Coventry City 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 Coventry City beat Reading 2–1, the SharpXI model made 14 confident calls on the player markets and 13 landed — the strongest being Josh Eccles for 1+ tackles (95%, had 5). Its clearest miss: Kelvin Ehibhatiomhan for 1+ shots total (88%, 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 |
|---|---|---|---|---|---|
| Josh Eccles | tackles | 1+ | 95% | 5 | ✓ |
| Viktor Gyökeres | shots total | 1+ | 95% | 7 | ✓ |
| Gustavo Hamer | shots total | 1+ | 92% | 4 | ✓ |
| Matt Godden | shots total | 1+ | 91% | 2 | ✓ |
| Andy Yiadom | tackles | 1+ | 91% | 4 | ✓ |
| Cesare Casadei | tackles | 1+ | 89% | 2 | ✓ |
| Kelvin Ehibhatiomhan | shots total | 1+ | 88% | 0 | ✗ |
| Tyrese Fornah | tackles | 1+ | 86% | 1 | ✓ |
| Nesta Guinness-Walker | tackles | 1+ | 86% | 1 | ✓ |
| Luke McNally | tackles | 1+ | 86% | 1 | ✓ |
| Gustavo Hamer | tackles | 1+ | 86% | 1 | ✓ |
| Mamadi Camara | tackles | 1+ | 86% | 1 | ✓ |
| Brooke Norton-Cuffy | tackles | 1+ | 86% | 2 | ✓ |
| Femi Azeez | shots total | 1+ | 82% | 2 | ✓ |
How these are modelled: Tackles Shots total
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match cards | O4.5 | 32% | 9 cards | ✓ |
| BTTS | Yes | 13% | Yes | ✓ |
| Match goals | O2.5 | 13% | 3 goals | ✓ |
How these are modelled: Match cards BTTS
Dig deeper
Past meetings
- Reading 1–0 Coventry City Dec 2022
Frequently asked
How did the SharpXI model do on Coventry City v Reading?
13 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 Coventry City v Reading?
The most confident call it got wrong was Kelvin Ehibhatiomhan at 88% for shots total — 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.