01 · 2 legs
Safe
- Double chance St. Gallen or draw (X2)67%
- Over 1.5 goals80%
Swiss Super LeagueSt. Jakob-Park, Basel18°14 km/h
Läs på svenskaSofia Andersson · · The model's read on the match · How the predictions work
St. Gallen's 43% probability to win indicates they dominate this matchup, with a clear edge over Basel. The visitors have been more proficient in creating chances, boasting an xG of 2.1 per match compared to the hosts' 1.1. St. Gallen's ability to control possession should pose a significant challenge for Basel's balanced and physical approach.
Basel's recent head-to-head record against St. Gallen shows only 1 win in 7 encounters, further tilting the expectation towards the visitors. St. Gallen's xPoints of 11.0 surpass Basel's 8.1, reinforcing the visitors' advantage. Despite Basel's slightly better defensive numbers, the attacking prowess of St. Gallen, particularly their xG of 0.46 within 8 seconds of regaining possession, suggests they can exploit any defensive lapses.
While the model suggests a slight lean towards a scoreline of 1-1, the value lies in the under 2.5 goals market, with significant odds of 2.82 offered by Betsafe, Betsson, and Nordicbet. Despite a 57% prediction for over 2.5 goals, the model sees a 43% chance for under, providing a 20% edge for the disciplined bettor.
01 · 2 legs
02 · 3 legs
03 · 4 legs
Bets where the model's probability beats what the odds imply (EV+).
| Bookmaker | 1 · Basel | X | 2 · St. Gallen |
|---|---|---|---|
| Betfair Exchange | 1.25 | 1.26 | 1.25 |
| Betsafe | 2.45 | EV+ 4% 3.85 | EV+ 2% 2.35 |
| Betsson | 2.45 | EV+ 4% 3.85 | EV+ 2% 2.35 |
| Nordicbet | 2.45 | EV+ 4% 3.85 | EV+ 2% 2.35 |
| Pinnacle | 2.55 | EV+ 7% 3.98 | EV+ 6% 2.44 |
Odds updated 17 Sept, 06:36
Head-to-head based on Swiss Super League data since 2023.
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 | Basel | St. Gallen |
|---|---|---|
| Points | 10 | 10 |
| xPoints | 8.1 | 11 |
| xG per match | 1.1 | 2.1 |
| xGA per match | 1.3 | 1.4 |
| xG within 8s of winning the ball | 0.25 | 0.46 |
| xGA within 8s of losing the ball | 0.19 | 0.32 |
| Playing style | Basel | St. Gallen |
|---|---|---|
| Build-up efficiency | 0.32 | 0.33 |
| Field tilt | 0.46 | 0.62 |
| xT per match | 0.91 | 1.3 |
| xTA per match | 1.2 | 0.65 |
| Won balls, offensive half | 21 | 35 |
| Pressing intensity | 0.24 | 0.22 |
| Pressing efficiency | 0.27 | 0.37 |
| Pressing efficiency, offensive half | 0.21 | 0.36 |
| Entries into the box per match | 12 | 21 |
| Entries into the box against | 18 | 14 |
| Pass completion % | 0.78 | 0.66 |
| Pass completion % under pressure | 0.72 | 0.62 |
| Passes per match | 362 | 291 |
| Passes against per match | 381 | 267 |
| Switches of play per match | 31.3 | 19.2 |
| Long balls per match | 32 | 34 |
| Set pieces | Basel | St. Gallen |
|---|---|---|
| xG from free kicks | 0.03 | 0.1 |
| Corners per match | 3.8 | 7.7 |
| Corners against per match | 6.7 | 4 |
| xG per corner | 0.02 | 0.02 |
| xGA per corner against | 0.01 | 0.02 |
| First touch, offensive corners % | 0.63 | 0.46 |
| First touch, defensive corners % | 0.43 | 0.48 |
| Other | Basel | St. Gallen |
|---|---|---|
| Throw-in control | 0.66 | 0.7 |
| The goalkeepers | Mirko Salvi (Basel) | Lawrence Ati Zigi (St. Gallen) |
|---|---|---|
| Saves | 19 | 17 |
| Save % | 59% | 59% |
| xG prevented | 36% | 50% |
| Claims | 0 (0%) | 0 (0%) |
The model gives St. Gallen a 43% win probability. Full 1X2 picture: Basel 30%, draw 27%, St. Gallen 43%.
The model's most likely final score is 1-1 at 12% probability.
The model rates over 2.5 goals at 57% and under at 43%.
The probability of both teams scoring is 60% 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.