Reading v Stoke City
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 Reading beat Stoke City 2–1, the SharpXI model made 14 confident calls on the player markets and 11 landed — the strongest being Liam Delap for 1+ fouls committed (81%, had 2). Its clearest miss: Jacob Brown 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.
11 matches on record — too few to quote a card rate against. See the record →
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 |
|---|---|---|---|---|---|
| Liam Delap | fouls committed | 1+ | 81% | 2 | ✓ |
| Jacob Brown | fouls committed | 1+ | 78% | 0 | ✗ |
| Tyrese Campbell | shots total | 1+ | 76% | 1 | ✓ |
| Jacob Brown | shots total | 1+ | 76% | 3 | ✓ |
| Lucas João | fouls committed | 1+ | 75% | 1 | ✓ |
| Liam Delap | shots total | 1+ | 74% | 0 | ✗ |
| Andy Yiadom | fouls drawn | 1+ | 73% | 5 | ✓ |
| Shane Long | shots total | 1+ | 73% | 1 | ✓ |
| Lucas João | shots total | 1+ | 72% | 4 | ✓ |
| Lucas João | fouls drawn | 1+ | 71% | 2 | ✓ |
| Tom Ince | fouls drawn | 1+ | 70% | 3 | ✓ |
| Sam Clucas | fouls committed | 1+ | 70% | 2 | ✓ |
| Shane Long | fouls committed | 1+ | 70% | 0 | ✗ |
| Tom Ince | shots total | 1+ | 69% | 2 | ✓ |
How these are modelled: Fouls committed · Shots total · Fouls drawn
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
- Stoke City 4–0 Reading Jan 2023
Frequently asked
How did the SharpXI model do on Reading v Stoke City?
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 Reading v Stoke City?
The most confident call it got wrong was Jacob Brown 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.