Borussia Dortmund v FC St. Pauli
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 FC St. Pauli 3–2, the SharpXI model made 14 confident calls on the player markets and 10 landed — the strongest being Lars Ritzka for 1+ tackles (92%, had 6). Its clearest miss: Adam Dźwigała 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 |
|---|---|---|---|---|---|
| Lars Ritzka | tackles | 1+ | 92% | 6 | ✓ |
| Adam Dźwigała | tackles | 1+ | 92% | 0 | ✗ |
| Ricky-Jade Jones | shots total | 1+ | 88% | 4 | ✓ |
| James Sands | tackles | 1+ | 86% | 2 | ✓ |
| Joel Chima Fujita | tackles | 1+ | 86% | 5 | ✓ |
| Karim Adeyemi | shots total | 1+ | 83% | 1 | ✓ |
| Martijn Kaars | shots total | 1+ | 83% | 1 | ✓ |
| Fábio Silva | shots total | 1+ | 83% | 0 | ✗ |
| Mathias Pereira Lage | shots total | 1+ | 80% | 1 | ✓ |
| Mathias Pereira Lage | tackles | 1+ | 80% | 4 | ✓ |
| Hauke Wahl | tackles | 1+ | 80% | 1 | ✓ |
| Karol Mets | tackles | 1+ | 78% | 2 | ✓ |
| Eric Smith | tackles | 1+ | 78% | 0 | ✗ |
| Jobe Bellingham | tackles | 1+ | 78% | 0 | ✗ |
How these are modelled: Tackles Shots total
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match goals | O2.5 | 55% | 5 goals | ✓ |
| BTTS | Yes | 43% | Yes | ✓ |
| Match cards | O4.5 | 29% | 4 cards | ✗ |
How these are modelled: Match goals Match cards
Dig deeper
Past meetings
- FC St. Pauli 3–3 Borussia Dortmund Aug 2025
- FC St. Pauli 0–2 Borussia Dortmund Mar 2025
- Borussia Dortmund 2–1 FC St. Pauli Oct 2024
Frequently asked
How did the SharpXI model do on Borussia Dortmund v FC St. Pauli?
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 FC St. Pauli?
The most confident call it got wrong was Adam Dźwigała 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.