RallyIQ

ATP · Right-handed · 34 charted matches · 2021–2026

Jesper De Jong

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 64.5% ±2.6 raw 63.5% · tour 63.4% · 2,897 points
Return points won 37.8% ±2.7 raw 37.2% · tour 36.6% · 2,879 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 −0.14 ±0.06 better than 21% of ATP · raw −0.13
Shot selection +0.30 ±0.12 better than 80% of ATP · raw +0.32
Execution −0.72 ±0.35 better than 36% of ATP · raw −0.44
Tactical adaptability +0.10 first serves toward what's working, set to set · 34 matches
Adaptation speed +0.15 same, every two to three service games · per 100 first serves
Points left on the table 2.79 per 100 shots vs best direction · lower than 32% 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 14,982 shots.

Shot expected value

The share of points Jesper De Jong 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 · 1,024 shots

OptionUsedWin %Tour
BH crosscourt 31% 42.2%±4.4 47.6%
BH through the middle 27% 43.0%±4.7 43.7%
FH inside-out 10% 54.5%±7.5 51.8%
BH slice crosscourt 7% 35.8%±8.4 42.5%
BH down the line 6% 43.0%±9.0 46.4%
BH slice through the middle 6% 33.4%±8.8 35.1%
BH drop shot down the line 5% 45.4%±10.0 47.2%
FH inside-in 3% 50.8%±11.3 54.7%

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

position worth 44% to the average player · 732 shots

OptionUsedWin %Tour
FH crosscourt 40% 41.1%±4.6 46.6%
FH through the middle 30% 43.7%±5.3 41.5%
FH down the line 21% 39.5%±6.1 44.7%
FH slice through the middle 3% 26.5%±10.8 24.5%
FH slice down the line 2% 26.1%±12.2 25.6%
FH drop shot crosscourt 2% 61.4%±13.5 52.5%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 655 shots

OptionUsedWin %Tour
BH crosscourt 32% 40.4%±5.4 48.0%
BH through the middle 22% 43.6%±6.3 43.8%
BH slice crosscourt 13% 43.6%±8.1 42.1%
BH down the line 9% 34.1%±8.9 46.5%
BH slice through the middle 8% 28.2%±8.8 35.1%
BH drop shot down the line 4% 50.1%±12.0 47.8%
BH slice down the line 3% 34.5%±12.2 35.8%
FH inside-out 3% 43.5%±13.2 52.6%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 619 shots

OptionUsedWin %Tour
FH down the line 25% 43.9%±6.2 51.5%
FH crosscourt 19% 50.8%±7.1 52.7%
FH through the middle 15% 48.6%±7.7 47.0%
BH through the middle 14% 41.6%±7.8 46.8%
BH crosscourt 9% 41.9%±9.3 49.1%
FH down the line + approach 6% 68.6%±10.1 70.5%
BH down the line 3% 45.0%±13.5 48.3%
BH slice through the middle 2% 42.3%±14.1 44.8%

Serve under pressure

Pressure predictability index +4 How much less varied Jesper De Jong's first-serve direction gets on break points. Positive means easier to read. Based on 260 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 44% 44% 73% / 73%
Body 7% 8% 54% / 63%
T 48% 48% 81% / 75%

1,443 normal · 71 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 44% 43% 73% / 73%
Body 9% 6% 56% / 63%
T 46% 51% 71% / 72%

1,170 normal · 189 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% 62.9%±3.0 n=672 39% ▼
Body7% 54.3%±6.9 n=113 0% ▼
T48% 67.1%±2.8 n=729 61% ▲

Off equilibrium (p = 0.003): serve T more. Gap 2.8 points per 100 first serves.
Optimal mix: +0.8 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide44% 63.6%±3.2 n=601 57% ▲
Body9% 57.0%±6.7 n=118 0% ▼
T47% 62.8%±3.1 n=640 43% ▼

Consistent with an optimal mix (p = 0.23).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.73 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: +3.7±3.5 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. (1,160 repeats, 1,645 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 105 42% +5.3±7.0
1stAd courtT 294 36% +8.2±4.4
1stAd courtWide 408 27% −0.7±3.5
1stDeuce courtBody 134 36% −0.7±6.2
1stDeuce courtT 438 25% −0.4±3.3
1stDeuce courtWide 376 28% +0.9±3.7
2ndAd courtBody 193 51% +1.2±5.5
2ndAd courtT 94 47% −1.9±7.4
2ndAd courtWide 268 51% +2.5±4.8
2ndDeuce courtBody 206 48% −0.8±5.4
2ndDeuce courtT 228 50% +0.3±5.1
2ndDeuce courtWide 107 46% −2.5±7.0

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH crosscourt used 2.1% · won 57% · −9.2±8.9 vs own baseline
  2. Wide serve (deuce court) → FH down the line used 2.1% · won 57% · −9.7±9.0 vs own baseline
  3. Body serve (deuce court) → BH through the middle used 2.0% · won 53% · −13.3±9.2 vs own baseline
  4. T serve (ad court) → FH down the line used 2.8% · won 53% · −12.9±8.2 vs own baseline
  5. Body serve (deuce court) → FH through the middle used 2.5% · won 52% · −14.8±8.5 vs own baseline

Return

  1. vs wide serve (deuce court) → FH through the middle, deep used 2.7% · won 52% · +12.3±8.9 vs own baseline
  2. vs wide serve (ad court) → BH through the middle, deep used 3.0% · won 52% · +11.6±8.6 vs own baseline
  3. vs T serve (ad court) → FH through the middle, deep used 2.1% · won 49% · +8.6±9.7 vs own baseline
  4. vs T serve (ad court) → FH through the middle, mid used 3.0% · won 46% · +6.0±8.6 vs own baseline
  5. vs T serve (deuce court) → BH through the middle, deep used 2.5% · won 46% · +6.2±9.1 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH inside-out used 1.5% · won 53% · +10.4±9.6 vs own baseline
  2. FH crosscourt → FH down the line used 3.0% · won 47% · +4.5±7.5 vs own baseline
  3. FH through the middle → BH through the middle used 2.9% · won 47% · +4.5±7.5 vs own baseline
  4. BH crosscourt → FH through the middle used 2.0% · won 48% · +5.3±8.7 vs own baseline
  5. BH through the middle → BH crosscourt used 2.8% · won 47% · +4.4±7.6 vs own baseline

Discovered sequences

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

  1. FH down the line → BH crosscourt → FH inside-out used 0.6% · won 57% · +12.2±9.6 vs own baseline · +11.4 vs tour on the same sequence Disrupted by Sumit Nagal (3/7), Carlos Alcaraz (5/6)
  2. T serve → FH through the middle return, deep → FH crosscourt used 0.2% · won 54% · +9.0±12.5 vs own baseline · +15.2 vs tour on the same sequence
  3. BH through the middle → FH down the line → BH crosscourt used 0.7% · won 50% · +5.2±9.3 vs own baseline · +6.2 vs tour on the same sequence Disrupted by Camilo Ugo Carabelli (3/9), Carlos Taberner (6/8)
  4. FH crosscourt → FH crosscourt → FH down the line used 0.9% · won 50% · +4.6±8.6 vs own baseline · +4.7 vs tour on the same sequence Disrupted by Tallon Griekspoor (4/8), Sumit Nagal (6/11)
  5. BH crosscourt → BH crosscourt → FH inside-out used 0.2% · won 53% · +7.9±12.7 vs own baseline · +13.9 vs tour on the same sequence
  6. FH crosscourt → FH through the middle → FH down the line used 0.3% · won 52% · +6.5±11.7 vs own baseline · +5.3 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 backhand · return +1+3.0185
FH to the middle · rally+1.7542
FH to their backhand · return +1+1.5251
BH to the middle · serve +1+1.3214
FH to their forehand · serve +1+1.0318

Most exposed to

BH to the middle · rally−2.0389
FH to the middle · rally−1.2403
BH to the middle · serve +1−1.2185
BH to the middle · return +1−1.1172
FH to their forehand · rally−0.91,002

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +1.32, Miomir Kecmanovic +1.10, Roberto Bautista Agut +0.91, Jack Draper +0.80, Casper Ruud +0.76

Favourable matchups

Fabian Marozsan +1.28, Miomir Kecmanovic +1.21, Roberto Carballes Baena +1.20, Pedro Martinez +1.19, Roberto Bautista Agut +1.18

Active players who are best at the shot in the top weakness: Juan Carlos Prado Angelo, Raphael Collignon, Jack Draper, Pedro Martinez, Thiago Monteiro

Tactical fingerprint

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

Drop shots / shot3.9%
Through the middle32%
T serves · ad47%
Forehand share57%
T serves · deuce48%
Run-around forehands22%
Avg rally length4.1
Deep returns29%
Wide serves · deuce44%
Serve & volley9%
FH down the line30%
Points at net11%
Chipped returns15%
Backhand slice19%
Point-ending shots21.4%
1st serve in59%
Unforced errors / shot8.3%
Wide serves · ad44%
BH down the line15%

Plays most like

  1. Botic Van De Zandschulp 2019–2026 plan v
  2. Otto Virtanen 2022–2025 plan v
  3. Arthur Cazaux 2020–2025 plan v
  4. Andreas Seppi 2008–2021 plan v
  5. Nuno Borges 2021–2026 plan v
  6. Matteo Arnaldi 2022–2025 plan v
  7. Mackenzie Mcdonald 2015–2025 plan v
  8. Alejandro Tabilo 2021–2026 plan v

Closest from another era

  1. Andrei Pavel 1999–2006
  2. Guillermo Canas 2001–2007
  3. Sebastien Grosjean 1999–2005

Charted matches