RallyIQ

ATP · Right-handed · 110 charted matches · 2019–2026

Botic Van De Zandschulp

Archetype: Grinder · Ad-court T server

Against an average opponent

Serve points won 64.5% ±2.4 raw 62.1% · tour 63.4% · 9,359 points
Return points won 39.5% ±2.5 raw 37.2% · tour 36.6% · 9,433 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 −0.09 ±0.03 better than 32% of ATP · raw −0.09
Shot selection +0.08 ±0.08 better than 62% of ATP · raw +0.09
Execution −1.07 ±0.25 better than 23% of ATP · raw −0.92
Tactical adaptability ±0.00 first serves toward what's working, set to set · 107 matches
Adaptation speed +0.12 same, every two to three service games · per 100 first serves
Long-rally execution +0.27 ±0.38 shot 9 on v own earlier rally shots · 7,226 shots · better than 94% of ATP
Points left on the table 2.53 per 100 shots vs best direction · lower than 58% 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 50,752 shots.

Shot expected value

The share of points Botic Van De Zandschulp 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 · 3,535 shots

OptionUsedWin %Tour
BH crosscourt 36% 44.4%±2.3 47.6%
BH through the middle 28% 45.3%±2.6 43.7%
BH slice crosscourt 8% 40.6%±4.5 42.5%
BH slice through the middle 7% 36.1%±4.7 35.1%
FH inside-out 6% 51.4%±5.2 51.8%
BH down the line 5% 48.0%±6.0 46.4%
FH inside-in 3% 58.7%±7.8 54.7%
FH through the middle 2% 43.9%±8.7 45.2%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 2,597 shots

OptionUsedWin %Tour
BH crosscourt 36% 49.2%±2.7 48.0%
BH through the middle 26% 48.3%±3.1 43.8%
BH slice crosscourt 12% 38.5%±4.5 42.1%
BH slice through the middle 9% 41.0%±5.2 35.1%
BH down the line 7% 40.4%±5.9 46.5%
FH inside-out 4% 61.5%±7.4 52.6%
BH slice down the line 2% 34.0%±9.1 35.8%
FH inside-in 2% 57.5%±9.6 54.3%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 2,444 shots

OptionUsedWin %Tour
FH crosscourt 24% 47.4%±3.3 52.7%
FH down the line 22% 45.5%±3.5 51.5%
FH through the middle 18% 44.6%±3.8 47.0%
BH through the middle 11% 47.3%±4.7 46.8%
BH crosscourt 9% 44.0%±5.2 49.1%
FH down the line + approach 3% 69.4%±8.1 70.5%
BH down the line 3% 49.6%±8.8 48.3%
BH slice through the middle 3% 45.7%±9.0 44.8%

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

position worth 44% to the average player · 2,249 shots

OptionUsedWin %Tour
FH crosscourt 43% 47.2%±2.6 46.6%
FH through the middle 28% 41.2%±3.2 41.5%
FH down the line 15% 41.3%±4.3 44.7%
FH slice through the middle 6% 24.9%±5.9 24.5%
FH down the line + approach 2% 69.3%±8.9 69.3%
FH slice down the line 2% 20.2%±8.9 25.6%
FH slice crosscourt 1% 28.9%±10.7 30.9%
FH drop shot down the line + approach 1% 78.4%±10.6 65.7%

Serve under pressure

Pressure predictability index +4 How much less varied Botic Van De Zandschulp's first-serve direction gets on break points. Positive means easier to read. Based on 820 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 42% 38% 72% / 73%
Body 12% 9% 63% / 63%
T 47% 53% 77% / 75%

4,638 normal · 203 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 36% 44% ▲ 72% / 73%
Body 16% 12% 58% / 63%
T 48% 44% 70% / 72%

3,839 normal · 617 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
Wide41% 63.6%±1.8 n=2,005 40% ▼
Body12% 58.4%±3.3 n=559 0% ▼
T47% 64.1%±1.6 n=2,277 60% ▲

Off equilibrium (p = 0.024): serve T more. Gap 0.8 points per 100 first serves.
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide37% 61.9%±1.9 n=1,661 37%
Body15% 54.5%±3.1 n=681 2% ▼
T47% 61.9%±1.7 n=2,114 61% ▲

Off equilibrium (p < 0.001): serve T more. Gap 1.1 points per 100 first serves.
Optimal mix: +0.9 per 100 first serves.

Exploitability 0.74 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: −0.1±1.8 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. (3,252 repeats, 5,825 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 373 36% −0.7±3.9
1stAd courtT 1,174 31% +2.7±2.2
1stAd courtWide 1,272 29% +2.2±2.1
1stDeuce courtBody 440 37% +0.1±3.7
1stDeuce courtT 1,319 30% +4.5±2.0
1stDeuce courtWide 1,345 28% +1.1±2.0
2ndAd courtBody 683 50% +0.2±3.1
2ndAd courtT 281 51% +1.5±4.7
2ndAd courtWide 709 45% −3.0±3.0
2ndDeuce courtBody 779 49% ±0.0±2.9
2ndDeuce courtT 729 49% −0.6±3.0
2ndDeuce courtWide 274 50% +2.1±4.7

Signature patterns

Recurring sequences that win more than Botic Van De Zandschulp's own baseline, ranked by edge weighted by how often they're used.

Serve → +1

  1. Wide serve (deuce court) → FH down the line + approach used 2.2% · won 72% · +5.9±5.1 vs own baseline
  2. T serve (deuce court) → FH crosscourt used 2.3% · won 61% · −5.3±5.3 vs own baseline
  3. T serve (ad court) → FH crosscourt used 4.0% · won 56% · −10.1±4.2 vs own baseline
  4. Body serve (deuce court) → FH down the line used 2.5% · won 52% · −13.4±5.3 vs own baseline
  5. Wide serve (deuce court) → FH down the line used 2.9% · won 53% · −13.2±4.9 vs own baseline

Return

  1. vs T serve (ad court) → FH through the middle, mid used 2.8% · won 52% · +13.7±5.1 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, mid used 4.0% · won 49% · +10.2±4.3 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 2.3% · won 52% · +13.2±5.6 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 3.5% · won 48% · +9.4±4.6 vs own baseline
  5. vs T serve (ad court) → FH through the middle, deep used 2.4% · won 50% · +11.3±5.5 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → BH crosscourt used 2.0% · won 50% · +4.4±4.9 vs own baseline
  2. BH crosscourt → FH crosscourt used 2.7% · won 50% · +3.8±4.3 vs own baseline
  3. FH crosscourt → FH crosscourt used 2.9% · won 49% · +3.6±4.1 vs own baseline
  4. BH through the middle → BH crosscourt used 3.1% · won 48% · +2.2±4.0 vs own baseline
  5. FH through the middle → BH through the middle used 2.4% · won 48% · +2.4±4.5 vs own baseline

Discovered sequences

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

  1. FH down the line + approach → BH slice through the middle → FH volley crosscourt used 0.1% · won 71% · +23.2±10.1 vs own baseline · +4.3 vs tour on the same sequence
  2. FH down the line + approach → BH lob through the middle → Smash crosscourt used 0.1% · won 71% · +24.0±10.2 vs own baseline · +3.5 vs tour on the same sequence
  3. FH crosscourt → FH through the middle → FH down the line + approach used 0.2% · won 64% · +17.0±8.9 vs own baseline · −0.6 vs tour on the same sequence Disrupted by Diego Schwartzman (4/6), Alex De Minaur (5/6)
  4. FH down the line + approach → BH through the middle → FH volley crosscourt used 0.1% · won 66% · +18.4±10.2 vs own baseline · +5.5 vs tour on the same sequence
  5. FH down the line → BH through the middle → FH crosscourt used 0.4% · won 57% · +10.0±6.9 vs own baseline · +5.1 vs tour on the same sequence Disrupted by Alex De Minaur (6/11), Raphael Collignon (8/11)
  6. Wide serve → FH slice through the middle return, mid → FH down the line + approach used 0.1% · won 68% · +20.9±10.7 vs own baseline · +13.1 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 slice to their forehand · return +1+2.5123
FH slice to the middle · return +1+2.0130
FH to the middle · return +1+2.0561
BH to the middle · return +1+1.4751
BH slice to the middle · return +1+1.3320

Most exposed to

FH to the middle · return +1−2.3524
FH slice to the middle · rally−1.8181
FH to the middle · serve +1−1.2722
BH to the middle · return−1.11,565
BH to the middle · return +1−1.0599

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Miomir Kecmanovic +0.98, Rafael Nadal +0.97, Roberto Bautista Agut +0.69, Daniil Medvedev +0.66, Casper Ruud +0.63

Favourable matchups

Miomir Kecmanovic +0.90, Fabian Marozsan +0.86, Pedro Martinez +0.76, Roberto Carballes Baena +0.74, Roberto Bautista Agut +0.67

Active players who are best at the shot in the top weakness: Brandon Nakashima, Diego Schwartzman, Alejandro Davidovich Fokina, Daniil Medvedev, Sebastian Baez

Tactical fingerprint

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

Through the middle30%
T serves · ad47%
Deep returns34%
Avg rally length4.3
Drop shots / shot2.2%
1st serve in63%
Backhand slice26%
Run-around forehands22%
T serves · deuce47%
Points at net13%
Forehand share54%
Unforced errors / shot9.8%
Point-ending shots22.6%
Wide serves · deuce41%
Serve & volley2%
Chipped returns11%
FH down the line27%
BH down the line11%
Wide serves · ad37%

Plays most like

  1. Miomir Kecmanovic 2019–2026 plan v
  2. Jesper De Jong 2021–2026 plan v
  3. Mackenzie Mcdonald 2015–2025 plan v
  4. Emil Ruusuvuori 2021–2024 plan v
  5. Nuno Borges 2021–2026 plan v
  6. Zhizhen Zhang 2019–2026 plan v
  7. Zizou Bergs 2021–2026 plan v
  8. Jordan Thompson 2016–2025 plan v

Closest from another era

  1. Guillermo Canas 2001–2007
  2. Andy Roddick 2001–2012
  3. Mario Ancic 2002–2008

Charted matches