RallyIQ

ATP · Right-handed · 80 charted matches · 2015–2026

Karen Khachanov

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 66.3% ±2.4 raw 64.6% · tour 63.4% · 6,430 points
Return points won 38.3% ±2.6 raw 35.6% · tour 36.6% · 6,540 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 ±0.06 better than 59% of ATP · raw +0.01
Shot selection −0.28 ±0.08 better than 25% of ATP · raw −0.29
Execution +0.50 ±0.28 better than 84% of ATP · raw +0.44
Tactical adaptability −0.02 first serves toward what's working, set to set · 78 matches
Adaptation speed +0.02 same, every two to three service games · per 100 first serves
Long-rally execution +0.10 ±0.46 shot 9 on v own earlier rally shots · 4,504 shots · better than 82% of ATP
Points left on the table 2.41 per 100 shots vs best direction · lower than 72% 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 33,066 shots.

Shot expected value

The share of points Karen Khachanov 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 · 2,022 shots

OptionUsedWin %Tour
BH crosscourt 45% 45.9%±2.7 47.6%
BH through the middle 21% 45.2%±3.9 43.7%
BH down the line 13% 47.8%±4.9 46.4%
BH slice crosscourt 6% 35.7%±6.8 42.5%
BH slice through the middle 5% 31.4%±6.9 35.1%
FH inside-out 4% 48.5%±8.0 51.8%
FH inside-in 2% 61.1%±9.8 54.7%
BH slice down the line 1% 34.2%±11.6 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 1,678 shots

OptionUsedWin %Tour
FH down the line 25% 54.6%±3.9 51.5%
FH crosscourt 21% 49.3%±4.3 52.7%
BH crosscourt 17% 47.2%±4.7 49.1%
FH through the middle 16% 49.6%±4.8 47.0%
BH through the middle 13% 54.1%±5.3 46.8%
BH down the line 4% 45.9%±8.5 48.3%
FH down the line + approach 2% 68.3%±11.2 70.5%
FH crosscourt + approach 1% 66.6%±14.2 69.9%

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

position worth 44% to the average player · 1,412 shots

OptionUsedWin %Tour
FH crosscourt 35% 46.6%±3.7 46.6%
FH through the middle 26% 40.4%±4.1 41.5%
FH down the line 23% 50.0%±4.4 44.7%
FH slice through the middle 9% 23.1%±5.6 24.5%
FH slice down the line 3% 28.8%±9.4 25.6%
FH slice crosscourt 2% 33.0%±11.1 30.9%
FH down the line + approach 2% 72.4%±11.1 69.3%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 1,310 shots

OptionUsedWin %Tour
BH crosscourt 44% 49.7%±3.4 48.0%
BH through the middle 19% 47.5%±5.0 43.8%
BH down the line 14% 45.0%±5.7 46.5%
BH slice crosscourt 10% 44.1%±6.6 42.1%
BH slice through the middle 6% 32.7%±7.6 35.1%
FH inside-out 2% 40.7%±11.7 52.6%
BH slice down the line 2% 40.9%±12.5 35.8%
FH inside-in 1% 53.7%±13.5 54.3%

Serve under pressure

Pressure predictability index −2 How much less varied Karen Khachanov's first-serve direction gets on break points. Positive means easier to read. Based on 528 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 50% 48% 73% / 73%
Body 5% 5% 63% / 63%
T 45% 47% 73% / 75%

3,217 normal · 133 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 53% 46% 74% / 73%
Body 6% 7% 61% / 63%
T 41% 47% 69% / 72%

2,676 normal · 395 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
Wide50% 66.3%±1.9 n=1,678 63% ▲
Body5% 59.7%±5.7 n=168 0% ▼
T45% 63.9%±2.0 n=1,504 37% ▼

Consistent with an optimal mix (p = 0.08).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide52% 66.9%±1.9 n=1,587 65% ▲
Body6% 59.5%±5.3 n=198 0% ▼
T42% 61.9%±2.2 n=1,286 35% ▼

Off equilibrium (p = 0.003): serve wide more. Gap 2.6 points per 100 first serves.
Optimal mix: +0.7 per 100 first serves.

Exploitability 0.60 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±2.2 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. (2,723 repeats, 3,540 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 196 35% −2.4±5.2
1stAd courtT 893 28% +0.2±2.4
1stAd courtWide 826 24% −3.3±2.4
1stDeuce courtBody 264 36% −1.0±4.6
1stDeuce courtT 869 24% −0.8±2.4
1stDeuce courtWide 1,012 26% −1.4±2.2
2ndAd courtBody 425 52% +2.7±3.9
2ndAd courtT 272 53% +3.3±4.7
2ndAd courtWide 515 50% +2.0±3.5
2ndDeuce courtBody 498 48% −0.8±3.6
2ndDeuce courtT 493 50% ±0.0±3.6
2ndDeuce courtWide 274 48% −0.6±4.7

Signature patterns

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

Serve → +1

  1. Wide serve (deuce court) → FH crosscourt used 2.2% · won 66% · −1.7±6.1 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 2.2% · won 62% · −5.1±6.3 vs own baseline
  3. Wide serve (deuce court) → FH down the line used 4.0% · won 60% · −7.1±4.9 vs own baseline
  4. T serve (ad court) → FH down the line used 2.7% · won 58% · −9.4±5.8 vs own baseline
  5. T serve (ad court) → FH crosscourt used 2.6% · won 57% · −10.4±6.0 vs own baseline

Return

  1. vs T serve (ad court) → FH through the middle, mid used 2.0% · won 51% · +13.4±7.0 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, deep used 2.2% · won 47% · +9.8±6.8 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, short used 2.4% · won 45% · +7.4±6.5 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 3.5% · won 44% · +5.9±5.5 vs own baseline
  5. vs T serve (deuce court) → BH through the middle, mid used 2.8% · won 39% · +1.6±6.0 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.4% · won 59% · +11.5±7.0 vs own baseline
  2. BH through the middle → BH crosscourt used 2.8% · won 55% · +7.8±5.2 vs own baseline
  3. FH crosscourt → FH crosscourt used 2.9% · won 53% · +5.1±5.1 vs own baseline
  4. BH crosscourt → FH down the line used 2.6% · won 53% · +5.2±5.4 vs own baseline
  5. FH down the line → FH down the line used 1.1% · won 54% · +6.7±7.8 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Karen Khachanov 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 0.4% · won 60% · +11.8±8.3 vs own baseline · +12.0 vs tour on the same sequence Disrupted by Daniil Medvedev (5/11), Jannik Sinner (4/6)
  2. BH crosscourt → BH slice crosscourt → FH inside-out used 0.3% · won 62% · +13.6±9.5 vs own baseline · +15.6 vs tour on the same sequence Disrupted by Daniel Evans (8/12), Dominic Thiem (5/6)
  3. BH crosscourt → BH slice crosscourt → FH inside-in used 0.2% · won 64% · +15.5±10.4 vs own baseline · +20.4 vs tour on the same sequence Disrupted by Daniel Evans (7/10)
  4. FH down the line → BH slice through the middle → FH crosscourt used 0.2% · won 63% · +14.6±10.1 vs own baseline · +10.0 vs tour on the same sequence
  5. FH crosscourt → FH slice through the middle → FH down the line used 0.2% · won 63% · +13.9±10.2 vs own baseline · +9.7 vs tour on the same sequence
  6. FH crosscourt → FH crosscourt → FH down the line + approach used 0.1% · won 67% · +18.4±11.5 vs own baseline · +19.3 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 forehand · return+3.5280
FH slice to the middle · return +1+2.4132
FH to their forehand · return+2.4411
FH slice to the middle · rally+2.1286
FH to the middle · serve +1+1.9469

Most exposed to

FH volley to their forehand · rally−3.6171
FH to their forehand · serve +1−2.2906
FH to their forehand · return−2.1465
BH slice to their backhand · return +1−1.8237
BH to their forehand · serve +1−1.7310

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +2.28, Miomir Kecmanovic +1.99, Jack Draper +1.82, Pedro Martinez +1.79, Casper Ruud +1.76

Favourable matchups

Miomir Kecmanovic +1.52, Pedro Martinez +1.46, Fabian Marozsan +1.43, Roberto Carballes Baena +1.31, Roberto Bautista Agut +1.30

Active players who are best at the shot in the top weakness: Stefanos Tsitsipas, Alex De Minaur, Andy Murray, Carlos Alcaraz, Jannik Sinner

Tactical fingerprint

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

Wide serves · deuce50%
FH down the line35%
1st serve in65%
Deep returns31%
Avg rally length4.2
T serves · ad42%
Wide serves · ad52%
Through the middle25%
Chipped returns16%
T serves · deuce45%
Forehand share53%
BH down the line20%
Drop shots / shot1.2%
Run-around forehands16%
Unforced errors / shot9.2%
Serve & volley1%
Point-ending shots21.4%
Backhand slice13%
Points at net8%

Plays most like

  1. Laslo Djere 2018–2026 plan v
  2. Novak Djokovic 2005–2026 plan v
  3. Denis Istomin 2006–2021 plan v
  4. Learner Tien 2022–2026 plan v
  5. Alexander Shevchenko 2023–2026 plan v
  6. Hubert Hurkacz 2018–2026 plan v
  7. Gregoire Barrere 2016–2024 plan v
  8. Brandon Nakashima 2020–2026 plan v

Closest from another era

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

Charted matches