Swansea 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 Swansea City beat Reading 3–2, the SharpXI model made 14 confident calls on the player markets and 8 landed — the strongest being Mamadou Loum for 1+ fouls committed (81%, had 2). Its clearest miss: Matthew Sorinola for 1+ fouls committed (78%, 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 |
|---|---|---|---|---|---|
| Mamadou Loum | fouls committed | 1+ | 81% | 2 | ✓ |
| Joel Latibeaudiere | fouls committed | 1+ | 79% | 2 | ✓ |
| Matthew Sorinola | fouls committed | 1+ | 78% | 0 | ✗ |
| Yakou Méïté | fouls committed | 1+ | 77% | 1 | ✓ |
| Oliver Cooper | fouls drawn | 1+ | 75% | 1 | ✓ |
| Junior Hoilett | fouls committed | 1+ | 74% | 1 | ✓ |
| Yakou Méïté | shots total | 1+ | 74% | 1 | ✓ |
| Lucas João | fouls committed | 1+ | 73% | 1 | ✓ |
| Armstrong Oko-Flex | shots total | 1+ | 72% | 0 | ✗ |
| Matthew Sorinola | fouls drawn | 1+ | 72% | 0 | ✗ |
| Armstrong Oko-Flex | fouls committed | 1+ | 72% | 0 | ✗ |
| Andy Yiadom | fouls committed | 1+ | 70% | 0 | ✗ |
| Oliver Cooper | shots total | 1+ | 69% | 2 | ✓ |
| Tom Ince | fouls committed | 1+ | 68% | 0 | ✗ |
How these are modelled: Fouls committed · Fouls drawn · Shots total
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match cards | O4.5 | 28% | 2 cards | ✗ |
How these are modelled: Match cards
Dig deeper
Past meetings
- Reading 2–1 Swansea City Dec 2022
Frequently asked
How did the SharpXI model do on Swansea City v Reading?
8 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 Swansea City v Reading?
The most confident call it got wrong was Matthew Sorinola at 78% for fouls committed — 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.