RallyIQ

ATP · Right-handed · 61 charted matches · 2019–2026

Jiri Lehecka

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 64.9% ±2.5 raw 63.1% · tour 63.4% · 4,224 points
Return points won 35.5% ±2.5 raw 32.1% · tour 36.6% · 3,932 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 −0.11 ±0.11 better than 30% of ATP · raw −0.11
Shot selection −0.02 ±0.14 better than 49% of ATP · raw −0.02
Execution −0.37 ±0.43 better than 50% of ATP · raw −0.35
Tactical adaptability +0.09 first serves toward what's working, set to set · 55 matches
Adaptation speed +0.04 same, every two to three service games · per 100 first serves
Points left on the table 2.73 per 100 shots vs best direction · lower than 37% 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 18,639 shots.

Shot expected value

The share of points Jiri Lehecka 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 · 1,033 shots

OptionUsedWin %Tour
BH crosscourt 44% 38.4%±3.7 47.6%
BH through the middle 31% 35.1%±4.3 43.7%
BH down the line 8% 38.5%±7.9 46.4%
BH slice crosscourt 4% 46.1%±10.2 42.5%
FH inside-out 4% 45.0%±10.3 51.8%
BH slice through the middle 4% 29.1%±9.5 35.1%
BH slice down the line 2% 41.7%±13.3 37.1%
FH inside-in 1% 48.4%±13.9 54.7%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 966 shots

OptionUsedWin %Tour
FH through the middle 20% 41.6%±5.5 47.0%
FH down the line 19% 49.2%±5.7 51.5%
BH through the middle 19% 43.8%±5.7 46.8%
FH crosscourt 19% 42.7%±5.8 52.7%
BH crosscourt 10% 45.4%±7.7 49.1%
BH down the line 6% 38.7%±9.3 48.3%
FH crosscourt + approach 2% 62.4%±12.6 69.9%
FH down the line + approach 2% 64.4%±12.6 70.5%

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

position worth 44% to the average player · 736 shots

OptionUsedWin %Tour
FH crosscourt 39% 44.9%±4.7 46.6%
FH through the middle 24% 34.8%±5.6 41.5%
FH down the line 18% 46.7%±6.7 44.7%
FH slice through the middle 10% 20.1%±6.8 24.5%
FH slice crosscourt 6% 26.5%±9.3 30.9%
FH slice down the line 2% 29.8%±12.9 25.6%

Return +1: drive to your backhand side

position worth 44% to the average player · 572 shots

OptionUsedWin %Tour
BH crosscourt 42% 44.3%±5.1 46.9%
BH through the middle 28% 36.3%±5.9 43.0%
BH down the line 10% 43.8%±9.4 44.2%
BH slice crosscourt 8% 37.0%±9.6 40.9%
BH slice through the middle 6% 23.6%±9.6 32.6%
FH inside-out 2% 43.4%±14.2 51.7%

Serve under pressure

Pressure predictability index ±0 How much less varied Jiri Lehecka's first-serve direction gets on break points. Positive means easier to read. Based on 409 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 44% 44% 72% / 73%
Body 12% 8% 60% / 63%
T 44% 48% 76% / 75%

2,122 normal · 89 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 54% 51% 73% / 73%
Body 9% 9% 65% / 63%
T 37% 39% 72% / 72%

1,692 normal · 320 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% 65.6%±2.5 n=969 57% ▲
Body12% 57.9%±4.8 n=258 0% ▼
T45% 64.0%±2.5 n=984 43% ▼

Off equilibrium (p = 0.028): serve wide more. Gap 1.6 points per 100 first serves.
Optimal mix: +0.7 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide54% 62.4%±2.4 n=1,079 67% ▲
Body9% 63.6%±5.4 n=183 0% ▼
T37% 61.6%±2.9 n=750 33% ▼

Consistent with an optimal mix (p = 0.82).
Optimal mix: +0.2 per 100 first serves.

Exploitability 0.44 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: −3.2±2.3 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. (1,519 repeats, 2,584 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 70 33% −3.9±7.7
1stAd courtT 513 23% −4.9±3.0
1stAd courtWide 574 23% −4.5±2.8
1stDeuce courtBody 101 40% +3.8±7.1
1stDeuce courtT 604 24% −0.9±2.8
1stDeuce courtWide 595 23% −4.4±2.8
2ndAd courtBody 234 45% −4.4±5.0
2ndAd courtT 118 49% −0.1±6.8
2ndAd courtWide 351 45% −3.6±4.2
2ndDeuce courtBody 208 47% −2.1±5.3
2ndDeuce courtT 393 47% −2.2±4.0
2ndDeuce courtWide 171 43% −5.1±5.7

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH down the line used 2.4% · won 62% · −5.7±7.3 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 2.2% · won 61% · −6.3±7.6 vs own baseline
  3. Wide serve (deuce court) → FH down the line used 2.9% · won 59% · −8.4±6.9 vs own baseline
  4. Wide serve (deuce court) → FH crosscourt used 2.9% · won 56% · −11.3±7.0 vs own baseline
  5. T serve (deuce court) → FH crosscourt used 3.2% · won 55% · −12.2±6.6 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 2.7% · won 51% · +13.8±8.1 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, mid used 3.3% · won 46% · +9.0±7.5 vs own baseline
  3. vs T serve (deuce court) → BH through the middle used 4.4% · won 38% · +0.5±6.5 vs own baseline
  4. vs T serve (ad court) → FH through the middle used 2.6% · won 33% · −4.5±7.8 vs own baseline
  5. vs wide serve (deuce court) → FH crosscourt used 2.1% · won 30% · −7.7±8.1 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH down the line used 2.9% · won 49% · +8.7±7.4 vs own baseline
  2. BH through the middle → FH down the line used 2.6% · won 47% · +6.8±7.8 vs own baseline
  3. FH down the line → FH down the line used 1.7% · won 48% · +7.1±9.0 vs own baseline
  4. BH crosscourt → FH crosscourt used 2.5% · won 46% · +5.8±7.8 vs own baseline
  5. FH crosscourt → BH crosscourt used 3.3% · won 45% · +4.5±7.1 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Jiri Lehecka 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 through the middle → FH down the line used 0.5% · won 57% · +12.7±10.1 vs own baseline · +12.3 vs tour on the same sequence
  2. Wide serve → FH through the middle return → FH down the line used 0.2% · won 57% · +12.4±12.0 vs own baseline · +10.5 vs tour on the same sequence
  3. BH through the middle → FH crosscourt → FH crosscourt used 0.7% · won 50% · +5.2±8.7 vs own baseline · +6.6 vs tour on the same sequence Disrupted by Carlos Alcaraz (5/10)
  4. BH crosscourt → BH through the middle → FH down the line used 0.8% · won 49% · +4.7±8.6 vs own baseline · −0.6 vs tour on the same sequence Disrupted by Andy Murray (2/6), Novak Djokovic (3/6)
  5. Wide serve → FH through the middle return, mid → FH down the line used 0.2% · won 52% · +8.0±12.1 vs own baseline · +6.0 vs tour on the same sequence
  6. Wide serve → BH through the middle return, mid → FH down the line used 0.2% · won 53% · +8.3±12.7 vs own baseline · +7.4 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+4.3146
Wide 2nd serve · deuce court+3.0232
T 1st serve · ad court+2.4741
Wide 1st serve · ad court+2.31,064
T 1st serve · deuce court+1.9970

Most exposed to

Wide 2nd serve · deuce court−4.1170
BH to the middle · return−3.5765
BH to their backhand · return−2.8454
T 1st serve · ad court−2.2786
Wide 1st serve · deuce court−2.2892

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +1.85, Miomir Kecmanovic +1.71, Nishesh Basavareddy +1.53, Jack Draper +1.49, Casper Ruud +1.43

Favourable matchups

Miomir Kecmanovic +0.38, Fabian Marozsan +0.36, Pedro Martinez +0.25, Roberto Bautista Agut +0.19, Roberto Carballes Baena +0.16

Active players who are best at the shot in the top weakness: Andrey Rublev, Brandon Nakashima, Giovanni Mpetshi Perricard, Nick Kyrgios, Reilly Opelka

Tactical fingerprint

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

Through the middle31%
Unforced errors / shot12.9%
Chipped returns23%
Point-ending shots27.2%
Deep returns31%
Wide serves · ad54%
1st serve in63%
Forehand share55%
FH down the line31%
Wide serves · deuce44%
Run-around forehands18%
T serves · deuce45%
Points at net11%
Serve & volley6%
Drop shots / shot1.3%
T serves · ad37%
Backhand slice15%
Avg rally length3.6
BH down the line14%

Plays most like

  1. Gabriel Diallo 2024–2025 plan v
  2. Ben Shelton 2021–2026 plan v
  3. Zizou Bergs 2021–2026 plan v
  4. Arthur Rinderknech 2021–2026 plan v
  5. Gregoire Barrere 2016–2024 plan v
  6. Luca Nardi 2022–2025 plan v
  7. Zhizhen Zhang 2019–2026 plan v
  8. Alexander Shevchenko 2023–2026 plan v

Closest from another era

  1. Andrei Pavel 1999–2006
  2. Ivan Ljubicic 2003–2011
  3. Mardy Fish 2003–2012

Charted matches