Banker as favourites
8/9Lugano won 8 of 9 as favourites (league 51%).
Super League Predictions & Stats
Free AI predictions for every upcoming Super League match — 1X2, Both Teams to Score, Over/Under goals and Correct Score probabilities.
Predictions updated on 11 October 2026.
Super League Predictions by Market
Season 2026/2027 · Round 10 · Regular Season
Full-Time Result
56%
SUCCESS RATE AVG.
Both Teams To Score
67%
SUCCESS RATE AVG.
Over/Under 2.5 Goals
72%
SUCCESS RATE AVG.
Over/Under 3.5 Goals
51%
SUCCESS RATE AVG.
First Half Result
45%
SUCCESS RATE AVG.
Correct Score
15%
SUCCESS RATE AVG.
Super League 2026/2027 prediction accuracy over the last 100 matches: 1X2 56%, BTTS 67%, Over/Under 2.5 72%, Over/Under 3.5 51%, correct score 15%.
Super League stats: goals, BTTS, corners and cards vs other leagues
How this competition ranks among the leagues and cups we cover for goals, chances (xG), corners and cards.
How to read it
last 12 months · 237 matchesrank 1 = highest of 63 competitionsGoals galoreAway days payCard-heavy
Goals a match
3.41
2nd of 63
xG a match
3.21
1st of 62
Corners a match
10.33
8th of 62
Cards a match
4.79
13th of 63
Calculated by MyGameOdds · xG: our own model
How it works
We use the league's matches from the last 12 months, without qualifying rounds, and rank it against the 63 leagues and club competitions with 50 or more matches in that time (1 = highest). A label marks a league in the top fifth on goals, home or away wins, draws, cards or corners, or in the bottom fifth on goals. xG is our estimate of each match's chances from its shots.
Super League: the stats that stand out
The Super League teams most unusual in their last 10 games.
How to read it
the teamleague averageeach team's last 10 games8/9Goal-fests
10/10Young Boys games went over 2.5 goals in 10 of their last 10 (league 68%).
Goals at both ends
9/9Vaduz: both teams scored in 9 of their last 9 (league 66%).
Shot-shy
4/10Lausanne Sport failed to score in 4 of their last 10 (league 19%).
Leaky
0/10Zürich kept no clean sheet in their last 10 (league 19%).
Always chasing
7/10Sion conceded first in 7 of 10 recent matches with goal times (league 48%).
Calculated by MyGameOdds
How it works
For each stat we show the club that stands out most, one club per stat. A fact needs at least 6 games and a result far enough from the league average to be unusual (at least one standard deviation).
How we measure →Today's Betting Tips for Super League Switzerland
Free predictions for today's Super League matches: 1X2, both teams to score, over/under and correct score.
Grasshopper0
Young Boys2Winner
X2 72%
BTTS*
Yes 60%
Correct Score
1-1 10%
Over/Under 2.5 goals
over 62%
Over/Under 3.5 goals
over 51%
Grasshopper0Young Boys2Winner
X2 72%
BTTS*
Yes 60%
Correct Score
1-1 10%
Over/Under 2.5 goals
over 62%
Over/Under 3.5 goals
over 51%
Full Time
128%
X23%
249%
Team Goals Over/Under
| <0.5 | >0.5 | <1.5 | >1.5 | |
|---|---|---|---|---|
 | 37% | 63% | 66% | 34% |
| 21% | 79% | 47% | 53% |
Goals Over/Under
| <2.5 | >2.5 | <3.5 | >3.5 | |
|---|---|---|---|---|
| FT | 38% | 62% | 49% | 51% |
Correct Score
1-1
9.7%
1-2
8.5%
0-1
7.5%
2-1
6.6%
2-2
6.4%
0-2
6.3%
Vaduz3
Basel0Winner
X2 67%
BTTS*
Yes 67%
Correct Score
1-2 10%
Over/Under 2.5 goals
over 69%
Over/Under 3.5 goals
over 55%
Vaduz3Basel0Winner
X2 67%
BTTS*
Yes 67%
Correct Score
1-2 10%
Over/Under 2.5 goals
over 69%
Over/Under 3.5 goals
over 55%
St. Gallen1
Lausanne Sport0Winner
1X 69%
BTTS*
Yes 62%
Correct Score
1-1 10%
Over/Under 2.5 goals
over 62%
Over/Under 3.5 goals
under 51%
St. Gallen1Lausanne Sport0Winner
1X 69%
BTTS*
Yes 62%
Correct Score
1-1 10%
Over/Under 2.5 goals
over 62%
Over/Under 3.5 goals
under 51%
*Probability of each predicted outcome is expressed in percentage (%)
*BTTS - Both teams to score
Super League xG: chances created and allowed
Every Super League team's chances created and allowed a game, measured with our own xG.
How to read it
each logo is a team · tap one for detailseach logo is a team · hover one for detailsSuper League average · 1.70 xG, 1.70 xGAlast 10 games eachTap a logo to see the team's numbers
↑ Fewer chances allowed (xGA a game)
More chances created (xG a game) →
Teams by box· 12
Good attack, good defence
Good attack, weak defence
Weak attack, good defence
Weak attack, weak defence
Calculated by MyGameOdds · xG: our own model
How it works
xG is our estimate of how many goals a team's chances were worth, from the shots in each match; xGA is the same for the chances it allowed. The dashed lines are the average of the teams shown. A team close to a line is about average. Teams with fewer than 5 games here aren't in the chart yet.
How we measure →Super League Results vs the Odds
Season 2026/2027 and the last 30 days
How often each result has happened in Super League this season (thick bar) and in the last 30 days (thin bar), next to what the bookmakers’ closing odds expected. The last 30 days cover fewer matches, so their normal range is wider and big swings there are still normal. This is not our prediction accuracy.
How to read it
what the closing odds expectednormal range: chance alone lands here 19 times in 20gap to the odds, in percentage pointsgap outside the normal rangethick bar: Season · thin bar: 30 days
Result · happened
◀ fewer −30◀ fewer than expected · −30 pts odds expected+30 more ▶+30 pts · more than expected ▶
Verdict
Home wins
57 matches
42.1%
Season (57) · 42.1% vs 45.3%
Season
−3.2
±12.4
30 days (18) · 38.9% vs 42.5%
30 days
−3.6
±22.1
Draws
57 matches
17.5%
Season (57) · 17.5% vs 23.0%
Season
−5.5
±10.9
30 days (18) · 11.1% vs 23.6%
30 days
−12.5
±19.6
Away wins
57 matches
40.4%
Season (57) · 40.4% vs 31.6%
Season
+8.7
±11.6
30 days (18) · 50.0% vs 33.9%
30 days
+16.1
±21.3
Over 2.5 goals
57 matches
78.9%
Season (57) · 78.9% vs 65.4%More than expected
Season
+13.5
±12.2More than expected
30 days (18) · 83.3% vs 66.3%
30 days
+17.1
±21.7
Both teams scored
57 matches
71.9%
Season (57) · 71.9% vs 65.0%
Season
+6.9
±12.3
30 days (18) · 66.7% vs 66.7%
30 days
−0.1
±21.7
Show more markets (6)Show fewer markets
Over 3.5 goals
57 matches
56.1%
Season (57) · 56.1% vs 44.5%
Season
+11.6
±12.8
30 days (18) · 61.1% vs 45.5%
30 days
+15.6
±22.8
Home side ahead at half-time
57 matches
36.8%
Season (57) · 36.8% vs 36.7%
Season
+0.2
±12.3
30 days (18) · 27.8% vs 35.4%
30 days
−7.6
±21.8
Level at half-time
57 matches
36.8%
Season (57) · 36.8% vs 36.2%
Season
+0.6
±12.5
30 days (18) · 22.2% vs 36.0%
30 days
−13.8
±22.2
Away side ahead at half-time
57 matches
26.3%
Season (57) · 26.3% vs 27.1%
Season
−0.8
±11.4
30 days (18) · 50.0% vs 28.6%More than expected
30 days
+21.4
±20.7More than expected
Home team scored 2+
57 matches
61.4%
Season (57) · 61.4% vs 55.2%
Season
+6.2
±12.6
30 days (18) · 61.1% vs 54.8%
30 days
+6.3
±22.4
Away team scored 2+
57 matches
57.9%
Season (57) · 57.9% vs 43.8%More than expected
Season
+14.1
±12.6More than expected
30 days (18) · 55.6% vs 47.2%
30 days
+8.3
±22.8
Outside the normal range this season: Over 2.5 goals 78.9% vs 65.4% expected (chance alone: about 1 in 35); Away team scored 2+ 57.9% vs 43.8% expected (chance alone: about 1 in 35).
Shows what happened, not what comes next. Closing odds from one bookmaker per match, bookmaker margin removed. Updated daily.
Show as a tableHide the table
| Result | Period | Matches | Happened | Odds expected | Gap (pts) | Normal range (± pts) | Verdict |
|---|---|---|---|---|---|---|---|
| Home wins | Season | 57 | 42.1% | 45.3% | −3.2 | ±12.4 | Normal range |
| Home wins | 30 days | 18 | 38.9% | 42.5% | −3.6 | ±22.1 | Normal range |
| Draws | Season | 57 | 17.5% | 23.0% | −5.5 | ±10.9 | Normal range |
| Draws | 30 days | 18 | 11.1% | 23.6% | −12.5 | ±19.6 | Normal range |
| Away wins | Season | 57 | 40.4% | 31.6% | +8.7 | ±11.6 | Normal range |
| Away wins | 30 days | 18 | 50.0% | 33.9% | +16.1 | ±21.3 | Normal range |
| Over 2.5 goals | Season | 57 | 78.9% | 65.4% | +13.5 | ±12.2 | More than expected |
| Over 2.5 goals | 30 days | 18 | 83.3% | 66.3% | +17.1 | ±21.7 | Normal range |
| Both teams scored | Season | 57 | 71.9% | 65.0% | +6.9 | ±12.3 | Normal range |
| Both teams scored | 30 days | 18 | 66.7% | 66.7% | −0.1 | ±21.7 | Normal range |
| Over 3.5 goals | Season | 57 | 56.1% | 44.5% | +11.6 | ±12.8 | Normal range |
| Over 3.5 goals | 30 days | 18 | 61.1% | 45.5% | +15.6 | ±22.8 | Normal range |
| Home side ahead at half-time | Season | 57 | 36.8% | 36.7% | +0.2 | ±12.3 | Normal range |
| Home side ahead at half-time | 30 days | 18 | 27.8% | 35.4% | −7.6 | ±21.8 | Normal range |
| Level at half-time | Season | 57 | 36.8% | 36.2% | +0.6 | ±12.5 | Normal range |
| Level at half-time | 30 days | 18 | 22.2% | 36.0% | −13.8 | ±22.2 | Normal range |
| Away side ahead at half-time | Season | 57 | 26.3% | 27.1% | −0.8 | ±11.4 | Normal range |
| Away side ahead at half-time | 30 days | 18 | 50.0% | 28.6% | +21.4 | ±20.7 | More than expected |
| Home team scored 2+ | Season | 57 | 61.4% | 55.2% | +6.2 | ±12.6 | Normal range |
| Home team scored 2+ | 30 days | 18 | 61.1% | 54.8% | +6.3 | ±22.4 | Normal range |
| Away team scored 2+ | Season | 57 | 57.9% | 43.8% | +14.1 | ±12.6 | More than expected |
| Away team scored 2+ | 30 days | 18 | 55.6% | 47.2% | +8.3 | ±22.8 | Normal range |
Super League luck check: the last 10 games
Super League teams taking more or fewer points than their chances usually bring, measured with our own xG.
How to read it
what their chances usually bringnormal range (±4)outside it+9.0 = 9 points more than their chances usually bringRiding their luck1
- LuganoClinical · +11 goals+9.0
Unlucky1
St. GallenWasteful · −6 goals−4.2
Points in line, but wasteful: Lausanne Sport (−4 goals), Luzern (−3), Servette (−3). Clinical: Young Boys (+8).
In line with their chances: Zürich, Sion, Basel, Grasshopper, Thun and Vaduz.
Calculated by MyGameOdds · xG: our own model
How it works
For each of a team's last 10 games, we work out how many points a team usually gets from a game with those chances (xG) for and against, add them up and compare with the points it actually got. We do the same for goals. Strong teams often get a bit more than their chances suggest, so we compare each team with sides of similar strength in this league. That way nobody is flagged just for being good.
We flag a team when the gap is 4 points or more (or 3 goals or more). If some games have no xG data, we use the ones that do.
Does it mean anything? 85% of teams 4+ points ahead of their chances got fewer points in their next 10 games, and 83% of teams 4+ points behind got more. Bookmakers already expect these gaps to even out, so it's a fan's read, not a betting edge.
How we measure →Super League last week: smash-and-grab wins and upsets
Smash-and-grab wins (the side with clearly fewer chances won) and upsets (results the closing odds gave under 20%) from the last 7 days.
How to read it
Oct 4–Oct 11 · 6 matches · odds: closing, margin removedNo smash-and-grab wins or upsets in these 6 matches.
Calculated by MyGameOdds · xG: our own model
How it works
Smash-and-grab: the winner had at least 0.8 less xG than the loser (our xG, from shots). Upset: the result the closing odds gave under 20%, with the bookmaker margin removed. Across our leagues about 6% of matches are smash-and-grab wins and about 5% are upsets.
How we measure →Super League Standings
Check the current league table, team positions, points, and form. Click to view complete standings with detailed statistics.
#TEAM | MP | PTS | W | D | L | G | GD | FORM |
|---|---|---|---|---|---|---|---|---|
1  Lugano | 10 | 28 | 9 | 1 | 0 | 31:7 | +24 | W W W D W |
2  Young Boys | 10 | 22 | 6 | 4 | 0 | 33:18 | +15 | W W D D W |
3  Sion | 10 | 19 | 6 | 1 | 3 | 23:17 | +6 | L D W W W |
4  St. Gallen | 10 | 16 | 5 | 1 | 4 | 17:19 | -2 | W W L L W |
5  Zürich | 10 | 14 | 4 | 2 | 4 | 18:22 | -4 | W D W D L |
Championship Round
Relegation Round
MP=Matches Played
PTS=Points
W=Wins
D=Draws
L=Losses
G=Goals (For:Against)
GD=Goal Difference
FORM=Last 5 Matches
About Super League
The league profile compares Super League with the 63 leagues and cups we rank over the last 12 months (rank 1 = highest). The stats that stand out pick the most unusual numbers from each team's last 10 games. The attack vs defence chart puts each team in one of four boxes: top right creates more and allows fewer chances than the league average. The luck check shows who got more or fewer points than their chances in the last 10 games, and Last week lists wins with fewer chances and results the bookmakers gave under 20%.
These statistics represent prediction accuracy based on the last 100 matches in the league. Accuracy reflects how often the model correctly predicted the outcome for each market. Our football predictions are generated using advanced AI techniques combined with historical match data, team form, player availability, tactical trends, and head-to-head records to deliver reliable forecasts. Explore our prediction results tracker for live accuracy across all completed matches, our league accuracy data for competition-level breakdowns, or prediction performance for team-level insights.
The Swiss Super League is the top professional football league in Switzerland. It consists of 10 teams and operates on a system of promotion and relegation with the Swiss Challenge League. The Swiss Super League is known for its competitive matches and scenic stadiums. FC Basel is the most successful club in Swiss Super League history.