig deeper
Past meetings
- Borussia Dortmund 3–2 Hamburger SV Mar 2026
- Hamburger SV 1–1 Borussia Dortmund Nov 2025
Frequently asked
How did the SharpXI model do on Borussia Dortmund v Hamburger SV?
10 of its 14 most-confident calls landed. The board on this page lists every one with the model's pre-kickoff probability next to what actually happened, hits and misses in the same table.
What did the model get wrong on Borussia Dortmund v Hamburger SV?
The most confident call it got wrong was Albert Grønbæk at 92% for tackles — shown in the same table as the hits, marked with a cross. A record that hides its misses isn't a record, so we don't.
Are these probabilities hindsight?
No. Each one is the number the model produced from data available before kick-off, using the same settings as every other fixture on the site — nothing was refitted after the result. That is the only way a per-match report means anything.
Does one match tell you if the model is any good in the Bundesliga?
No, and we'd rather say so. A single fixture is a handful of calls and mostly noise; the season-long, market-by-market record — including the markets that fail to beat a naive guess — is on the track record page.
SharpXI models probabilities from public match data; it does not take bets or guarantee outcomes. Prices are entered per leg in the tool. 18+ — please gamble responsibly.