RallyIQ

ATP · Right-handed · 42 charted matches · 2015–2026

Pablo Carreno Busta

Archetype: Grinder · Ad-court T server

Against an average opponent

Serve points won 64.5% ±2.7 raw 62.3% · tour 63.4% · 3,460 points
Return points won 37.9% ±2.8 raw 34.7% · tour 36.6% · 3,462 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 −0.01 ±0.09 better than 54% of ATP · raw −0.01
Shot selection −0.04 ±0.12 better than 48% of ATP · raw −0.04
Execution +0.75 ±0.44 better than 90% of ATP · raw +0.68
Tactical adaptability +0.29 first serves toward what's working, set to set · 41 matches
Adaptation speed +0.14 same, every two to three service games · per 100 first serves
Long-rally execution −0.05 ±0.56 shot 9 on v own earlier rally shots · 2,581 shots · better than 70% of ATP
Points left on the table 2.31 per 100 shots vs best direction · lower than 82% 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 17,880 shots.

Shot expected value

The share of points Pablo Carreno Busta 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 · 1,289 shots

OptionUsedWin %Tour
BH crosscourt 53% 48.5%±3.1 47.6%
BH through the middle 23% 43.7%±4.6 43.7%
BH down the line 9% 50.9%±7.1 46.4%
FH inside-out 4% 61.6%±9.4 51.8%
BH slice crosscourt 3% 46.9%±10.2 42.5%
BH slice through the middle 3% 32.3%±10.0 35.1%
FH inside-in 2% 53.7%±11.4 54.7%
FH through the middle 1% 39.5%±14.0 45.2%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 917 shots

OptionUsedWin %Tour
FH crosscourt 25% 52.2%±5.2 52.7%
FH down the line 21% 51.5%±5.6 51.5%
BH crosscourt 16% 55.5%±6.3 49.1%
BH through the middle 15% 47.1%±6.5 46.8%
FH through the middle 14% 48.6%±6.7 47.0%
BH down the line 3% 43.6%±11.3 48.3%
FH down the line + approach 2% 73.8%±12.4 70.5%
FH drop shot crosscourt 1% 54.6%±14.3 55.1%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 898 shots

OptionUsedWin %Tour
BH crosscourt 46% 49.8%±3.9 48.0%
BH through the middle 21% 48.2%±5.7 43.8%
BH down the line 12% 48.7%±7.2 46.5%
BH slice crosscourt 6% 52.6%±9.6 42.1%
BH slice through the middle 4% 43.4%±11.2 35.1%
FH inside-in 3% 58.9%±11.6 54.3%
FH inside-out 3% 58.2%±11.6 52.6%
BH slice down the line 1% 36.8%±13.8 35.8%

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

position worth 44% to the average player · 855 shots

OptionUsedWin %Tour
FH crosscourt 45% 46.3%±4.1 46.6%
FH through the middle 22% 45.6%±5.7 41.5%
FH down the line 19% 48.9%±6.1 44.7%
FH slice through the middle 8% 17.3%±6.7 24.5%
FH slice crosscourt 3% 31.4%±11.8 30.9%
FH drop shot crosscourt 1% 48.4%±14.5 52.5%
FH slice down the line 1% 19.8%±11.8 25.6%

Serve under pressure

Pressure predictability index +8 How much less varied Pablo Carreno Busta's first-serve direction gets on break points. Positive means easier to read. Based on 336 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 48% 50% 70% / 73%
Body 20% 13% 65% / 63%
T 32% 37% 68% / 75%

1,723 normal · 82 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 47% 57% ▲ 71% / 73%
Body 14% 10% 66% / 63%
T 39% 33% 66% / 72%

1,397 normal · 254 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
Wide48% 63.4%±2.6 n=873 61% ▲
Body19% 62.1%±4.1 n=348 6% ▼
T32% 62.6%±3.2 n=584 33%

Consistent with an optimal mix (p = 0.88).
Optimal mix: +0.3 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide48% 61.9%±2.8 n=798 61% ▲
Body14% 64.1%±5.0 n=224 14%
T38% 60.0%±3.1 n=629 25% ▼

Consistent with an optimal mix (p = 0.43).
Optimal mix: +0.1 per 100 first serves.

Exploitability 0.22 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: +1.0±3.1 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. (1,263 repeats, 2,109 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 95 38% +0.7±7.1
1stAd courtT 387 26% −2.5±3.5
1stAd courtWide 509 25% −2.5±3.1
1stDeuce courtBody 81 38% +1.1±7.6
1stDeuce courtT 468 22% −3.5±3.0
1stDeuce courtWide 547 23% −3.9±2.9
2ndAd courtBody 264 53% +3.6±4.8
2ndAd courtT 99 54% +4.8±7.2
2ndAd courtWide 296 46% −1.9±4.5
2ndDeuce courtBody 281 50% +1.1±4.7
2ndDeuce courtT 286 51% +0.9±4.6
2ndDeuce courtWide 149 46% −2.0±6.1

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.9% · won 64% · −0.7±7.2 vs own baseline
  2. Body serve (deuce court) → FH down the line used 2.1% · won 61% · −2.9±8.2 vs own baseline
  3. Wide serve (deuce court) → FH down the line used 3.8% · won 60% · −4.5±6.6 vs own baseline
  4. Wide serve (deuce court) → FH through the middle used 2.2% · won 58% · −6.2±8.2 vs own baseline
  5. Wide serve (deuce court) → FH crosscourt used 2.4% · won 58% · −6.7±7.9 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 4.4% · won 48% · +8.5±7.1 vs own baseline
  2. vs wide serve (deuce court) → FH through the middle, deep used 2.3% · won 50% · +10.3±9.0 vs own baseline
  3. vs wide serve (ad court) → BH through the middle, deep used 2.1% · won 47% · +7.2±9.2 vs own baseline
  4. vs T serve (deuce court) → BH through the middle, mid used 3.1% · won 44% · +4.5±8.0 vs own baseline
  5. vs wide serve (deuce court) → FH through the middle, mid used 3.7% · won 42% · +2.1±7.5 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH crosscourt used 4.1% · won 54% · +5.3±5.8 vs own baseline
  2. FH through the middle → BH crosscourt used 3.3% · won 54% · +5.4±6.4 vs own baseline
  3. BH crosscourt → FH down the line used 2.1% · won 54% · +5.2±7.7 vs own baseline
  4. BH down the line → FH down the line used 1.1% · won 55% · +7.0±9.4 vs own baseline
  5. BH crosscourt → BH crosscourt used 8.6% · won 51% · +2.4±4.1 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH through the middle → BH crosscourt used 0.6% · won 56% · +7.1±8.8 vs own baseline · +8.9 vs tour on the same sequence Disrupted by Novak Djokovic (2/6), Jannik Sinner (8/13)
  2. FH down the line → BH crosscourt → FH inside-out used 0.3% · won 59% · +10.3±11.3 vs own baseline · +16.8 vs tour on the same sequence
  3. T serve → BH through the middle return, deep → FH down the line used 0.2% · won 62% · +12.6±12.5 vs own baseline · +31.6 vs tour on the same sequence
  4. BH crosscourt → BH crosscourt → BH crosscourt used 2.6% · won 52% · +3.1±4.9 vs own baseline · +4.0 vs tour on the same sequence Disrupted by Stan Wawrinka (1/6), Fabio Fognini (2/7)
  5. Wide serve → BH through the middle return, deep → FH crosscourt used 0.3% · won 58% · +8.9±11.1 vs own baseline · +13.2 vs tour on the same sequence Disrupted by Jannik Sinner (5/6)
  6. BH down the line → FH crosscourt → FH down the line used 0.3% · won 58% · +8.9±11.1 vs own baseline · +18.6 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

FH to their backhand · return +1+2.6202
BH to the middle · return +1+2.2222
BH to their forehand · return +1+1.8129
BH to their forehand · rally+1.6513
FH to the middle · rally+1.5593

Most exposed to

BH to their forehand · return +1−4.1142
BH to their forehand · rally−2.6449
FH to their backhand · rally−2.21,229
FH to the middle · return−2.2677
BH to their backhand · return−1.9467

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +2.74, Miomir Kecmanovic +2.41, Jack Draper +2.33, Nishesh Basavareddy +2.23, Roberto Bautista Agut +2.09

Favourable matchups

Miomir Kecmanovic +2.05, Fabian Marozsan +1.87, Pedro Martinez +1.87, Roberto Carballes Baena +1.75, Roberto Bautista Agut +1.75

Active players who are best at the shot in the top weakness: Rafael Nadal, Adrian Mannarino, Yoshihito Nishioka, Learner Tien, Casper Ruud

Tactical fingerprint

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

1st serve in68%
Wide serves · deuce48%
Avg rally length4.4
Deep returns30%
Run-around forehands20%
Drop shots / shot1.6%
Forehand share54%
Chipped returns16%
Through the middle25%
T serves · ad38%
Wide serves · ad48%
Serve & volley1%
FH down the line28%
Point-ending shots20.0%
Points at net7%
Backhand slice10%
Unforced errors / shot8.1%
BH down the line14%
T serves · deuce32%

Plays most like

  1. Bernabe Zapata Miralles 2019–2024 plan v
  2. Alejandro Tabilo 2021–2026 plan v
  3. Luca Nardi 2022–2025 plan v
  4. Casper Ruud 2017–2026 plan v
  5. Tommy Paul 2016–2026 plan v
  6. Jaume Munar 2018–2026 plan v
  7. Valentin Vacherot 2024–2026 plan v
  8. Miomir Kecmanovic 2019–2026 plan v

Closest from another era

  1. Guillermo Coria 2002–2005
  2. Magnus Norman 2000–2001
  3. Andre Agassi 1988–2006

Charted matches