Sheffield United v Reading
How the SharpXI model rated this Championship fixture — every call it made on shots, cards and fouls, set against what actually happened on the day.
Before Sheffield United beat Reading 4–0, the SharpXI model made 14 confident calls on the player markets and 11 landed — the strongest being Oliver Norwood for 1+ tackles (95%, had 6). Its clearest miss: Sander Berge for 1+ tackles (86%, 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 |
|---|---|---|---|---|---|
| Max Lowe | tackles | 1+ | 95% | 4 | ✓ |
| Oliver Norwood | tackles | 1+ | 95% | 6 | ✓ |
| Oli McBurnie | shots total | 1+ | 91% | 4 | ✓ |
| Rhian Brewster | shots total | 1+ | 89% | 1 | ✓ |
| Iliman Ndiaye | shots total | 1+ | 87% | 4 | ✓ |
| Tommy Doyle | tackles | 1+ | 86% | 2 | ✓ |
| Sander Berge | tackles | 1+ | 86% | 0 | ✗ |
| Mamadou Loum | tackles | 1+ | 86% | 1 | ✓ |
| Anel Ahmedhodžić | tackles | 1+ | 86% | 1 | ✓ |
| Reda Khadra | tackles | 1+ | 86% | 0 | ✗ |
| Rhys Norrington-Davies | tackles | 1+ | 80% | 1 | ✓ |
| George Baldock | tackles | 1+ | 80% | 1 | ✓ |
| Mamadou Loum | fouls committed | 1+ | 76% | 1 | ✓ |
| Tyrese Fornah | tackles | 1+ | 75% | 0 | ✗ |
How these are modelled: Tackles Shots total Fouls committed
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match cards | O4.5 | 49% | 0 cards | ✗ |
| BTTS | Yes | 13% | No | ✗ |
| Match goals | O2.5 | 13% | 4 goals | ✓ |
How these are modelled: Match cards BTTS
Dig deeper
Past meetings
- Reading 0–1 Sheffield United Mar 2023
Frequently asked
How did the SharpXI model do on Sheffield United v Reading?
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 Sheffield United v Reading?
The most confident call it got wrong was Sander Berge at 86% 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 Championship?
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.