- Sport
- Football
- Career
- 2000–2016
- Country
- 🇳🇬 Nigeria
- Peak
- 93.0
- Dominance
- 88.0
- Statistics
- 92.0
- Honours
- 88.0
- Longevity
- 86.0
GOAT Rank · 674
This ranking is led by Lionel Messi, Cristiano Ronaldo and Marta Vieira da Silva. GOAT Rank currently ranks 674 eligible Football players using verified career records across dominance, peak, longevity, honours and statistics.
Quick answer
According to GOAT Rank's current model, Lionel Messi ranks #1 on this list with a GOAT Score of 97.0.
How the GOAT Score is calculated →| # | Athlete | Sport | Country | Career | GOAT Score |
|---|---|---|---|---|---|
| 51 | Perpetua Nkwocha | Football | 🇳🇬 Nigeria | 2000–2016 | 89.2 |
| 52 | Antonio Cabrini | Football | 🇮🇹 Italy | 1974–1991 | 89.2 |
| 53 | Marcelo Vieira | Football | 🇧🇷 Brazil | 2005–active | 89.2 |
| 54 | Enzo Francescoli | Football | 🇺🇾 Uruguay | 1980–1997 | 89.1 |
| 55 | Thibaut Nicolas Marc Courtois | Football | 🇧🇪 Belgium | 2009–active | 89.1 |
| 56 | Gianluigi Buffon | Football | 🇮🇹 Italy | 1995–2023 | 89.0 |
| 57 | Michelle Akers | Football | 🇺🇸 United States | 1985–2000 | 89.0 |
| 58 | Linda Medalen | Football | 🇳🇴 Norway | 1987–2001 | 89.0 |
| 59 | Andriy Shevchenko | Football | 🇺🇦 Ukraine | 1994–2012 | 88.9 |
| 60 | Sun Wen | Football | 🇨🇳 China | 1990–2006 | 88.9 |
| 61 | Raphaël Varane | Football | 🇫🇷 France | 2010–2024 | 88.9 |
| 62 | Norberto Méndez | Football | 🇦🇷 Argentina | 1941–1958 | 88.9 |
| 63 | Paolo Maldini | Football | 🇮🇹 Italy | 1984–2009 | 88.8 |
| 64 | Andrés Iniesta | Football | 🇪🇸 Spain | 2002–2024 | 88.8 |
| 65 | Robert Lewandowski | Football | 🇵🇱 Poland | 2006–active | 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 |
| 74 | Wendie Renard | Football | 🇫🇷 France | 2006–active | 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 |
| 79 | N'Golo Kanté | Football | 🇫🇷 France | 2012–active | 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 |
| 94 | Ivan Rakitić | Football | 🇭🇷 Croatia | 2006–active | 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 |
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.