RallyIQ

ATP · Left-handed · 425 charted matches · 2003–2024

Rafael Nadal

Archetype: Avoids the wide serve · Ad-court slider

Against an average opponent

Serve points won 68.6% ±2.0 raw 66.0% · tour 63.4% · 34,627 points
Return points won 42.8% ±2.3 raw 40.1% · tour 36.6% · 36,179 points

Serve and return points won, refitted against every opponent at once so a record built on weak or strong opposition is put on the same scale. Career, all surfaces, with a 90% margin. Raw is the plain share of points won.

Value per 100 shots

Direction choice +0.02 ±0.03 better than 62% of ATP · raw +0.02
Shot selection +0.38 ±0.05 better than 85% of ATP · raw +0.37
Execution +1.32 ±0.10 better than 99% of ATP · raw +1.22
Tactical adaptability +0.26 first serves toward what's working, set to set · 420 matches
Adaptation speed +0.24 same, every two to three service games · per 100 first serves
Long-rally execution −0.19 ±0.23 shot 9 on v own earlier rally shots · 29,225 shots · better than 53% of ATP
Points left on the table 2.66 per 100 shots vs best direction · lower than 43% of ATP

Points gained per 100 shots compared with an average tour player in the same position, adjusted for the strength of the opponents faced, with a 90% margin (shots clustered by match). Raw is before the opponent adjustment. Built on 194,980 shots.

Shot expected value

The share of points Rafael Nadal goes on to win after each option in the positions they face most often, shrunk toward tour average when the sample is small. Showing the 8 most-used options; teal marks the best one with at least 30 shots.

Rally, shots 5–8: drive to your backhand side

position worth 46% to the average player · 15,689 shots

OptionUsedWin %Tour
BH crosscourt 32% 52.4%±1.2 47.6%
BH through the middle 20% 47.8%±1.5 43.7%
BH down the line 17% 52.5%±1.6 46.4%
FH inside-in 6% 58.3%±2.6 54.7%
BH slice through the middle 6% 42.6%±2.7 35.1%
BH slice down the line 6% 45.4%±2.7 37.1%
FH inside-out 5% 59.2%±2.8 51.8%
BH slice crosscourt 3% 49.3%±3.5 42.5%

Rally, shots 5–8: drive to your forehand side

position worth 44% to the average player · 11,067 shots

OptionUsedWin %Tour
FH crosscourt 58% 51.8%±1.0 46.6%
FH down the line 20% 53.3%±1.8 44.7%
FH through the middle 14% 45.1%±2.1 41.5%
FH slice through the middle 2% 24.5%±4.4 24.5%
FH slice crosscourt 2% 38.4%±5.0 30.9%
FH down the line + approach 1% 71.3%±7.5 69.3%
FH slice down the line 1% 20.1%±7.0 25.6%
BH inside-out 1% 39.4%±9.0 45.4%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 10,250 shots

OptionUsedWin %Tour
FH crosscourt 35% 60.6%±1.3 52.7%
FH down the line 19% 58.7%±1.8 51.5%
FH through the middle 13% 52.3%±2.3 47.0%
BH through the middle 10% 49.9%±2.6 46.8%
BH crosscourt 9% 55.1%±2.6 49.1%
BH down the line 6% 53.3%±3.3 48.3%
BH slice down the line 2% 49.4%±5.6 45.6%
BH slice through the middle 2% 44.4%±5.6 44.8%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 10,161 shots

OptionUsedWin %Tour
BH crosscourt 33% 53.1%±1.4 48.0%
BH through the middle 17% 48.4%±1.9 43.8%
BH down the line 17% 51.2%±2.0 46.5%
BH slice through the middle 7% 42.8%±3.0 35.1%
BH slice down the line 7% 41.2%±3.0 35.8%
FH inside-in 5% 55.6%±3.4 54.3%
BH slice crosscourt 4% 46.6%±3.9 42.1%
FH inside-out 4% 57.8%±4.0 52.6%

Serve under pressure

Pressure predictability index +2 How much less varied Rafael Nadal's first-serve direction gets on break points. Positive means easier to read. Based on 2585 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 30% 45% ▲ 75% / 73%
Body 18% 15% 64% / 63%
T 52% 40% ▼ 69% / 75%

17,501 normal · 575 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 54% 56% 71% / 73%
Body 18% 15% 67% / 63%
T 28% 29% 75% / 72%

14,419 normal · 2,010 break-point 1st serves

Is the serve mix in equilibrium?

Game theory says a well-mixed server wins equally often with every direction they use. If one direction wins more, it's underused and points are being left behind. This is the minimax test Walker and Wooders ran on Wimbledon finals, applied to every charted first serve. Win rates include faults. "Optimal" allows for returners reading a habit. No measurable response (−0.05 ± 0.15 points per 100 serves for every 10 points of habitual usage), measured from ATP servers whose mix drifted between matches. Shifts stay within the range servers' habits actually vary, the only range that response was measured over.

Deuce court

1st serveUsagePoints wonOptimal
Wide31% 66.6%±1.0 n=5,514 44% ▲
Body18% 61.8%±1.4 n=3,310 5% ▼
T51% 65.4%±0.8 n=9,252 51%

Off equilibrium (p < 0.001): serve wide more. Gap 1.5 points per 100 first serves.
Optimal mix: +0.8 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide54% 67.4%±0.8 n=8,870 60% ▲
Body18% 65.3%±1.4 n=2,934 5% ▼
T28% 67.1%±1.1 n=4,625 35% ▲

Consistent with an optimal mix (p = 0.08).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.57 points per 100 first serves What the optimal mix would win over the current one, both courts. More exploitable than 100% of ATP servers. Tested on matches they weren't fitted on, ATP mixes picked this way win 0.33 per 100 first serves on average.

Repeating the previous direction to the same court: +0.3±0.9 points per 100 against switching. Negative means returners read repeats. Tour-wide, repeating costs women about 0.4 points per 100 and costs men nothing, so men's returners don't measurably anticipate direction. (13,551 repeats, 20,108 switches.)

Return by serve direction

Return points won against each serve direction, compared with the tour average.

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 1,317 43% +5.9±2.2
1stAd courtT 4,940 34% +5.8±1.1
1stAd courtWide 4,303 29% +1.3±1.1
1stDeuce courtBody 1,139 42% +5.2±2.4
1stDeuce courtT 4,512 26% +0.8±1.1
1stDeuce courtWide 6,378 34% +6.7±1.0
2ndAd courtBody 2,099 55% +5.3±1.8
2ndAd courtT 2,855 54% +4.3±1.5
2ndAd courtWide 1,754 51% +2.7±1.9
2ndDeuce courtBody 1,545 54% +5.4±2.1
2ndDeuce courtT 870 54% +4.3±2.7
2ndDeuce courtWide 4,318 53% +4.8±1.2

Signature patterns

Recurring sequences that win more than Rafael Nadal's own baseline, ranked by edge weighted by how often they're used.

Serve → +1

  1. Body serve (ad court) → FH crosscourt used 2.9% · won 62% · −6.1±2.5 vs own baseline
  2. Wide serve (ad court) → FH down the line used 5.5% · won 63% · −4.8±1.8 vs own baseline
  3. Body serve (ad court) → FH down the line used 2.5% · won 60% · −7.6±2.7 vs own baseline
  4. T serve (deuce court) → FH down the line used 3.4% · won 61% · −6.7±2.3 vs own baseline
  5. Body serve (deuce court) → FH crosscourt used 3.3% · won 60% · −7.5±2.4 vs own baseline

Return

  1. vs wide serve (deuce court) → BH crosscourt, mid used 3.7% · won 54% · +12.1±2.3 vs own baseline
  2. vs wide serve (deuce court) → BH through the middle, deep used 2.2% · won 55% · +12.4±3.0 vs own baseline
  3. vs wide serve (ad court) → FH crosscourt, mid used 2.6% · won 53% · +10.3±2.8 vs own baseline
  4. vs wide serve (deuce court) → BH crosscourt, short used 2.7% · won 52% · +9.5±2.7 vs own baseline
  5. vs T serve (deuce court) → FH through the middle, mid used 2.1% · won 52% · +9.4±3.1 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 5.2% · won 59% · +6.5±1.5 vs own baseline
  2. FH down the line → FH crosscourt used 1.4% · won 62% · +9.9±2.9 vs own baseline
  3. BH crosscourt → FH crosscourt used 2.7% · won 58% · +5.4±2.1 vs own baseline
  4. FH crosscourt → FH crosscourt used 6.1% · won 56% · +3.3±1.4 vs own baseline
  5. FH inside-in → FH crosscourt used 1.2% · won 59% · +6.8±3.1 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Rafael Nadal wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.

  1. FH crosscourt → BH through the middle → FH crosscourt used 1.5% · won 61% · +7.6±2.0 vs own baseline · +8.8 vs tour on the same sequence Disrupted by Mackenzie Mcdonald (2/6), Alexandr Dolgopolov (2/6)
  2. Wide serve → BH through the middle return, mid → FH crosscourt used 0.4% · won 67% · +13.1±3.7 vs own baseline · +9.0 vs tour on the same sequence Disrupted by David Ferrer (5/12), Nikolay Davydenko (4/9)
  3. BH crosscourt → FH through the middle → FH crosscourt used 0.6% · won 62% · +8.2±3.1 vs own baseline · +9.3 vs tour on the same sequence Disrupted by Mikhail Youzhny (3/9), Diego Schwartzman (5/14)
  4. FH crosscourt → BH slice through the middle → FH down the line used 0.2% · won 68% · +13.6±4.8 vs own baseline · +9.2 vs tour on the same sequence Disrupted by Stan Wawrinka (4/9), David Ferrer (5/9)
  5. FH down the line → FH through the middle → FH crosscourt used 0.6% · won 62% · +8.0±3.1 vs own baseline · +7.2 vs tour on the same sequence Disrupted by Guillermo Coria (2/6), Karen Khachanov (3/8)
  6. FH crosscourt → BH slice through the middle → FH crosscourt used 0.3% · won 66% · +12.4±4.7 vs own baseline · +9.9 vs tour on the same sequence

Strengths and vulnerabilities

Value per 100 shots compared with the average player hitting (strengths) or facing (vulnerabilities) the same shot. Only shot types seen at least 120 times.

Hurts opponents most with

BH volley to their forehand · rally+11.2412
FH volley to their backhand · rally+9.1419
FH volley to the middle · rally+8.0189
FH drop shot to their backhand · rally+7.1134
Smash to the middle · rally+7.1199

Most exposed to

BH volley to their forehand · rally−7.1795
FH volley to their backhand · serve +1−5.6346
FH volley to their backhand · rally−3.5753
BH to their forehand · return−3.13,264
BH slice to their forehand · return−2.9516

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Jack Draper +1.47, Miomir Kecmanovic +1.20, Pedro Martinez +1.05, Yoshihito Nishioka +1.04, Casper Ruud +1.03

Favourable matchups

Miomir Kecmanovic +3.10, Pedro Martinez +3.05, Alexander Shevchenko +3.01, Fabian Marozsan +3.01, Arthur Rinderknech +2.96

Active players who are best at the shot in the top weakness: Casper Ruud, Carlos Alcaraz, Alex De Minaur, Dominic Thiem, Stefanos Tsitsipas

Tactical fingerprint

Each bar shows how far a style trait is from the ATP average, in standard deviations.

1st serve in69%
Forehand share59%
Avg rally length4.7
T serves · deuce51%
BH down the line25%
Wide serves · ad54%
Run-around forehands21%
Backhand slice20%
Serve & volley1%
Drop shots / shot1.0%
Deep returns24%
Chipped returns11%
Points at net8%
Point-ending shots19.3%
FH down the line26%
Through the middle20%
Unforced errors / shot6.6%
T serves · ad28%
Wide serves · deuce31%

Plays most like

  1. Albert Ramos 2014–2025 plan v
  2. Cameron Norrie 2015–2026 plan v
  3. Fernando Verdasco 2005–2022 plan v
  4. Yoshihito Nishioka 2015–2025 plan v
  5. Juan Martin Del Potro 2007–2022 plan v
  6. Nikolay Davydenko 2002–2014 plan v
  7. Juan Carlos Ferrero 2000–2009 plan v
  8. Mariano Navone 2022–2026 plan v

Closest from another era

  1. Jimmy Connors 1974–1991
  2. Marcelo Rios 1995–2001
  3. Sergi Bruguera 1990–1997

Charted matches