Tottenham v Burnley
How the SharpXI model rated this Premier League fixture — every call it made on shots, cards and fouls, set against what actually happened on the day.
Before Tottenham beat Burnley 3–0, the SharpXI model made 14 confident calls on the player markets and 11 landed — the strongest being Richarlison for 1+ shots total (94%, had 5). Its clearest miss: Lesley Ugochukwu for 1+ tackles (91%, 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 |
|---|---|---|---|---|---|
| Richarlison | shots total | 1+ | 94% | 5 | ✓ |
| Mohammed Kudus | shots total | 1+ | 94% | 2 | ✓ |
| Jaidon Anthony | shots total | 1+ | 94% | 4 | ✓ |
| Hannibal Mejbri | fouls drawn | 1+ | 92% | 3 | ✓ |
| Lesley Ugochukwu | tackles | 1+ | 91% | 0 | ✗ |
| Mohammed Kudus | fouls drawn | 1+ | 90% | 2 | ✓ |
| Jacob Bruun Larsen | shots total | 1+ | 89% | 0 | ✗ |
| Lyle Foster | shots total | 1+ | 89% | 2 | ✓ |
| Hannibal Mejbri | shots total | 1+ | 89% | 1 | ✓ |
| Brennan Johnson | shots total | 1+ | 89% | 2 | ✓ |
| Josh Cullen | fouls drawn | 1+ | 87% | 1 | ✓ |
| Hannibal Mejbri | fouls committed | 1+ | 84% | 0 | ✗ |
| Pedro Porro | tackles | 1+ | 84% | 2 | ✓ |
| Lucas Bergvall | tackles | 1+ | 84% | 2 | ✓ |
How these are modelled: Shots total Fouls drawn Tackles Fouls committed
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match goals | O2.5 | 67% | 3 goals | ✓ |
| BTTS | Yes | 64% | No | ✗ |
| Match cards | O4.5 | 30% | 0 cards | ✗ |
How these are modelled: Match goals Match cards
Dig deeper
Past meetings
- Burnley 2–2 Tottenham Jan 2026
- Tottenham 2–1 Burnley May 2024
- Burnley 2–5 Tottenham Sep 2023
Frequently asked
How did the SharpXI model do on Tottenham v Burnley?
11 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 Tottenham v Burnley?
The most confident call it got wrong was Lesley Ugochukwu at 91% 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 Premier League?
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.