2025-2026
Live Ratings
Updated 21 Jun 2026
Tennis Power Rankings
ATP players ranked across six metrics that go beyond official rankings. Each metric captures a different dimension of player strength — from overall skill to surface dominance to recent form.
Rating Systems
ELOOverall strength, updated every match
Glicko-2Rating + confidence interval
SurfaceHard / Clay / Grass specific
FormPerformance vs expectations, last 15 matches
665
Players Ranked
2540
Top ELO (Jannik Sinner)
2653
Top Glicko-2 (Carlos Alcaraz)
Player Search
ELO Rating measures overall player strength. It updates after every match based on the result, opponent strength, tournament importance, match round, and set dominance. A player who beats a higher-rated opponent in a Grand Slam final gains more points than winning a first-round match at a 250.
Full methodology →
Glicko-2 extends ELO with two extra numbers: RD (Rating Deviation) shows confidence — lower RD means the rating is more reliable. Volatility tracks consistency — a player with low volatility performs at a steady level.
ELO Top 10
| # | Player | ELO | MP | Win% |
|---|---|---|---|---|
| 1 | Jannik Sinner | 2540 | 35 | 91.4% |
| 2 | Carlos Alcaraz | 2427 | 25 | 88.0% |
| 3 | Alexander Zverev | 2174 | 42 | 81.0% |
| 4 | Novak Djokovic | 2069 | 13 | 69.2% |
| 5 | Arthur Fils | 1970 | 26 | 76.9% |
| 6 | Casper Ruud | 1969 | 33 | 66.7% |
| 7 | Jakub Mensik | 1936 | 30 | 73.3% |
| 8 | Rafael Jodar | 1932 | 41 | 75.6% |
| 9 | Flavio Cobolli | 1914 | 35 | 62.9% |
| 10 | Daniil Medvedev | 1911 | 38 | 73.7% |
Glicko-2 Top 10
| # | Player | Rating | RD | Vol |
|---|---|---|---|---|
| 1 | Carlos Alcaraz | 2653 | 61.9 | 0.022 |
| 2 | Jannik Sinner | 2630 | 62.0 | 0.020 |
| 4 | Alexander Zverev | 2075 | 55.8 | 0.020 |
| 5 | Arthur Fils | 2009 | 78.6 | 0.020 |
| 6 | Novak Djokovic | 2004 | 74.0 | 0.022 |
| 7 | Daniil Medvedev | 1952 | 66.2 | 0.020 |
| 8 | Jakub Mensik | 1922 | 73.0 | 0.020 |
| 9 | Taylor Fritz | 1918 | 68.9 | 0.025 |
| 10 | Ben Shelton | 1914 | 64.8 | 0.020 |
| 11 | Felix Auger-Aliassime | 1911 | 60.9 | 0.020 |
Surface ratings track each player's strength separately on hard courts, clay, and grass. A player's overall ELO may be high, but their clay rating could be much lower if they rarely win on that surface. These use the same ELO algorithm but only update when a match is played on that specific surface.
Full methodology →
Hard Court
Australian Open, US Open, most ATP events| # | Player | Rating |
|---|---|---|
| 1 | Jannik Sinner | 75 |
| 2 | Carlos Alcaraz | 66 |
| 3 | Novak Djokovic | 57 |
| 4 | Daniil Medvedev | 56 |
| 5 | Alexander Zverev | 53 |
| 7 | Ben Shelton | 44 |
| 8 | Felix Auger-Aliassime | 43 |
| 9 | Arthur Fils | 43 |
| 10 | Jakub Mensik | 41 |
| 11 | Learner Tien | 40 |
Clay Court
Roland Garros, Rome, Madrid, Barcelona| # | Player | Rating |
|---|---|---|
| 1 | Carlos Alcaraz | 96 |
| 2 | Jannik Sinner | 85 |
| 3 | Alexander Zverev | 57 |
| 4 | Casper Ruud | 44 |
| 5 | Lorenzo Musetti | 43 |
| 6 | Novak Djokovic | 41 |
| 7 | Arthur Fils | 41 |
| 8 | Flavio Cobolli | 40 |
| 9 | Jakub Mensik | 40 |
| 11 | Tommy Paul | 37 |
Grass Court
Wimbledon, Queens Club, Halle| # | Player | Rating |
|---|---|---|
| 1 | Jannik Sinner | 100 |
| 2 | Carlos Alcaraz | 98 |
| 3 | Taylor Fritz | 52 |
| 4 | Novak Djokovic | 51 |
| 5 | Ben Shelton | 43 |
| 6 | Alexander Zverev | 39 |
| 7 | Alex De Minaur | 37 |
| 8 | Alexander Bublik | 33 |
| 9 | Lorenzo Musetti | 32 |
| 10 | Karen Khachanov | 30 |
Form Index measures who is outperforming expectations right now. For each of a player's last 15 matches, we compare the actual result against the win probability from our surface ELO model. Beating someone you had a 20% chance against earns far more than beating someone you were 95% to beat. Losses work the same way in reverse: losing a match you should have won is heavily penalized, while losing to a genuine threat barely dents your form. Results are weighted by tournament importance (Grand Slam > Masters > 500 > 250) and round (final > early rounds), with recent matches counting more. Inactive players see their form decay rapidly.
Full methodology →
How to read this table
ELO #
Shows overall strength rank. A player ranked #4 ELO and #1 Form is a top player on a hot streak. A player ranked #80 ELO and #3 Form is a lower-ranked player punching well above their weight.
Rising
Players ranked outside the ELO top 30 who have broken into the Form top 10 — names to watch in upcoming draws.
Example
A player with surface ELO 1700 faces an opponent rated 1900 — our model gives them roughly a 25% chance. If they win, the surplus is +0.75 (1.0 − 0.25). At a Masters 1000 semifinal, that's multiplied by the tournament weight (1.8) and round weight (1.3), giving +1.76 form points for that match. Meanwhile, the world #1 beating a qualifier they were 97% to beat earns only +0.05 form points — the win is expected, so the form reward is minimal.
Form Index Top 10
| # | Player | Form | ELO # | MP |
|---|---|---|---|---|
| 1 | Jakub Mensik | 59.59 | #7 | 30 |
| 2 | Frances Tiafoe | 59.13 | #17 | 38 |
| 3 | Alexander Zverev | 58.65 | #3 | 42 |
| 4 | Zachary Svajda Rising | 55.67 | #55 | 31 |
| 5 | Raphael Collignon Rising | 55.62 | #46 | 21 |
| 6 | Tommy Paul | 55.10 | #14 | 39 |
| 7 | Francisco Cerundolo | 54.83 | #24 | 36 |
| 8 | Alex Molcan Rising | 54.64 | #93 | 16 |
| 9 | Joao Fonseca | 53.20 | #13 | 25 |
| 10 | Flavio Cobolli | 52.33 | #9 | 35 |
Understanding the Ratings
ELO — Overall strength, updated after every match.
Learn more
Glicko-2 — Like ELO but includes a confidence interval (RD) and consistency measure (volatility).
Surface Ratings — Separate ELO for hard, clay, grass.
Learn more
Form Index — Who is outperforming expectations over their last 15 matches.
Learn more
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