RallyIQ

ATP · Right-handed · 38 charted matches · 2018–2026

Jaume Munar

Archetype: Grinder · Ad-court T server

Against an average opponent

Serve points won 62.9% ±2.6 raw 60.0% · tour 63.4% · 3,136 points
Return points won 38.9% ±2.7 raw 37.3% · tour 36.6% · 3,137 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 ±0.08 better than 53% of ATP · raw −0.01
Shot selection −0.31 ±0.21 better than 22% of ATP · raw −0.31
Execution +0.60 ±0.36 better than 86% of ATP · raw +0.72
Tactical adaptability +0.05 first serves toward what's working, set to set · 35 matches
Adaptation speed +0.07 same, every two to three service games · per 100 first serves
Long-rally execution −0.34 ±0.57 shot 9 on v own earlier rally shots · 2,486 shots · better than 33% of ATP
Points left on the table 2.55 per 100 shots vs best direction · lower than 55% 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 17,418 shots.

Shot expected value

The share of points Jaume Munar 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 · 1,342 shots

OptionUsedWin %Tour
BH crosscourt 35% 47.1%±3.7 47.6%
BH through the middle 24% 41.2%±4.4 43.7%
BH down the line 14% 47.7%±5.8 46.4%
BH slice crosscourt 11% 40.8%±6.2 42.5%
BH slice through the middle 6% 27.2%±7.2 35.1%
FH inside-out 3% 45.2%±10.2 51.8%
FH inside-in 3% 48.1%±11.0 54.7%
FH through the middle 1% 37.6%±12.6 45.2%

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

position worth 44% to the average player · 935 shots

OptionUsedWin %Tour
FH crosscourt 37% 42.2%±4.3 46.6%
FH down the line 29% 40.7%±4.7 44.7%
FH through the middle 21% 42.1%±5.5 41.5%
FH slice through the middle 6% 23.9%±7.9 24.5%
FH slice crosscourt 3% 27.3%±10.2 30.9%
FH slice down the line 1% 27.7%±12.8 25.6%
FH down the line + approach 1% 73.7%±13.0 69.3%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 825 shots

OptionUsedWin %Tour
BH crosscourt 28% 44.2%±5.2 48.0%
BH through the middle 21% 43.2%±5.8 43.8%
BH slice crosscourt 19% 45.9%±6.2 42.1%
BH down the line 14% 47.6%±7.1 46.5%
BH slice through the middle 9% 38.6%±8.2 35.1%
BH slice down the line 2% 42.9%±12.9 35.8%
BH drop shot crosscourt 2% 53.9%±13.3 47.4%
FH inside-in 2% 52.4%±13.7 54.3%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 753 shots

OptionUsedWin %Tour
FH down the line 22% 48.6%±6.0 51.5%
FH crosscourt 22% 44.7%±6.0 52.7%
BH through the middle 16% 51.7%±6.9 46.8%
FH through the middle 14% 46.8%±7.2 47.0%
BH crosscourt 10% 50.3%±8.5 49.1%
BH down the line 5% 47.7%±10.8 48.3%
BH slice crosscourt 3% 42.4%±12.7 47.0%
FH down the line + approach 2% 72.5%±12.2 70.5%

Serve under pressure

Pressure predictability index +6 How much less varied Jaume Munar's first-serve direction gets on break points. Positive means easier to read. Based on 316 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 54% 65% ▲ 68% / 73%
Body 10% 1% ▼ 65% / 63%
T 36% 34% 73% / 75%

1,550 normal · 79 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 51% 51% 68% / 73%
Body 14% 14% 64% / 63%
T 35% 35% 66% / 72%

1,268 normal · 237 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
Wide55% 61.5%±2.6 n=894 51% ▼
Body10% 57.9%±5.9 n=157 0% ▼
T35% 61.2%±3.3 n=578 49% ▲

Consistent with an optimal mix (p = 0.57).
Optimal mix: +0.3 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide51% 59.8%±2.9 n=768 51%
Body14% 59.1%±5.2 n=210 1% ▼
T35% 57.5%±3.4 n=527 48% ▲

Consistent with an optimal mix (p = 0.64).
Optimal mix: +0.1 per 100 first serves.

Exploitability 0.21 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±3.0 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. (1,331 repeats, 1,729 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 85 37% −0.4±7.4
1stAd courtT 338 31% +2.5±3.9
1stAd courtWide 533 30% +3.0±3.2
1stDeuce courtBody 108 46% +8.9±7.0
1stDeuce courtT 402 29% +3.5±3.6
1stDeuce courtWide 495 28% +0.8±3.2
2ndAd courtBody 183 46% −3.0±5.6
2ndAd courtT 72 50% +0.5±8.1
2ndAd courtWide 292 50% +1.2±4.6
2ndDeuce courtBody 232 45% −4.1±5.1
2ndDeuce courtT 247 49% −1.0±4.9
2ndDeuce courtWide 149 52% +4.1±6.1

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 3.2% · won 62% · −1.1±7.4 vs own baseline
  2. Wide serve (deuce court) → FH crosscourt used 3.5% · won 62% · −1.1±7.1 vs own baseline
  3. T serve (deuce court) → FH crosscourt used 2.4% · won 56% · −7.0±8.3 vs own baseline
  4. Wide serve (deuce court) → BH crosscourt used 2.3% · won 54% · −8.9±8.6 vs own baseline
  5. Body serve (deuce court) → FH down the line used 2.5% · won 55% · −8.7±8.2 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 5.3% · won 46% · +8.2±6.6 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, deep used 2.2% · won 47% · +8.7±9.1 vs own baseline
  3. vs T serve (ad court) → FH through the middle, short used 2.1% · won 45% · +7.2±9.3 vs own baseline
  4. vs T serve (deuce court) → BH through the middle, short used 2.1% · won 45% · +6.6±9.3 vs own baseline
  5. vs wide serve (deuce court) → FH through the middle, deep used 2.6% · won 44% · +5.6±8.6 vs own baseline

Rally, consecutive own shots

  1. BH through the middle → BH through the middle used 2.1% · won 53% · +9.3±7.7 vs own baseline
  2. BH crosscourt → FH crosscourt used 3.0% · won 51% · +7.1±6.7 vs own baseline
  3. BH crosscourt → FH down the line used 1.4% · won 53% · +8.5±8.8 vs own baseline
  4. FH through the middle → BH down the line used 1.0% · won 51% · +6.9±9.7 vs own baseline
  5. FH through the middle → BH crosscourt used 1.7% · won 49% · +4.6±8.4 vs own baseline

Discovered sequences

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

  1. Wide serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 64% · +18.2±11.3 vs own baseline · +24.6 vs tour on the same sequence
  2. BH through the middle → FH down the line → BH through the middle used 0.6% · won 54% · +8.3±9.1 vs own baseline · +15.0 vs tour on the same sequence Disrupted by Guido Andreozzi (3/7)
  3. BH crosscourt → BH down the line → FH crosscourt used 0.3% · won 56% · +9.8±11.4 vs own baseline · +17.9 vs tour on the same sequence
  4. FH crosscourt → FH through the middle → BH crosscourt used 0.2% · won 56% · +10.3±11.9 vs own baseline · +18.1 vs tour on the same sequence
  5. BH slice crosscourt → FH inside-out → BH crosscourt used 0.4% · won 54% · +8.1±10.6 vs own baseline · +12.3 vs tour on the same sequence
  6. FH through the middle → FH down the line → BH crosscourt used 0.3% · won 54% · +7.6±11.1 vs own baseline · +13.8 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 forehand · return +1+3.3292
BH to the middle · return +1+3.1277
BH to their forehand · rally+2.5477
BH to their backhand · serve +1+2.5273
BH to their backhand · return+2.1392

Most exposed to

BH to their forehand · return−3.3178
BH to their forehand · rally−2.5428
FH to their forehand · rally−2.11,399
FH to their forehand · return +1−1.4338
FH to their forehand · return−1.4352

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +2.22, Miomir Kecmanovic +1.95, Jack Draper +1.89, Nishesh Basavareddy +1.83, Novak Djokovic +1.63

Favourable matchups

Miomir Kecmanovic +2.21, Fabian Marozsan +2.12, Pedro Martinez +2.09, Roberto Carballes Baena +2.05, Roberto Bautista Agut +2.03

Active players who are best at the shot in the top weakness: Ugo Humbert, Karen Khachanov, Andy Murray, Joao Fonseca, Yoshihito Nishioka

Tactical fingerprint

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

Wide serves · deuce55%
Avg rally length4.7
Through the middle27%
FH down the line33%
1st serve in63%
Deep returns30%
Drop shots / shot2.0%
Chipped returns19%
Backhand slice23%
Wide serves · ad51%
Forehand share53%
BH down the line20%
Run-around forehands16%
Serve & volley3%
Points at net9%
T serves · ad35%
Point-ending shots17.0%
T serves · deuce35%
Unforced errors / shot6.6%

Plays most like

  1. Guillermo Coria 2002–2005 plan v
  2. Carlos Berlocq 2011–2019 plan v
  3. Bernabe Zapata Miralles 2019–2024 plan v
  4. Novak Djokovic 2005–2026 plan v
  5. Mikhail Kukushkin 2014–2022 plan v
  6. Brandon Nakashima 2020–2026 plan v
  7. Karen Khachanov 2015–2026 plan v
  8. Pablo Carreno Busta 2015–2026 plan v

Closest from another era

  1. Guillermo Coria 2002–2005
  2. Magnus Norman 2000–2001
  3. Jiri Novak 1996–2004

Charted matches