League stage statistics with the probability on rank class and past results of clubs. Based on a simulation of remaining match results with club strength based on draw pots (and thus loosely based on UEFA coefficients). For more details see below. The table is sorted by the average ranking position in the simulation. Results are ordered by the opponents draw pots (away and home), and the superscript number denotes the matchday.
| Conference League 2024/25 |
pld | pnts | probability on rank | results | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1-8 | 9-16 | 17-24 | 25-36 | avg | std | 1A | 1H | 2A | 2H | 3A | 3H | ||||||
| Chelsea | Eng | 4 | 12 | 100 | 0 | 0 | 0 | 2.0 | 1.5 | W4 | W1 | 5 | 6 | W2 | W3 | ||
| Legia Warsaw | Pol | 4 | 12 | 99 | 1 | 0 | 0 | 2.6 | 1.8 | 6 | W1 | W4 | 5 | W2 | W3 | ||
| Vitória Guimarães | Por | 4 | 10 | 70 | 30 | 0 | 0 | 6.6 | 3.7 | W2 | 6 | D4 | W3 | 5 | W1 | ||
| Jagiellonia Bialystok | Pol | 4 | 10 | 68 | 32 | 0 | 0 | 6.6 | 3.5 | W1 | W3 | 5 | 6 | D4 | W2 | ||
| Rapid Wien | Aut | 4 | 10 | 67 | 33 | 0 | 0 | 6.9 | 3.7 | W1 | 6 | 5 | D4 | W3 | W2 | ||
| Fiorentina | Ita | 4 | 9 | 64 | 33 | 3 | 0 | 7.6 | 4.1 | L3 | 5 | 6 | W1 | W2 | W4 | ||
| Olimpija Ljubljana | Slo | 4 | 9 | 64 | 32 | 4 | 0 | 7.6 | 4.2 | L1 | W2 | W3 | 5 | 6 | W4 | ||
| 1.FC Heidenheim | Ger | 4 | 9 | 60 | 35 | 5 | 0 | 8.3 | 4.3 | 5 | L4 | W3 | W1 | W2 | 6 | ||
| FC Lugano | Sui | 4 | 9 | 54 | 39 | 6 | 0 | 8.9 | 4.4 | 5 | W4 | W2 | W1 | L3 | 6 | ||
| Shamrock Rovers | Irl | 4 | 8 | 34 | 48 | 18 | 0 | 11.2 | 4.9 | 6 | D1 | D4 | W3 | W2 | 5 | ||
| APOEL Nicosia | Cyp | 4 | 7 | 25 | 53 | 20 | 2 | 12.3 | 5.4 | W4 | W3 | D1 | 6 | 5 | L2 | ||
| Djurgårdens IF | Swe | 4 | 7 | 24 | 53 | 23 | 1 | 12.5 | 5.3 | D1 | 6 | W4 | L2 | 5 | W3 | ||
| Cercle Brugge | Bel | 4 | 7 | 17 | 46 | 37 | 1 | 13.8 | 5.4 | D3 | 6 | 5 | W4 | L2 | W1 | ||
| AA Gent | Bel | 4 | 6 | 18 | 49 | 26 | 6 | 14.4 | 5.7 | L1 | W2 | L4 | W3 | 6 | 5 | ||
| FK Borac Banja Luka | Bos | 4 | 7 | 10 | 43 | 41 | 6 | 16.0 | 5.6 | W2 | W4 | 5 | 6 | L3 | D1 | ||
| Pafos FC | Cyp | 4 | 6 | 9 | 39 | 39 | 13 | 17.1 | 5.9 | L4 | L2 | 6 | W3 | W1 | 5 | ||
| FC København | Den | 4 | 5 | 7 | 37 | 39 | 17 | 17.6 | 6.0 | D2 | D3 | 6 | 5 | W4 | L1 | ||
| Vikingur Reykjavik | Isl | 4 | 7 | 4 | 33 | 53 | 10 | 18.2 | 5.2 | 6 | 5 | L1 | W2 | D4 | W3 | ||
| Hearts FC | Sco | 4 | 6 | 5 | 33 | 42 | 20 | 18.6 | 5.9 | 5 | L3 | L4 | W2 | W1 | 6 | ||
| Real Betis | Esp | 4 | 4 | 0 | 27 | 48 | 25 | 20.4 | 6.1 | L1 | D2 | L4 | 6 | 5 | W3 | ||
| NK Celje | Slo | 4 | 4 | 0 | 14 | 41 | 44 | 22.9 | 6.1 | L3 | W2 | L1 | 6 | 5 | D4 | ||
| Panathinaikos | Gre | 4 | 4 | 0 | 13 | 41 | 47 | 24.0 | 5.9 | L3 | L2 | 5 | W4 | D1 | 6 | ||
| TSC Backa Topola | Srb | 4 | 4 | 0 | 10 | 42 | 47 | 24.0 | 5.8 | 5 | L2 | L1 | W3 | D4 | 6 | ||
| FK Astana | Kaz | 4 | 4 | 0 | 9 | 37 | 54 | 24.9 | 5.7 | 6 | 5 | L2 | D4 | L3 | W1 | ||
| Molde FK | Nor | 4 | 3 | 0 | 11 | 34 | 55 | 24.9 | 5.8 | L2 | L4 | 5 | 6 | L3 | W1 | ||
| The New Saints | Wal | 4 | 3 | 0 | 12 | 32 | 56 | 24.9 | 5.8 | L1 | L4 | L3 | W2 | 6 | 5 | ||
| Omonia Nicosia | Cyp | 4 | 3 | 0 | 10 | 31 | 59 | 25.3 | 5.6 | L3 | L4 | L2 | 5 | 6 | W1 | ||
| FC Sankt Gallen | Sui | 4 | 4 | 0 | 6 | 27 | 67 | 26.6 | 5.4 | 6 | L2 | L1 | 5 | W3 | D4 | ||
| FC Noah | Arm | 4 | 4 | 0 | 6 | 25 | 69 | 26.9 | 5.4 | L3 | 5 | L2 | W1 | 6 | D4 | ||
| Mladá Boleslav | Cze | 4 | 3 | 0 | 6 | 24 | 71 | 27.0 | 5.4 | 6 | W4 | L3 | L2 | L1 | 5 | ||
| LASK | Aut | 4 | 2 | 0 | 2 | 23 | 75 | 27.1 | 5.2 | 5 | D1 | L2 | D3 | L4 | 6 | ||
| HJK Helsinki | Fin | 4 | 3 | 0 | 3 | 18 | 79 | 28.5 | 5.2 | 6 | 5 | L1 | L3 | L4 | W2 | ||
| Istanbul Basaksehir | Tur | 4 | 2 | 0 | 1 | 17 | 82 | 28.7 | 5.0 | D3 | 5 | 6 | L1 | L2 | D4 | ||
| Petrocub Hîncesti | Mol | 4 | 1 | 0 | 0 | 4 | 96 | 33.3 | 3.2 | D4 | 5 | 6 | L3 | L2 | L1 | ||
| Dinamo Minsk | Bls | 4 | 0 | 0 | 0 | 1 | 99 | 33.6 | 2.9 | L3 | L4 | L2 | L1 | 6 | 5 | ||
| Larne FC | Nir | 4 | 0 | 0 | 0 | 0 | 100 | 34.4 | 2.3 | L1 | 6 | L4 | L2 | 5 | L3 | ||
The probability on rank class is calculated by 50.000 random sets of remaining match results. Clubs are divided into the same pots as used by the draw of the league stage. A weight factor of 2 for scoring goals is used between clubs of the highest and the lowest pots, while other clubs have a weight factor in between. The number of goals in a match result is determined by a pseudo zero-inflated Poisson distribution with an average of about 3 goals per match.