01 · 2 legs
Safe
- Nottingham Forest to win48%
- Over 1.5 goals76%
Premier LeagueThe City Ground, Nottingham14°1,4 mm22 km/h
Läs på svenskaErik Lindberg · · Written from the model's numbers · How the predictions work
TEXT: Nottingham Forest's 48% chance of victory stands out as the leading probability for this clash, underscoring their edge in both form and expected goals metrics. The hosts' direct style paired with a low defensive base has proven effective, as evidenced by their 1.4 xG per match against Coventry's modest 0.77. This tactical approach aligns well with a Coventry side that has suffered three consecutive losses, further tipping the scales in Forest's favor.
Coventry's struggles are compounded by their higher xGA of 1.5 compared to Forest's 1.2, suggesting potential vulnerabilities at the back which the home side might exploit. The most likely scorelines—1-1 (12%), 1-0 (10%), and 2-1 (9%)—paint a picture of a tightly contested match, where Forest’s marginal dominance could tip the outcome. A 1-0 victory for the hosts seems plausible, with the model slightly favoring an over 2.5 goals scenario at 51%, though not overwhelmingly so.
The numbers suggest a home win, grounded in tactical solidity and statistical superiority.
01 · 2 legs
02 · 3 legs
03 · 4 legs
Bets where the model's probability beats what the odds imply (EV+).
| Bookmaker | 1 · Nottingham Forest | X | 2 · Coventry City |
|---|---|---|---|
| Betsafe | 1.78 | 3.70 | EV+ 16% 4.40 |
| Betsson | 1.80 | 3.71 | EV+ 16% 4.42 |
| Nordicbet | 1.80 | 3.70 | EV+ 16% 4.40 |
| Pinnacle | 1.77 | 3.79 | EV+ 15% 4.37 |
Odds updated 11 Sept, 05:38
Solid line = created (xG), dashed = conceded (xGA).
Last 5 matches. Circle size = pass volume, line width = combinations between players. Attacking left to right.
The same network weighted by offensive threat (xT): circle size = threat created by the player, line width = threat of the combinations. Last 5 matches, attacking left to right.
| Performance | Nottingham Forest | Coventry City |
|---|---|---|
| Points | 2 | 0 |
| xPoints | 4.6 | 3.1 |
| xG per match | 1.4 | 0.77 |
| xGA per match | 1.2 | 1.5 |
| xG within 8s of winning the ball | 0.12 | 0.05 |
| xGA within 8s of losing the ball | 0.21 | 0.3 |
| Playing style | Nottingham Forest | Coventry City |
|---|---|---|
| Build-up efficiency | 0.32 | 0.34 |
| Field tilt | 0.42 | 0.38 |
| xT per match | 0.87 | 0.77 |
| xTA per match | 0.7 | 1 |
| Won balls, offensive half | 24 | 22 |
| Pressing intensity | 0.23 | 0.24 |
| Pressing efficiency | 0.28 | 0.2 |
| Pressing efficiency, offensive half | 0.21 | 0.14 |
| Entries into the box per match | 11 | 8 |
| Entries into the box against | 11 | 15 |
| Pass completion % | 0.69 | 0.74 |
| Pass completion % under pressure | 0.67 | 0.71 |
| Passes per match | 261 | 309 |
| Passes against per match | 393 | 507 |
| Switches of play per match | 23.4 | 20.2 |
| Long balls per match | 31 | 30 |
| Set pieces | Nottingham Forest | Coventry City |
|---|---|---|
| xG from free kicks | 0.06 | 0.02 |
| Corners per match | 3.4 | 4.4 |
| Corners against per match | 5 | 4.7 |
| xG per corner | 0.05 | 0.01 |
| xGA per corner against | 0.04 | 0.01 |
| First touch, offensive corners % | 0.3 | 0.23 |
| First touch, defensive corners % | 0.47 | 0.57 |
| Other | Nottingham Forest | Coventry City |
|---|---|---|
| Throw-in control | 0.81 | 0.77 |
| The goalkeepers | Matz Sels (Nottingham Forest) | Carl Rushworth (Coventry City) |
|---|---|---|
| Saves | 4 | 6 |
| Save % | 57% | 67% |
| xG prevented | 40% | 57% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Nottingham Forest a 48% win probability. Full 1X2 picture: Nottingham Forest 48%, draw 26%, Coventry City 26%.
The model's most likely final score is 1-1 at 12% probability.
The model rates over 2.5 goals at 51% and under at 49%.
The probability of both teams scoring is 55% according to the model.
The same rules as the bookmakers’ builders: legs that contradict or already follow from your slip cannot be combined — for example correct score 2–1 with under 2.5 goals. The difference is that we don’t look the rules up in a table; we compute them straight from the score matrix.
Predictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.