RallyIQ

ATP · Right-handed · 74 charted matches · 2003–2019

David Ferrer

Archetype: Grinder · Ad-court T server

Against an average opponent

Serve points won 63.7% ±2.6 raw 58.3% · tour 63.4% · 6,055 points
Return points won 39.8% ±2.7 raw 36.7% · tour 36.6% · 5,829 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 −0.03 ±0.06 better than 48% of ATP · raw −0.04
Shot selection +0.44 ±0.08 better than 89% of ATP · raw +0.43
Execution +0.21 ±0.29 better than 76% of ATP · raw −0.06
Tactical adaptability +0.20 first serves toward what's working, set to set · 73 matches
Adaptation speed +0.09 same, every two to three service games · per 100 first serves
Long-rally execution +0.20 ±0.42 shot 9 on v own earlier rally shots · 6,505 shots · better than 91% of ATP
Points left on the table 2.21 per 100 shots vs best direction · lower than 92% 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 36,228 shots.

Shot expected value

The share of points David Ferrer 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 · 3,120 shots

OptionUsedWin %Tour
BH crosscourt 43% 46.8%±2.2 47.6%
BH through the middle 24% 42.6%±3.0 43.7%
FH inside-out 9% 50.8%±4.7 51.8%
BH down the line 9% 49.4%±4.7 46.4%
FH inside-in 6% 57.0%±5.9 54.7%
BH slice through the middle 3% 29.6%±7.6 35.1%
FH through the middle 2% 43.8%±8.3 45.2%
BH slice crosscourt 2% 37.5%±9.1 42.5%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 2,362 shots

OptionUsedWin %Tour
BH crosscourt 46% 46.9%±2.5 48.0%
BH through the middle 21% 41.2%±3.5 43.8%
BH down the line 10% 48.4%±5.1 46.5%
FH inside-out 6% 48.0%±6.3 52.6%
FH inside-in 5% 56.7%±7.1 54.3%
BH slice through the middle 4% 31.8%±7.4 35.1%
BH slice crosscourt 3% 41.1%±8.5 42.1%
FH through the middle 2% 50.4%±10.8 46.1%

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

position worth 44% to the average player · 1,870 shots

OptionUsedWin %Tour
FH crosscourt 50% 44.6%±2.7 46.6%
FH through the middle 23% 41.3%±3.8 41.5%
FH down the line 20% 47.8%±4.2 44.7%
FH slice through the middle 3% 25.2%±8.0 24.5%
FH slice crosscourt 2% 27.5%±10.6 30.9%
FH down the line + approach 1% 71.8%±11.3 69.3%
FH slice down the line 1% 22.3%±10.7 25.6%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 1,783 shots

OptionUsedWin %Tour
FH down the line 29% 51.8%±3.5 51.5%
FH crosscourt 27% 49.2%±3.7 52.7%
FH through the middle 15% 48.6%±4.9 47.0%
BH through the middle 11% 48.1%±5.6 46.8%
BH crosscourt 10% 43.7%±5.9 49.1%
BH down the line 3% 47.6%±9.4 48.3%
FH down the line + approach 3% 74.1%±8.4 70.5%
FH crosscourt + approach 1% 64.4%±11.7 69.9%

Serve under pressure

Pressure predictability index +1 How much less varied David Ferrer's first-serve direction gets on break points. Positive means easier to read. Based on 651 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 44% 51% 67% / 73%
Body 20% 17% 61% / 63%
T 36% 33% 67% / 75%

2,973 normal · 172 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 38% 41% 67% / 73%
Body 17% 17% 57% / 63%
T 45% 42% 63% / 72%

2,395 normal · 479 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
Wide44% 61.3%±2.1 n=1,390 57% ▲
Body20% 56.5%±3.2 n=624 7% ▼
T36% 59.9%±2.4 n=1,131 36%

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

Ad court

1st serveUsagePoints wonOptimal
Wide38% 59.1%±2.4 n=1,102 51% ▲
Body17% 53.0%±3.6 n=498 4% ▼
T44% 55.6%±2.3 n=1,274 45%

Off equilibrium (p = 0.024): serve wide more. Gap 2.6 points per 100 first serves.
Optimal mix: +0.5 per 100 first serves.

Exploitability 0.47 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: −1.3±2.0 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. (1,878 repeats, 3,993 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 200 38% +1.3±5.3
1stAd courtT 641 26% −2.3±2.8
1stAd courtWide 831 29% +1.6±2.5
1stDeuce courtBody 227 40% +3.8±5.0
1stDeuce courtT 782 27% +1.8±2.6
1stDeuce courtWide 876 26% −0.8±2.4
2ndAd courtBody 319 50% +0.1±4.4
2ndAd courtT 146 53% +3.4±6.2
2ndAd courtWide 622 49% +0.2±3.2
2ndDeuce courtBody 436 50% +0.5±3.8
2ndDeuce courtT 450 50% +0.7±3.8
2ndDeuce courtWide 264 50% +2.4±4.8

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH crosscourt used 2.2% · won 60% · −1.1±6.5 vs own baseline
  2. T serve (ad court) → FH crosscourt used 3.1% · won 57% · −3.4±5.7 vs own baseline
  3. Body serve (ad court) → FH crosscourt used 2.4% · won 57% · −4.3±6.3 vs own baseline
  4. T serve (ad court) → FH down the line used 3.2% · won 55% · −5.3±5.6 vs own baseline
  5. Wide serve (ad court) → FH crosscourt used 2.4% · won 55% · −6.1±6.3 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, short used 3.8% · won 50% · +12.3±5.6 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, mid used 5.8% · won 46% · +7.7±4.6 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 2.5% · won 47% · +9.6±6.8 vs own baseline
  4. vs T serve (deuce court) → BH through the middle, deep used 2.4% · won 47% · +9.6±6.8 vs own baseline
  5. vs T serve (deuce court) → BH crosscourt, mid used 2.2% · won 48% · +9.8±7.1 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 2.1% · won 53% · +5.9±5.2 vs own baseline
  2. BH crosscourt → FH inside-in used 1.5% · won 54% · +6.7±6.1 vs own baseline
  3. FH crosscourt → BH crosscourt used 5.1% · won 50% · +2.9±3.4 vs own baseline
  4. BH crosscourt → FH crosscourt used 5.3% · won 50% · +2.7±3.4 vs own baseline
  5. BH down the line → FH down the line used 1.0% · won 52% · +5.1±7.0 vs own baseline

Discovered sequences

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

  1. T serve → FH through the middle return, mid → FH crosscourt used 0.2% · won 63% · +14.8±9.2 vs own baseline · +15.0 vs tour on the same sequence · −20.2 v lefties Disrupted by Rafael Nadal (7/14), Andy Murray (7/11)
  2. FH crosscourt → FH through the middle → FH down the line + approach used 0.1% · won 66% · +18.1±10.7 vs own baseline · +9.3 vs tour on the same sequence Disrupted by Novak Djokovic (3/6)
  3. BH crosscourt → BH crosscourt → BH down the line used 0.4% · won 57% · +9.4±7.5 vs own baseline · +12.2 vs tour on the same sequence Disrupted by Novak Djokovic (13/27), Roger Federer (7/12)
  4. FH down the line → BH slice crosscourt → FH inside-in used 0.3% · won 60% · +12.1±9.0 vs own baseline · +5.8 vs tour on the same sequence Disrupted by Marcos Baghdatis (4/9), Novak Djokovic (5/8)
  5. FH crosscourt → FH through the middle → FH down the line used 0.6% · won 55% · +7.1±6.5 vs own baseline · +3.3 vs tour on the same sequence Disrupted by Bernard Tomic (1/6), Roger Federer (5/9)
  6. Wide serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 58% · +9.9±8.9 vs own baseline · +3.3 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 to their forehand · return+4.4310
FH slice to the middle · rally+1.9142
BH to their forehand · return +1+1.7270
FH to their forehand · return +1+1.3531
BH to their forehand · rally+1.3919

Most exposed to

FH volley to their forehand · rally−6.4165
FH volley to their backhand · rally−3.9130
FH to their backhand · return−3.6586
FH to their backhand · rally−2.22,809
FH to the middle · return−2.11,083

Active players who are best at the shot in the top weakness: Stefanos Tsitsipas, Alex De Minaur, Andy Murray, Carlos Alcaraz, Jannik Sinner

Tactical fingerprint

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

Avg rally length5.1
Run-around forehands30%
Forehand share59%
T serves · ad44%
1st serve in62%
Wide serves · deuce44%
Deep returns28%
FH down the line30%
Through the middle23%
Serve & volley0%
Chipped returns10%
Drop shots / shot0.9%
Points at net8%
Backhand slice10%
Unforced errors / shot8.1%
BH down the line15%
Point-ending shots17.4%
T serves · deuce36%
Wide serves · ad38%

Plays most like

  1. Tomas Martin Etcheverry 2022–2026 plan v
  2. Miomir Kecmanovic 2019–2026 plan v
  3. Carlos Berlocq 2011–2019 plan v
  4. Tommy Paul 2016–2026 plan v
  5. Diego Schwartzman 2015–2025 plan v
  6. Pablo Carreno Busta 2015–2026 plan v
  7. Guillermo Canas 2001–2007 plan v
  8. Ilya Ivashka 2018–2023 plan v

Closest from another era

  1. Aaron Krickstein 1989–1995
  2. Jim Courier 1989–1999
  3. Michael Chang 1989–1998

Charted matches