01 · 2 legs
Safe
- Cremonese to win49%
- Under 3.5 goals73%
Serie BStadio Giovanni Zini, Cremona21°0,6 mm6 km/h
Läs på svenskaOscar Nilsson · · Model-assisted analysis, fact-checked · How the predictions work
With Cremonese's model probability at 49% to clinch a win, the market gives them a slight edge in this Serie B clash against Virtus Entella. The expected goals tally at 1.55 for the hosts compared to 1.10 for the visitors suggests a marginal advantage for Cremonese, although the game is poised delicately with only a thin margin separating the two teams' offensive outputs. Despite the hosts' imperfect start with three points, their statistical edge in expected points and goals hints at underlying strengths not fully reflected in the league table just yet.
The most likely scorelines—1-1 at 12% and 1-0 at 11%—paint a picture of a tight contest. Given both teams employ a possession-heavy, high-pressing style, this encounter might hinge on who executes better on the day. Despite Cremonese's upper hand in xPoints and xG per match, Entella's near-parity in expected goals against (xGA) suggests their defensive solidity could frustrate the hosts' attempts to capitalize on possession.
At first glance, this looks like a low-scoring affair, yet the statistical model indicates a 49% likelihood for over 2.5 goals, almost a coin flip. Both teams to score has a slight edge at 53%, suggesting that while goals might be hard to come by, neither side is likely to keep a clean sheet. The predicted 1-1 scoreline holds water given these probabilities.
Bookmakers might have missed a trick if they're offering odds that deviate from this analysis. If you find Cremonese win odds at 2.05 or above, the value may lie with backing the hosts. This is a subtle nod to Cremonese's slightly superior metrics. While the numbers on paper favor them, matches are not won on spreadsheets—but that's where the sharpest opportunities can often be found.
01 · 2 legs
02 · 3 legs
03 · 4 legs
No odds available yet.
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 | Cremonese | Virtus Entella |
|---|---|---|
| Points | 3 | 1 |
| xPoints | 3.6 | 3.3 |
| xG per match | 1 | 0.94 |
| xGA per match | 0.93 | 0.9 |
| xG within 8s of winning the ball | 0.09 | 0.17 |
| xGA within 8s of losing the ball | 0.29 | 0.28 |
| Playing style | Cremonese | Virtus Entella |
|---|---|---|
| Build-up efficiency | 0.32 | 0.3 |
| Field tilt | 0.76 | 0.74 |
| xT per match | 1.2 | 1.2 |
| xTA per match | 0.4 | 0.38 |
| Won balls, offensive half | 27 | 32 |
| Pressing intensity | 0.24 | 0.21 |
| Pressing efficiency | 0.26 | 0.32 |
| Pressing efficiency, offensive half | 0.23 | 0.3 |
| Entries into the box per match | 11 | 16 |
| Entries into the box against | 6 | 4 |
| Pass completion % | 0.83 | 0.78 |
| Pass completion % under pressure | 0.8 | 0.7 |
| Passes per match | 520 | 369 |
| Passes against per match | 341 | 300 |
| Switches of play per match | 31.4 | 31.6 |
| Long balls per match | 30 | 36 |
| Set pieces | Cremonese | Virtus Entella |
|---|---|---|
| xG from free kicks | 0.01 | 0.09 |
| Corners per match | 5.4 | 4.9 |
| Corners against per match | 3 | 2.3 |
| xG per corner | 0.01 | 0.02 |
| xGA per corner against | 0.07 | 0.07 |
| First touch, offensive corners % | 0.44 | 0.53 |
| First touch, defensive corners % | 0.56 | 0.86 |
| Other | Cremonese | Virtus Entella |
|---|---|---|
| Throw-in control | 0.74 | 0.8 |
| The goalkeepers | Federico Agazzi (Cremonese) | Federico Del Frate (Virtus Entella) |
|---|---|---|
| Saves | 6 | 5 |
| Save % | 60% | 50% |
| xG prevented | 33% | 28% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Cremonese a 49% win probability. Full 1X2 picture: Cremonese 49%, draw 26%, Virtus Entella 26%.
The model's most likely final score is 1-1 at 12% probability.
The model rates over 2.5 goals at 49% and under at 51%.
The probability of both teams scoring is 53% 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.