Champions League Player Predictability
How predictable is each Champions League player? Before every match our models publish a full probability distribution for how many shots and shots on target each player will take. This board compares those distributions with what actually happened across the 2023-24 campaign, for every player who started at least 8 matches, a full league phase. The score measures how much closer our distributions get than a baseline that knows only the player's position and his expected minutes. Higher means easier to call in advance.
| # | Player | Role | Club | Starts | Score | Shots skill | On target skill | Scorer skill | Shots / match |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Stanislav Lobotka | Midfielder | Napoli | 8 | +69.3 ±5.4 | +58.3% | +80.2% | +67.2% | 0.12 |
| 2 | Igor Zubeldia | Midfielder | Real Sociedad | 8 | +66.1 ±5.4 | +43.0% | +89.2% | +76.3% | 0.50 |
| 3 | Ferland Mendy | Defender | Real Madrid | 9 | +56.8 ±7.4 | +50.1% | +63.6% | +18.7% | 0.00 |
| 4 | Koke | Midfielder | Atleti | 8 | +55.8 ±7.4 | +41.1% | +70.6% | +65.1% | 0.38 |
| 5 | Kevin Diks | Defender | Copenhagen | 8 | +42.2 ±7.0 | +7.1% | +77.4% | +92.2% | 0.25 |
| 6 | Erling Haaland | Forward | Man City | 9 | +41.0 ±11.7 | +40.6% | +41.4% | +25.1% | 4.78 |
| 7 | Axel Witsel | Midfielder | Atleti | 10 | +26.9 ±15.0 | +47.6% | +6.3% | +51.8% | 0.30 |
| 8 | Kylian Mbappé | Forward | Paris | 12 | +26.4 ±7.9 | +33.2% | +19.6% | +18.1% | 4.25 |
| 9 | Leroy Sané | Midfielder | Bayern München | 11 | +25.3 ±18.7 | +25.5% | +25.1% | -22.5% | 2.27 |
| 10 | Rodrygo | Forward | Real Madrid | 12 | +19.9 ±10.1 | +20.0% | +19.7% | +5.3% | 2.92 |
| 11 | Martin Zubimendi | Midfielder | Real Sociedad | 8 | +19.1 ±26.9 | +12.9% | +25.2% | +52.7% | 0.88 |
| 12 | Álvaro Morata | Forward | Atleti | 8 | +18.9 ±4.8 | +12.7% | +25.0% | +24.2% | 2.75 |
| 13 | Jude Bellingham | Midfielder | Real Madrid | 11 | +18.4 ±10.5 | +28.1% | +8.7% | +19.9% | 2.09 |
| 14 | Marquinhos | Defender | Paris | 10 | +14.4 ±12.5 | +7.6% | +21.3% | -118.7% | 0.30 |
| 15 | João Cancelo | Defender | Barcelona | 8 | +13.2 ±9.1 | +11.1% | +15.3% | +2.6% | 1.25 |
| 16 | Jamal Musiala | Midfielder | Bayern München | 11 | +10.2 ±8.7 | +20.9% | -0.4% | +3.9% | 2.18 |
| 17 | Giovanni Di Lorenzo | Defender | Napoli | 8 | +9.7 ±9.8 | +20.3% | -0.9% | -0.9% | 1.25 |
| 18 | Achraf Hakimi | Defender | Paris | 11 | +9.6 ±4.7 | +19.3% | -0.0% | +5.3% | 1.55 |
| 19 | Antoine Griezmann | Forward | Atleti | 10 | +9.4 ±10.3 | +7.1% | +11.7% | +19.5% | 2.20 |
| 20 | Johan Bakayoko | Forward | PSV | 8 | +8.7 ±10.0 | +17.3% | +0.2% | +10.9% | 3.00 |
| 21 | Luis Alberto | Midfielder | Lazio | 8 | +7.1 ±9.6 | +3.8% | +10.4% | +39.1% | 1.88 |
| 22 | Julian Brandt | Midfielder | B. Dortmund | 9 | +6.8 ±5.1 | +9.3% | +4.3% | +4.0% | 1.78 |
| 23 | William Saliba | Defender | Arsenal | 10 | +6.7 ±13.3 | +0.5% | +12.9% | -84.5% | 0.30 |
| 24 | Declan Rice | Midfielder | Arsenal | 9 | +6.2 ±9.9 | -1.5% | +14.0% | -64.5% | 0.56 |
| 25 | Matteo Politano | Forward | Napoli | 8 | +5.3 ±7.2 | +8.5% | +2.1% | +15.7% | 1.62 |
| 26 | Harry Kane | Forward | Bayern München | 11 | +4.8 ±23.9 | +1.5% | +8.1% | +9.6% | 2.91 |
| 27 | Bukayo Saka | Forward | Arsenal | 9 | +3.5 ±8.1 | +0.4% | +6.7% | +3.8% | 1.56 |
| 28 | Ousmane Dembélé | Forward | Paris | 10 | +3.3 ±8.0 | +3.8% | +2.9% | -0.4% | 3.20 |
| 29 | Vinícius Júnior | Forward | Real Madrid | 10 | +2.2 ±6.9 | +1.8% | +2.5% | +17.6% | 3.10 |
| 30 | Vitinha | Midfielder | Paris | 10 | +1.9 ±3.7 | +3.3% | +0.5% | -6.3% | 1.90 |
| 31 | Martin Ødegaard | Midfielder | Arsenal | 8 | +1.8 ±8.4 | +7.7% | -4.0% | +4.7% | 2.12 |
| 32 | Warren Zaïre-Emery | Midfielder | Paris | 10 | +1.4 ±15.7 | +2.6% | +0.2% | -4.9% | 0.70 |
| 33 | Nahuel Molina | Defender | Atleti | 10 | +1.2 ±10.2 | +6.5% | -4.1% | +52.9% | 0.40 |
| 34 | Rúben Dias | Defender | Man City | 9 | +0.7 ±21.4 | +4.8% | -3.4% | -168.1% | 0.67 |
| 35 | Antonio Rüdiger | Defender | Real Madrid | 11 | +0.6 ±9.7 | +2.9% | -1.7% | -135.5% | 0.55 |
| 36 | Nico Schlotterbeck | Defender | B. Dortmund | 11 | +0.3 ±8.6 | +4.0% | -3.4% | +68.8% | 0.36 |
| 37 | Niclas Füllkrug | Forward | B. Dortmund | 11 | -0.1 ±3.3 | -0.8% | +0.6% | +5.1% | 2.64 |
| 38 | Rodri | Midfielder | Man City | 8 | -0.7 ±9.5 | +0.3% | -1.7% | +5.9% | 1.50 |
| 39 | Ronald Araújo | Defender | Barcelona | 8 | -1.2 ±6.1 | +5.1% | -7.4% | +69.7% | 0.50 |
| 40 | Mats Hummels | Defender | B. Dortmund | 13 | -1.3 ±11.1 | -2.9% | +0.3% | -3.6% | 0.77 |
| 41 | Konrad Laimer | Midfielder | Bayern München | 8 | -1.9 ±16.2 | -5.7% | +2.0% | +44.2% | 0.25 |
| 42 | Karim Adeyemi | Forward | B. Dortmund | 8 | -2.1 ±6.9 | -8.2% | +3.9% | -1.5% | 1.88 |
| 43 | Toni Kroos | Midfielder | Real Madrid | 10 | -2.2 ±7.7 | -1.3% | -3.2% | +31.4% | 0.60 |
| 44 | Alan Varela | Midfielder | Porto | 8 | -2.6 ±10.6 | +2.4% | -7.6% | +35.2% | 1.00 |
| 45 | Jack Grealish | Midfielder | Man City | 8 | -2.6 ±10.3 | -2.6% | -2.7% | -45.6% | 1.62 |
| 46 | Marcel Sabitzer | Midfielder | B. Dortmund | 11 | -2.9 ±7.2 | -7.2% | +1.4% | +5.0% | 1.09 |
| 47 | Federico Valverde | Midfielder | Real Madrid | 12 | -3.0 ±9.0 | +3.5% | -9.5% | -9.3% | 1.75 |
| 48 | Gabriel | Defender | Arsenal | 10 | -3.5 ±16.4 | -0.9% | -6.1% | -11.1% | 0.70 |
| 49 | Emre Can | Defender | B. Dortmund | 11 | -4.2 ±7.9 | -5.8% | -2.7% | -0.6% | 0.45 |
| 50 | Nacho | Defender | Real Madrid | 11 | -4.2 ±4.9 | -3.8% | -4.6% | +4.0% | 0.55 |
| 51 | Dani Carvajal | Defender | Real Madrid | 9 | -4.3 ±6.2 | -4.5% | -4.1% | -3.7% | 0.89 |
| 52 | Julian Ryerson | Defender | B. Dortmund | 9 | -4.6 ±8.5 | -3.2% | -6.0% | +63.2% | 0.44 |
| 53 | Eduardo Camavinga | Midfielder | Real Madrid | 9 | -5.8 ±9.9 | +0.5% | -12.2% | +40.5% | 1.11 |
| 54 | İlkay Gündoğan | Midfielder | Barcelona | 9 | -6.7 ±9.8 | -6.7% | -6.7% | +13.6% | 1.56 |
| 55 | Robert Lewandowski | Forward | Barcelona | 9 | -7.6 ±27.2 | -5.6% | -9.5% | -0.3% | 2.44 |
| 56 | Jules Koundé | Defender | Barcelona | 8 | -8.3 ±32.3 | -2.1% | -14.4% | +3.9% | 0.25 |
| 57 | Mario Hermoso | Defender | Atleti | 9 | -9.4 ±5.9 | -14.2% | -4.7% | +0.0% | 0.44 |
| 58 | Jordan Teze | Defender | PSV | 8 | -10.4 ±8.5 | -10.3% | -10.5% | -4.0% | 0.50 |
| 59 | Denis Vavro | Defender | Copenhagen | 8 | -12.2 ±5.3 | -23.6% | -0.9% | +38.1% | 0.88 |
| 60 | Lucas Hernández | Defender | Paris | 9 | -14.1 ±14.3 | -23.8% | -4.3% | -1.6% | 0.22 |
| 61 | Khvicha Kvaratskhelia | Forward | Napoli | 8 | -17.0 ±25.7 | -18.2% | -15.9% | +14.2% | 2.12 |
| 62 | Mohamed Elyounoussi | Forward | Copenhagen | 8 | -21.9 ±16.2 | -25.9% | -17.8% | -15.7% | 2.00 |
| 63 | Rodrigo De Paul | Midfielder | Atleti | 8 | -23.5 ±16.7 | -16.0% | -31.0% | -6.6% | 0.75 |
| 64 | Noussair Mazraoui | Defender | Bayern München | 8 | -29.2 ±35.9 | -21.5% | -37.0% | -140.8% | 0.62 |
| 65 | Joshua Kimmich | Midfielder | Bayern München | 12 | -30.1 ±22.0 | -27.6% | -32.7% | -12.4% | 0.75 |
| 66 | Kai Havertz | Midfielder | Arsenal | 9 | -30.3 ±35.0 | -27.6% | -33.0% | +2.4% | 1.22 |
| 67 | Leon Goretzka | Midfielder | Bayern München | 9 | -91.3 ±37.9 | -89.8% | -92.9% | -155.1% | 0.89 |
| 68 | Alex Meret | Goalkeeper | Napoli | 8 | saves only | - | - | +79.0% | 4.0 saves |
| 69 | Andriy Lunin | Goalkeeper | Real Madrid | 8 | saves only | - | - | +29.8% | 4.8 saves |
| 70 | David Raya | Goalkeeper | Arsenal | 8 | saves only | - | - | +24.3% | 1.5 saves |
| 71 | Diogo Costa | Goalkeeper | Porto | 8 | saves only | - | - | +79.3% | 2.4 saves |
| 72 | Gianluigi Donnarumma | Goalkeeper | Paris | 12 | saves only | - | - | +85.9% | 3.1 saves |
| 73 | Gregor Kobel | Goalkeeper | B. Dortmund | 12 | saves only | - | - | +76.4% | 3.8 saves |
| 74 | Ivan Provedel | Goalkeeper | Lazio | 8 | saves only | - | - | -1.1% | 2.8 saves |
| 75 | Jan Oblak | Goalkeeper | Atleti | 10 | saves only | - | - | +87.5% | 4.0 saves |
| 76 | Kamil Grabara | Goalkeeper | Copenhagen | 8 | saves only | - | - | +91.1% | 3.8 saves |
| 77 | Manuel Neuer | Goalkeeper | Bayern München | 9 | saves only | - | - | +76.2% | 2.4 saves |
| 78 | Marc-André ter Stegen | Goalkeeper | Barcelona | 8 | saves only | - | - | +87.0% | 2.8 saves |
| 79 | Walter Benítez | Goalkeeper | PSV | 8 | saves only | - | - | +84.8% | 2.5 saves |
| 80 | Álex Remiro | Goalkeeper | Real Sociedad | 8 | saves only | - | - | +80.9% | 2.5 saves |
Starts = matches started. Skill = how much lower our CRPS is than the baseline's on the same matches, in percent, so positive means the model wins. The smaller number next to the score is one standard error. Goalkeepers take no shots, so they carry no score and are measured on saves on their own pages. Tap any column header to sort.
How the score works, and how to read it
A high score does not mean a better player. It means a player whose output our models can call match by match. The score compares two forecasters on the matches a player started: our model, which publishes a full probability distribution for his shots and shots on target once the team sheet is out, and a baseline that knows only his position and how long he is expected to be on the pitch. We measure both with CRPS, a standard score for probabilistic forecasts, and report how much better the model is, in percent. So the score really answers one question: how much does knowing WHO he is add on top of knowing WHAT he plays.
Read the score with the standard error next to it. The skill is a ratio of two small numbers, and it is much noisier for players who barely shoot: across this holdout the spread of the score is roughly three times wider for players under 0.2 shots a match than for those above 1.2. That is why the shots-per-match column sits on this board. A defender at the top of the table is usually a defender our model correctly expects to shoot almost never, which is a real win, but it is not the same measurement as a striker at the top.
The anytime-scorer skill is published alongside and deliberately kept out of the score. On a base rate of a few percent, a single season is too thin to separate players. Everything here is season level and aggregate: these pages report the accuracy of our own forecasts, not a match-by-match statistics feed.
Club title odds and the full league-phase board live on the Champions League simulations page, and how the models work on the methodology page.