- Sport
- Football
- Career
- 1994–2014
- Country
- 🇫🇷 France
- Peak
- 90.0
- Dominance
- 84.0
- Statistics
- 88.0
- Honours
- 86.0
- Longevity
- 82.0
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 |
|---|---|---|---|---|---|
| 195 | Thierry Henry | Football | 🇫🇷 France | 1994–2014 | 85.8 |
| 196 | Giorgio Chiellini | Football | 🇮🇹 Italy | 2000–2023 | 85.8 |
| 197 | Alan Hansen | Football | 🏴 Scotland | 1973–1991 | 85.8 |
| 198 | Phil Neal | Football | 🏴 England | 1968–1989 | 85.8 |
| 199 | Hope Solo | Football | 🇺🇸 United States | 2000–2016 | 85.8 |
| 200 | Therese Sjögran | Football | 🇸🇪 Sweden | 1997–2015 | 85.8 |
| 201 | Walter Zenga | Football | 🇮🇹 Italy | 1979–1999 | 85.8 |
| 203 | Fernando Torres | Football | 🇪🇸 Spain | 2001–2019 | 85.7 |
| 204 | Doris Fitschen | Football | 🇩🇪 Germany | 1986–2001 | 85.7 |
| 206 | Giampiero Boniperti | Football | 🇮🇹 Italy | 1946–1961 | 85.6 |
| 207 | Neville Southall | Football | 🏴 Wales | 1980–2002 | 85.6 |
| 208 | Denis Law | Football | 🏴 Scotland | 1956–1974 | 85.6 |
| 210 | Robert Prosinečki | Football | 🇭🇷 Croatia | 1986–2004 | 85.6 |
| 211 | Sonny Anderson | Football | 🇧🇷 Brazil | 1988–2006 | 85.6 |
| 212 | Igor Belanov | Football | 🇺🇦 Ukraine | 1979–1995 | 85.6 |
| 215 | Bebeto | Football | 🇧🇷 Brazil | 1983–2002 | 85.5 |
| 216 | Bixente Lizarazu | Football | 🇫🇷 France | 1988–2006 | 85.5 |
| 217 | Kurt Hamrin | Football | 🇸🇪 Sweden | 1952–1971 | 85.5 |
| 218 | Marco Materazzi | Football | 🇮🇹 Italy | 1993–2011 | 85.5 |
| 221 | Jill Scott | Football | 🏴 England | 2006–2022 | 85.5 |
| 222 | Lisa De Vanna | Football | 🇦🇺 Australia | 2004–2021 | 85.5 |
| 223 | Svenja Huth | Football | 🇩🇪 Germany | 2008–2024 | 85.5 |
| 224 | Franco Baresi | Football | 🇮🇹 Italy | 1977–1997 | 85.4 |
| 225 | Roberto Carlos | Football | 🇧🇷 Brazil | 1991–2015 | 85.4 |
| 226 | Gianni Rivera | Football | 🇮🇹 Italy | 1959–1979 | 85.4 |
| 227 | Kevin Keegan | Football | 🏴 England | 1968–1984 | 85.4 |
| 228 | Filippo Inzaghi | Football | 🇮🇹 Italy | 1991–2012 | 85.4 |
| 230 | Melanie Behringer | Football | 🇩🇪 Germany | 2005–2017 | 85.4 |
| 232 | Giancarlo Antognoni | Football | 🇮🇹 Italy | 1971–1989 | 85.4 |
| 233 | Raúl González | Football | 🇪🇸 Spain | 1994–2015 | 85.3 |
| 234 | Graeme Souness | Football | 🏴 Scotland | 1970–1991 | 85.3 |
| 235 | Gordon Banks | Football | 🏴 England | 1958–1978 | 85.3 |
| 236 | Pavel Nedvěd | Football | 🇨🇿 Czech Republic | 1991–2009 | 85.3 |
| 239 | Amy Rodriguez | Football | 🇺🇸 United States | 2005–2022 | 85.3 |
| 242 | Fatmire Alushi | Football | 🇩🇪 Germany | 2004–2017 | 85.3 |
| 244 | Claudio Pizarro | Football | 🇵🇪 Peru | 1996–2020 | 85.3 |
| 245 | Francesco Totti | Football | 🇮🇹 Italy | 1992–2017 | 85.2 |
| 246 | Carlos Bianchi | Football | 🇦🇷 Argentina | 1967–1984 | 85.2 |
| 248 | Rudi Völler | Football | 🇩🇪 Germany | 1980–1996 | 85.2 |
| 251 | Andrea Pirlo | Football | 🇮🇹 Italy | 1995–2017 | 85.1 |
| 253 | Lilian Thuram | Football | 🇫🇷 France | 1991–2008 | 85.1 |
| 254 | Jupp Heynckes | Football | 🇩🇪 Germany | 1964–1978 | 85.1 |
| 255 | Dominique Rocheteau | Football | 🇫🇷 France | 1971–1989 | 85.1 |
| 256 | Gro Espeseth | Football | 🇳🇴 Norway | 1990–2001 | 85.1 |
| 257 | Andreas Brehme | Football | 🇩🇪 Germany | 1979–1998 | 85.1 |
| 258 | Alessandro Nesta | Football | 🇮🇹 Italy | 1993–2014 | 85.0 |
| 259 | Paolo Rossi | Football | 🇮🇹 Italy | 1973–1987 | 85.0 |
| 260 | Dejan Savićević | Football | 🇲🇪 Montenegro | 1983–2001 | 85.0 |
| 261 | Gunnar Gren | Football | 🇸🇪 Sweden | 1938–1960 | 85.0 |
| 263 | Charmaine Hooper | Football | 🇨🇦 Canada | 1986–2006 | 85.0 |
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.