Kybunpark · Zürcher Strasse 464
FC St. Gallen 18790–0Scheduled
FC LuganoFC St. Gallen 1879 x FC Lugano: Probabilities, Odds, and AI Analysis
For FC St. Gallen 1879 vs. FC Lugano, the model Predora Market Median estimates a 40.8% probability of a win for FC St. Gallen 1879, 24.7% for a draw, and 34.5% for a win for FC Lugano.
View analysis: market vs. statistics
The bookmaker consensus and statistical relative strength both favor St. Gallen. Relative strength compares the teams using the supplied statistics; it is not a win probability.
With the draw excluded and home and away shares rescaled to total 100%, the bookmaker split is 54.5% for St. Gallen and 45.5% for Lugano. Relative strength is 57.1% and 42.9%, respectively. These are different measures. The draw accounts for 24.7% of the full three-outcome market.
Bookmaker prices range from 2.2 to 2.3 for St. Gallen, 3.5 to 3.8 for a draw, and 2.6 to 2.75 for Lugano. Against the overall statistical leaning, Lugano has more season points per game: 2.83 to 1.58 across 12 games each.
Market 1x2
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
2.45 / 40.8% Formula: 1 ÷ Estimated probability
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
2.30 / 43.5% Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
-2.7 p.p.Formula: Probability − Implied probability (Book)
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
-6.2%Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Available with Predora Pro
Create free account Already have an account? Sign in
Probability Models
| Model | FC St. Gallen 1879 | Draw | FC Lugano |
|---|---|---|---|
| Predora Market Median | 40.8% / 2.45 | 24.7% / 4.04 | 34.5% / 2.90 |
Market Double Chance
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.33 / 75.3% Formula: 1 ÷ Estimated probability
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.50 / 66.7% Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
+8.6 p.p.Formula: Probability − Implied probability (Book)
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
+12.9%Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Available with Predora Pro
Create free account Already have an account? Sign in
Probability Models
| Model | 1X | X2 | 12 |
|---|---|---|---|
| Predora Market Median | 65.5% / 1.53 | 59.2% / 1.69 | 75.3% / 1.33 |
AI Analysis
Market and data alignedAvailable with a free account
Create free account Already have an account? Sign in
Team Comparison
Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| H2H: W/D/L (last 5) Results from the last 5 head-to-head games between the teams. Example: 3–1–1 = 3 wins, 1 draw, 1 loss for the team on the left. | 3-1-1 | 1-1-3 |
| H2H: win % (home vs. away) (last 5) Head-to-head win percentage (last 5), split by home and away team. Example: the home team won 3 of 5 = 60%. | 60 % | 20 % |
Outcome Strength (Season)
Game context (Home/Away)
| Factor | FC St. Gallen 1879 Home | FC Lugano Away |
|---|---|---|
| PPG (home/away) Average points per game in the relevant context (home team at home, away team away). Example: 6 points in 4 games = 1.5 points/game.Points per game in context (home team at home / away team away). | 1.67 pts/game | 3 pts/game |
| Win % (home/away) Win percentage in the relevant context (home for the home team, away for the away team). Example: 2 wins in 4 games = 50%. | 50 % | 100 % |
| Draw % (home/away) Draw percentage in the home/away context. Example: 1 draw in 4 games = 25%. | 16.7 % | 0 % |
| Goal difference (home/away) Average goal difference in context: goals scored minus goals conceded per game. Example: scored 6 and conceded 4 in 4 games → (6−4)/4 = +0.5. | -0.17 goals/game | 2.2 goals/game |
| xG difference (home/away) Average xG difference in context: xG for minus xG against per game. Example: 1.4 − 1.1 = +0.3 xG/game. | 0.72 xG/game | 0.33 xG/game |
Season baseline (Overall) Temp
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| PPG (overall) Average points per game this season (home + away). Example: 12 points in 8 games = 1.5 points/game. | 1.58 pts/game | 2.83 pts/game |
| Win % (overall) Win percentage this season (home + away). Example: 4 wins in 8 games = 50%. | 50 % | 91.7 % |
| Draw % (overall) Draw percentage this season (home + away). Example: 2 draws in 8 games = 25%. | 8.3 % | 8.3 % |
| Goal difference (overall) Average goal difference this season: (goals scored − goals conceded) / games. Example: 10−6 in 8 games → +0.5 per game. | -0.25 goals/game | 2.17 goals/game |
| xG difference (overall) Average xG difference this season: xG for minus xG against per game. Example: 1.6 − 1.2 = +0.4 xG/game. | 0.6 xG/game | 0.37 xG/game |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| Form (last 5): W/D/L Results from the last 5 games: wins, draws, and losses. Example: 2–2–1 = 2 wins, 2 draws, 1 loss. | 3-0-2 | 5-0-0 |
| PPG (last 5) Average points from the last 5 games. Example: 7 points in 5 games = 1.4 points/game. | 1.8 pts/game | 3 pts/game |
Market Over 2.5 goals
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.57 / 63.6% Formula: 1 ÷ Estimated probability
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.48 / 67.8% Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
-4.2 p.p.Formula: Probability − Implied probability (Book)
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
-6.1%Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Available with Predora Pro
Create free account Already have an account? Sign in
Probability Models
| Model | Over | Under |
|---|---|---|
| Predora Market Median | 63.6% / 1.57 | 36.4% / 2.75 |
Team Comparison
Predictions (AI) Prev
| Factor | Game |
|---|---|
| Potential: average goals Pregame estimate of total goals, based on historical data and AI, combining both teams. Example: 2.8 goals/game ≈ an estimate of 3 goals. | 3.85 goals |
| Over 2.5 potential Pregame estimated probability of 3+ goals, based on historical data and AI. Example: 52% estimates Over 2.5 in about 52 of 100 similar games.Pregame probability of over 2.5 goals | 92 % |
| Under 2.5 potential Pregame estimated probability of under 2.5 goals, based on historical data and AI. Example: 55% estimates Under 2.5 in about 55 of 100 similar games.Pregame probability of under 2.5 goals | 9 % |
Season (baseline)
Game context (Home/Away)
| Factor | FC St. Gallen 1879 Home | FC Lugano Away |
|---|---|---|
| Goals scored (home/away) Average goals scored per game in the relevant context (home team at home, away team away). Example: 6 goals in 4 games = 1.5 goals/game. | 1.67 goals/game | 3.2 goals/game |
| Goals conceded (home/away) Average goals conceded per game in the home/away context. Example: 5 goals conceded in 4 games = 1.25 goals/game. | 1.83 goals/game | 1 goals/game |
| xG for (home/away) Average chance quality created per game (xG) in the home/away context. Example: 1.6 xG per game means the team’s shots add up to 1.6 expected goals per game on average. | 2.02 xG/game | 1.76 xG/game |
Overall (Season) Temp
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| Over 2.5 (season) Percentage of season games with over 2.5 goals. Example: 7 of 13 games = 54%.Season games with Over 2.5 % | 67 % | 92 % |
| Goals scored (overall) Average goals scored per game this season (home + away). Example: 20 goals in 13 games = 1.54 goals/game. | 1.58 goals/game | 3 goals/game |
| Shots on target / game Average shots on target per game this season (home + away). Example: 48 shots on target in 10 games = 4.8 per game. | 6.33 shots on target/game | 6.17 shots on target/game |
| Goals conceded (overall) Average goals conceded per game this season (home + away). Example: 15 goals in 13 games = 1.15 goals/game. | 1.83 goals/game | 0.83 goals/game |
League (baseline) League
| Factor | League |
|---|---|
| League average goals Average goals per game in the league this season (competition baseline). Example: 2.68 goals/game ≈ 2–3 goals per game.Average league goals per game (baseline) | 3.76 goals/game |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| Goals scored (last 5) Average goals scored per game in the last 5 games (recent form). Example: 9 goals in 5 games = 1.8 goals/game. | 1.4 goals/game | 3.4 goals/game |
| Goals conceded (last 5) Average goals conceded per game in the last 5 games (recent form). Example: 6 goals conceded in 5 games = 1.2 goals/game. | 1.6 goals/game | 0.8 goals/game |
Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| H2H: Over 2.5 % (last 5) Percentage of the last 5 head-to-head games with over 2.5 goals. Example: 3 of 5 games = 60%.Recent H2H games with Over 2.5 | 60 % | 60 % |
Market Both Teams to Score
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.52 / 65.6% Formula: 1 ÷ Estimated probability
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.44 / 69.3% Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
-3.6 p.p.Formula: Probability − Implied probability (Book)
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
-5.2%Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Available with Predora Pro
Create free account Already have an account? Sign in
Probability Models
| Model | Yes | No |
|---|---|---|
| Predora Market Median | 65.6% / 1.52 | 34.4% / 2.91 |
Team Comparison
Predictions (AI) Prev
| Factor | Game |
|---|---|
| Potential: BTTS (%) Pregame estimated probability of both teams scoring, based on historical data and AI. Example: 58% estimates that about 58 of 100 similar games would have goals from both teams. | 74 % |
| Over 2.5 potential Pregame estimated probability of 3+ goals, based on historical data and AI. Example: 52% estimates Over 2.5 in about 52 of 100 similar games.Pregame probability of over 2.5 goals | 92 % |
Season baseline (Season)
Indicators associated with more BTTS outcomes
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| BTTS (season) % Percentage of season games in which both teams scored. Example: 7 of 12 games = 58%. | 58 % | 67 % |
| Games scoring 1+ goal % (season) Percentage of season games in which the team scored at least 1 goal. Example: scored in 10 of 12 games = 83%. | 75 % | 100 % |
| Games conceding 1+ goal % (season) Percentage of season games in which the team conceded at least 1 goal. Example: conceded in 8 of 12 games = 67%. | 83 % | 67 % |
Indicators associated with fewer BTTS outcomes
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| Clean sheet % (season) Percentage of clean sheets, a factor associated with fewer Both Teams to Score outcomes. Example: 4 clean sheets in 12 games = 33%. | 17 % | 33 % |
| Failed to score % (season) Percentage of games without scoring, a factor associated with fewer Both Teams to Score outcomes. Example: no goals scored in 3 of 12 games = 25%. | 25 % | 0 % |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| Games scoring 1+ goal % (last 5) Percentage of the last 5 games in which the team scored at least 1 goal. Example: scored in 4 of 5 = 80%. | 80 % | 100 % |
| Games conceding 1+ goal % (last 5) Percentage of the last 5 games in which the team conceded at least 1 goal. Example: conceded in 3 of 5 = 60%. | 80 % | 60 % |
Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5
| Factor | Head-to-head (H2H) |
|---|---|
| H2H: BTTS % (last 5) Percentage of the last 5 head-to-head games in which both teams scored. Example: 3 of 5 games = 60%. | 80 % |
Market Over 9.5 corners
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.75 / 57.2% Formula: 1 ÷ Estimated probability
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.57 / 63.7% Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
-6.5 p.p.Formula: Probability − Implied probability (Book)
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
-10.2%Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Available with Predora Pro
Create free account Already have an account? Sign in
Probability Models
| Model | Over | Under |
|---|---|---|
| Predora Market Median | 57.2% / 1.75 | 42.8% / 2.34 |
Team Comparison
Predictions (AI) Prev
| Factor | Game |
|---|---|
| Potential: average corners Pregame estimate of total corners, based on historical data and AI. Example: 10.2 corners ≈ an estimate of 10 corners. | 10.27 corners |
| Potential Over 9.5 corners (%) Pregame estimated probability of 10+ corners, based on historical data and AI. Example: 58% estimates Over 9.5 in about 58 of 100 similar games. | 35 % |
Season (baseline)
Game context (Home/Away)
| Factor | FC St. Gallen 1879 Home | FC Lugano Away |
|---|---|---|
| Corners for (home/away) Average corners won per game in context (home team at home, away team away). Example: 24 corners in 6 games = 4.0 per game. | 5.67 corners/game | 4.6 corners/game |
| Total corners (home/away) Average total corners per game in context (both teams combined). Example: 60 corners in 6 games = 10.0 per game. | 10.34 corners/game | 8.4 corners/game |
Overall (Season) Temp
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| Corners for (overall) Average corners won per game this season (home + away). Example: 40 in 10 games = 4.0 per game. | 6.58 corners/game | 5.67 corners/game |
| Total corners (overall) Average total corners per game this season (home + away). Example: 105 in 10 games = 10.5 per game. | 11.16 corners/game | 10 corners/game |
League (baseline) League
| Factor | League |
|---|---|
| League average corners (corners/game) Average corners per game in the league this season (competition baseline). Example: 9.3 corners/game ≈ 9–10 corners per game. | 10.67 corners/game |
Cards
Team Comparison
Predictions (AI) Prev
| Factor | Game |
|---|---|
| Potential: average cards Pregame estimate of total cards, based on historical data and AI. Example: 4.8 cards ≈ an estimate of 5 cards. | 4.43 cards/game |
Season baseline (Season) Temp
| Factor | FC St. Gallen 1879 | FC Lugano |
|---|---|---|
| Total cards (average) Average cards per game this season (home + away). Example: 18 cards in 6 games = 3.0 cards/game. | 1.75 cards/game | 2.5 cards/game |
| Over 4.5 cards % Probability (or observed percentage, depending on the source) of 5+ cards in the game. Example: 60% estimates Over 4.5 in about 60 of 100 similar games. | 33 % | 42 % |
League (baseline) League
| Factor | League |
|---|---|
| League average cards Average cards per game in the league this season (competition baseline). Example: 4.3 cards/game ≈ 4–5 cards per game. | 4.83 cards/game |
FC Vaduz
FC Sion
FC Luzern
Young Boys Bern
Grasshopper Club Zurich
Lausanne-Sport
FC Thun
FC Basel 1893