- Sport
- Football
- Career
- 1984–2009
- Country
- 🇮🇹 Italy
- Peak
- 87.0
- Dominance
- 87.0
- Statistics
- 84.0
- Honours
- 89.0
- Longevity
- 96.0
GOAT Rank · 469
This ranking is led by Bobby Moore, Pelé and Giacinto Facchetti. GOAT Rank currently ranks 469 eligible Football players using verified career records across dominance, peak, longevity, honours and statistics.
Quick answer
According to GOAT Rank's current model, Bobby Moore ranks #1 on this list with a GOAT Score of 94.6.
How the GOAT Score is calculated →| # | Athlete | Sport | Country | Career | GOAT Score |
|---|---|---|---|---|---|
| 63 | Paolo Maldini | Football | 🇮🇹 Italy | 1984–2009 | 88.8 |
| 64 | Andrés Iniesta | Football | 🇪🇸 Spain | 2002–2024 | 88.8 |
| 66 | Peter Schmeichel | Football | 🇩🇰 Denmark | 1981–2003 | 88.8 |
| 67 | Stanley Matthews | Football | 🏴 England | 1932–1965 | 88.8 |
| 68 | Delio Onnis | Football | 🇦🇷 Argentina | 1971–1986 | 88.8 |
| 69 | Camille Abily | Football | 🇫🇷 France | 1999–2018 | 88.8 |
| 70 | Renate Lingor | Football | 🇩🇪 Germany | 1991–2008 | 88.8 |
| 71 | Conny Pohlers | Football | 🇩🇪 Germany | 1996–2013 | 88.8 |
| 72 | Andreas Möller | Football | 🇩🇪 Germany | 1986–2004 | 88.8 |
| 73 | Xavi Hernández | Football | 🇪🇸 Spain | 1998–2019 | 88.7 |
| 75 | Kelly Smith | Football | 🏴 England | 1994–2017 | 88.7 |
| 76 | Sepp Maier | Football | 🇩🇪 Germany | 1962–1980 | 88.6 |
| 77 | Briana Scurry | Football | 🇺🇸 United States | 1994–2008 | 88.6 |
| 78 | Carolina Morace | Football | 🇮🇹 Italy | 1978–1998 | 88.5 |
| 80 | Lothar Matthäus | Football | 🇩🇪 Germany | 1979–2000 | 88.4 |
| 81 | Peter Shilton | Football | 🏴 England | 1966–1997 | 88.4 |
| 82 | David Villa | Football | 🇪🇸 Spain | 2000–2020 | 88.4 |
| 83 | Marcel Desailly | Football | 🇫🇷 France | 1986–2006 | 88.4 |
| 84 | Leonardo Bonucci | Football | 🇮🇹 Italy | 2005–2024 | 88.4 |
| 85 | Diego Forlán | Football | 🇺🇾 Uruguay | 1997–2019 | 88.4 |
| 86 | Tobin Heath | Football | 🇺🇸 United States | 2008–2022 | 88.4 |
| 87 | Eusébio | Football | 🇵🇹 Portugal | 1960–1979 | 88.2 |
| 88 | Dani Alves | Football | 🇧🇷 Brazil | 2001–2023 | 88.2 |
| 89 | Petr Čech | Football | 🇨🇿 Czech Republic | 1999–2019 | 88.2 |
| 90 | Formiga | Football | 🇧🇷 Brazil | 1993–2022 | 88.2 |
| 91 | Pia Sundhage | Football | 🇸🇪 Sweden | 1975–1996 | 88.2 |
| 92 | Bernd Schuster | Football | 🇩🇪 Germany | 1979–1997 | 88.2 |
| 93 | David Josué Jiménez Silva | Football | 🇪🇸 Spain | 2005–2023 | 88.2 |
| 95 | Michel Platini | Football | 🇫🇷 France | 1972–1987 | 88.1 |
| 96 | Oleg Blokhin | Football | 🇺🇦 Ukraine | 1969–1990 | 88.1 |
| 97 | Dida | Football | 🇧🇷 Brazil | 1992–2015 | 88.0 |
| 98 | Ariane Hingst | Football | 🇩🇪 Germany | 1994–2011 | 88.0 |
| 99 | Luís Figo | Football | 🇵🇹 Portugal | 1989–2009 | 87.9 |
| 100 | José Martínez Sánchez | Football | 🇪🇸 Spain | 1964–1982 | 87.9 |
| 101 | Rinat Dasayev | Football | 🇷🇺 Russia | 1976–1990 | 87.9 |
| 102 | Abby Wambach | Football | 🇺🇸 United States | 2001–2015 | 87.7 |
| 106 | Marinette Pichon | Football | 🇫🇷 France | 1993–2010 | 87.7 |
| 108 | Paco Gento | Football | 🇪🇸 Spain | 1952–1971 | 87.6 |
| 109 | Ray Clemence | Football | 🏴 England | 1965–1988 | 87.6 |
| 110 | Fabio Cannavaro | Football | 🇮🇹 Italy | 1992–2011 | 87.6 |
| 112 | Oscar Ruggeri | Football | 🇦🇷 Argentina | 1980–1997 | 87.6 |
| 113 | Henrik Larsson | Football | 🇸🇪 Sweden | 1992–2013 | 87.5 |
| 115 | Bettina Wiegmann | Football | 🇩🇪 Germany | 1989–2003 | 87.5 |
| 117 | Martina Voss-Tecklenburg | Football | 🇩🇪 Germany | 1984–1999 | 87.5 |
| 118 | Lauren Holiday | Football | 🇺🇸 United States | 2007–2015 | 87.5 |
| 119 | Wesley Sneijder | Football | 🇳🇱 Netherlands | 2003–2019 | 87.5 |
| 120 | Anja Mittag | Football | 🇩🇪 Germany | 2002–2019 | 87.4 |
| 121 | Giuseppe Bergomi | Football | 🇮🇹 Italy | 1980–1999 | 87.4 |
| 123 | Zlatan Ibrahimović | Football | 🇸🇪 Sweden | 1999–2023 | 87.3 |
| 126 | Hanna Ljungberg | Football | 🇸🇪 Sweden | 1996–2009 | 87.3 |
Sport lists use the raw In-Sport GOAT Score. Cross-sport lists use the official competition-depth adjustment. No scores are recalculated for this page.
Read the full methodologyFive verified components are weighted consistently: dominance, peak, longevity, honours and statistics.
According to GOAT Rank's current data model, only verified athletes with sufficient career history, metrics, honours and independent sources are eligible. Rank and score are read live.