ATP & WTA First-Serve Return Points Won Leaders 2026

First-serve return points won is the share of points a player wins against the opponent's first serve — the hardest ball in tennis to do anything with.

Anyone can win points off a second serve; winning them off a first serve is what turns a good returner into a break-point machine. Because the baseline is so low — the tour median sits well under half — small differences here are large in practice, and the leaders are usually the players whose opponents describe them as impossible to serve through.

ATP first-serve return points won leaders 2026

Carlos Alcaraz leads the ATP with 35.3% of first-serve return points won in 2026, measured over 30 qualifying matches — the most of any qualified ATP player this season. Daniil Medvedev (33.9%) and Jannik Sinner (33.0%) are next. 89 ATP players qualify, and the median of that field is 27.6%.

ATP first-serve return points won leaders, 2026 season — top 50 of 89 qualified players, ranked by 1st return won %, with the match sample behind each figure.
#PlayerCountry1st return won %Matches
1Carlos AlcarazESP35.3%30
2Daniil Medvedev—33.9%41
3Jannik SinnerITA33.0%47
4Rafael JodarESP33.0%44
5Lorenzo MusettiITA32.4%26
6Corentin MoutetFRA32.4%20
7Francisco CerundoloARG31.5%37
8Learner TienUSA31.3%34
9Damir DzumhurBIH31.0%16
10Alex De MinaurAUS30.8%43
11Luciano DarderiITA30.4%32
12Andrey Rublev—30.4%35
13Denis ShapovalovCAN30.4%27
14Tommy PaulUSA30.2%43
15Felix Auger-AliassimeCAN30.1%41
16Thiago Agustin TiranteARG30.1%28
17Matteo ArnaldiITA30.0%19
18Arthur FeryGBR29.9%16
19Vit KoprivaCZE29.9%25
20Jakub MensikCZE29.8%41
21Ignacio BusePER29.4%23
22Jiri LeheckaCZE29.3%39
23Alexander ZverevGER29.2%63
24Flavio CobolliITA29.2%44
25Valentin VacherotMON29.1%24
26Tomas MachacCZE29.1%17
27Mariano NavoneARG29.0%21
28Botic Van De ZandschulpNED28.9%29
29Marton FucsovicsHUN28.9%21
30Arthur FilsFRA28.7%40
31Casper RuudNOR28.2%31
32Martin LandaluceESP28.2%20
33Michael ZhengUSA28.2%15
34Alejandro Davidovich FokinaESP28.1%27
35Nuno BorgesPOR28.0%28
36Alex MichelsenUSA27.9%32
37Daniel Merida AguilarESP27.9%19
38Yannick HanfmannGER27.9%22
39Hubert HurkaczPOL27.8%27
40Alexander BublikKAZ27.7%28
41Jaime FariaPOR27.7%19
42Jaume MunarESP27.7%16
43Adam WaltonAUS27.7%17
44Cameron NorrieGBR27.6%29
45Quentin HalysFRA27.6%21
46Novak DjokovicSRB27.5%21
47Karen Khachanov—27.5%37
48Tomas Martin EtcheverryARG27.5%33
49Raphael CollignonBEL27.5%15
50Alejandro TabiloCHI27.4%33

39 further qualified ATP players are outside the top 50; the full field is sortable in the ATP stat explorer on Stat Leaders.

WTA first-serve return points won leaders 2026

Iga Swiatek leads the WTA with 41.9% of first-serve return points won in 2026, measured over 44 qualifying matches — the most of any qualified WTA player this season. Coco Gauff (41.7%) and Maja Chwalinska (41.5%) are next. 80 WTA players qualify, and the median of that field is 35.7%.

WTA first-serve return points won leaders, 2026 season — top 50 of 80 qualified players, ranked by 1st return won %, with the match sample behind each figure.
#PlayerCountry1st return won %Matches
1Iga SwiatekPOL41.9%44
2Coco GauffUSA41.7%56
3Maja ChwalinskaPOL41.5%17
4Anastasia PotapovaAUT41.3%34
5Mirra Andreeva—40.6%58
6Marta KostyukUKR39.5%40
7Iva JovicUSA39.1%42
8Daria KasatkinaAUS39.1%20
9Jessica PegulaUSA39.0%63
10Elina SvitolinaUKR38.8%51
11Jasmine PaoliniITA38.4%28
12Magdalena FrechPOL38.4%32
13Amanda AnisimovaUSA38.3%33
14Cristina BucsaESP38.3%25
15Oleksandra OliynykovaUKR38.3%21
16Sara BejlekCZE38.2%22
17Yuliia StarodubtsevaUKR38.2%25
18Caty McNallyUSA38.2%23
19Victoria MbokoCAN38.1%29
20Katerina SiniakovaCZE37.9%29
21Viktorija GolubicSUI37.7%18
22Marie BouzkovaCZE37.5%28
23Jelena OstapenkoLAT37.5%31
24Zeynep SonmezTUR37.4%27
25Sorana CirsteaROU37.3%36
26McCartney KesslerUSA37.2%18
27Karolina MuchovaCZE37.1%43
28Diana Shnaider—36.9%43
29Belinda BencicSUI36.8%32
30Madison KeysUSA36.8%39
31Alexandra EalaPHI36.5%44
32Taylor TownsendUSA36.3%21
33Jessica Bouzas ManeiroESP36.3%17
34Naomi OsakaJPN36.2%37
35Ashlyn KruegerUSA35.9%18
36Maya JointAUS35.9%17
37Kamilla RakhimovaUZB35.9%21
38Hailey BaptisteUSA35.8%22
39Elena Gabriela RuseROU35.7%23
40Dayana YastremskaUKR35.7%20
41Anna Kalinskaya—35.6%40
42Aryna Sabalenka—35.5%54
43Elise MertensBEL35.4%39
44Nikola BartunkovaCZE35.2%25
45Paula BadosaESP35.2%16
46Camila OsorioCOL35.2%21
47Anna BondarHUN35.1%21
48Tereza ValentovaCZE35.1%17
49Solana SierraARG35.1%18
50Leylah FernandezCAN35.0%35

30 further qualified WTA players are outside the top 50; the full field is sortable in the WTA stat explorer on Stat Leaders.

How first-serve return points won is measured

First-serve return points won is total points won returning a first serve divided by total first serves faced, expressed as a percentage.

A player qualifies for this board with at least 15 singles matches in the 2026 pool and at least 15 of those matches carrying this statistic. The floor is half the busiest schedule on tour, capped at 15 — a flat 15 would leave the board empty until roughly April, when the pool has barely filled. The Matches column on every row is that player's own denominator, so a number taken over a thin sample is visible as one rather than hidden behind a rank. A tour section is withheld entirely below 25 qualified players.

Coverage and limits

Figures cover Grand Slam, 1000- and 500-level singles matches in 2026, on every surface. 250-level and lower-tier events are not counted, so a player's totals here run below their full-season numbers — which is also why this page ranks a per-match or per-point RATE rather than a season total. A total drawn from a partial pool would be wrong in a way a rate is not.

Recorded wherever the match carries return splits, alongside the second-serve return board. In the 2026 pool this statistic is recorded for 2,958 of the 3,040 ATP matches (97%) and 2,922 of the 3,298 WTA matches (89%).

Ranks and values on this page are computed over the same pool, so the ordering and the numbers beside it always agree. Drop Shot is not the ATP or the WTA and these are not official tour statistics: they are aggregated from our own match feed, and where a match did not report a statistic it contributes nothing to either the numerator or the denominator.