RallyIQ

ATP · Right-handed · 28 charted matches · 2013–2024

Thanasi Kokkinakis

Archetype: High-risk · Runs around the backhand

Against an average opponent

Serve points won 65.7% ±2.9 raw 66.1% · tour 63.4% · 2,551 points
Return points won 36.3% ±3.0 raw 31.8% · tour 36.6% · 2,486 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 +0.03 ±0.07 better than 63% of ATP · raw +0.03
Shot selection −0.38 ±0.18 better than 18% of ATP · raw −0.38
Execution −0.13 ±0.56 better than 61% of ATP · raw −0.16
Tactical adaptability +0.25 first serves toward what's working, set to set · 28 matches
Adaptation speed +0.28 same, every two to three service games · per 100 first serves
Points left on the table 2.45 per 100 shots vs best direction · lower than 68% 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 11,263 shots.

Shot expected value

The share of points Thanasi Kokkinakis 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 · 705 shots

OptionUsedWin %Tour
BH crosscourt 34% 43.7%±5.0 47.6%
BH through the middle 20% 41.1%±6.4 43.7%
BH slice crosscourt 9% 44.8%±8.8 42.5%
BH down the line 9% 39.4%±8.9 46.4%
BH slice through the middle 7% 33.4%±9.1 35.1%
FH inside-out 7% 56.2%±9.8 51.8%
FH inside-in 7% 56.6%±10.0 54.7%
BH slice down the line 4% 34.2%±11.6 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 497 shots

OptionUsedWin %Tour
FH down the line 30% 55.8%±6.3 51.5%
FH crosscourt 27% 60.7%±6.5 52.7%
FH through the middle 13% 49.9%±8.8 47.0%
BH crosscourt 13% 46.9%±8.8 49.1%
BH through the middle 12% 52.9%±9.1 46.8%
BH down the line 2% 50.5%±14.8 48.3%

Return +1: drive to your backhand side

position worth 44% to the average player · 381 shots

OptionUsedWin %Tour
BH crosscourt 31% 40.1%±6.9 46.9%
BH through the middle 18% 45.6%±8.7 43.0%
BH slice crosscourt 14% 37.2%±9.3 40.9%
BH down the line 12% 48.2%±10.3 44.2%
BH slice through the middle 10% 39.5%±10.7 32.6%
FH inside-out 5% 48.2%±13.3 51.7%
FH inside-in 4% 60.3%±13.4 53.6%
BH slice down the line 4% 32.4%±12.8 33.3%

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

position worth 44% to the average player · 377 shots

OptionUsedWin %Tour
FH crosscourt 35% 41.3%±6.6 46.6%
FH down the line 28% 47.2%±7.3 44.7%
FH through the middle 16% 35.8%±8.9 41.5%
FH slice through the middle 11% 33.2%±9.8 24.5%
FH slice down the line 6% 19.3%±10.0 25.6%
FH slice crosscourt 3% 47.3%±15.0 30.9%

Serve under pressure

Pressure predictability index +7 How much less varied Thanasi Kokkinakis's first-serve direction gets on break points. Positive means easier to read. Based on 179 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 48% 37% ▼ 76% / 73%
Body 5% 16% ▲ 61% / 63%
T 47% 47% 74% / 75%

1,289 normal · 38 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 51% 57% 80% / 73%
Body 8% 3% 62% / 63%
T 41% 40% 77% / 72%

1,072 normal · 141 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% 67.6%±3.0 n=636 61% ▲
Body5% 58.5%±8.1 n=71 0% ▼
T47% 64.9%±3.1 n=620 39% ▼

Consistent with an optimal mix (p = 0.09).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide52% 69.0%±3.0 n=625 65% ▲
Body7% 55.2%±7.6 n=87 0% ▼
T41% 66.0%±3.4 n=501 35% ▼

Off equilibrium (p = 0.002): serve wide more. Gap 2.3 points per 100 first serves.
Optimal mix: +0.8 per 100 first serves.

Exploitability 0.64 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: +1.6±3.6 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. (1,179 repeats, 1,305 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 67 38% +1.3±8.1
1stAd courtT 285 28% −0.3±4.2
1stAd courtWide 375 20% −6.9±3.3
1stDeuce courtBody 98 34% −2.3±6.9
1stDeuce courtT 386 22% −3.3±3.3
1stDeuce courtWide 363 23% −3.7±3.5
2ndAd courtBody 194 45% −4.4±5.5
2ndAd courtT 61 50% +1.0±8.6
2ndAd courtWide 186 49% +0.5±5.6
2ndDeuce courtBody 175 41% −7.7±5.7
2ndDeuce courtT 212 46% −3.9±5.3
2ndDeuce courtWide 73 47% −1.1±8.1

Signature patterns

Recurring sequences that win more than Thanasi Kokkinakis'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 2.3% · won 68% · −1.7±8.6 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 2.4% · won 66% · −4.2±8.6 vs own baseline
  3. Wide serve (deuce court) → FH crosscourt used 2.8% · won 60% · −10.1±8.4 vs own baseline
  4. T serve (ad court) → FH down the line used 2.0% · won 58% · −12.0±9.4 vs own baseline
  5. T serve (deuce court) → FH crosscourt used 2.7% · won 60% · −10.5±8.5 vs own baseline

Return

  1. vs T serve (deuce court) → BH through the middle, deep used 3.2% · won 46% · +11.0±9.0 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, deep used 2.7% · won 43% · +7.3±9.4 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, mid used 3.8% · won 40% · +4.4±8.3 vs own baseline
  4. vs wide serve (deuce court) → FH through the middle, deep used 2.4% · won 37% · +1.7±9.5 vs own baseline
  5. vs T serve (ad court) → FH down the line, mid used 2.0% · won 36% · +0.5±9.9 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 2.5% · won 61% · +13.7±9.3 vs own baseline
  2. FH down the line → FH down the line used 1.9% · won 61% · +13.3±10.1 vs own baseline
  3. FH crosscourt → FH down the line used 4.8% · won 55% · +8.1±7.5 vs own baseline
  4. BH through the middle → FH crosscourt used 2.5% · won 58% · +11.0±9.4 vs own baseline
  5. FH down the line → FH inside-out used 1.8% · won 57% · +9.4±10.3 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Thanasi Kokkinakis 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 crosscourt used 0.7% · won 59% · +11.1±10.2 vs own baseline · +11.2 vs tour on the same sequence Disrupted by Jannik Sinner (4/6)
  2. FH down the line → BH slice through the middle → FH crosscourt used 0.3% · won 64% · +16.5±12.2 vs own baseline · +25.3 vs tour on the same sequence
  3. FH crosscourt → FH through the middle → FH down the line used 0.7% · won 58% · +10.6±10.5 vs own baseline · +12.7 vs tour on the same sequence Disrupted by Stefanos Tsitsipas (3/7), Hubert Hurkacz (6/8)
  4. FH down the line → BH through the middle → FH down the line used 0.5% · won 58% · +10.8±11.1 vs own baseline · +15.2 vs tour on the same sequence
  5. FH crosscourt → FH crosscourt → FH down the line used 1.1% · won 55% · +7.4±9.1 vs own baseline · +11.4 vs tour on the same sequence Disrupted by Jannik Sinner (3/6), Alexei Popyrin (8/11)
  6. FH down the line → BH slice crosscourt → FH inside-out used 0.4% · won 56% · +8.8±12.0 vs own baseline · +11.8 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 the middle · return+1.6335
T 1st serve · ad court+1.4485
BH to the middle · rally+1.2294
FH to their forehand · serve +1+1.0384
BH to the middle · serve +1+1.0126

Most exposed to

BH to their backhand · serve +1−3.1202
FH to their forehand · serve +1−1.7348
BH to their forehand · rally−1.7165
FH to their backhand · serve +1−1.4404
Body 2nd serve · deuce court−1.1171

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +1.86, Miomir Kecmanovic +1.71, Nishesh Basavareddy +1.50, Jack Draper +1.47, Pedro Martinez +1.41

Favourable matchups

Fabian Marozsan +1.06, Miomir Kecmanovic +1.04, Pedro Martinez +0.89, Roberto Carballes Baena +0.84, Roberto Bautista Agut +0.78

Active players who are best at the shot in the top weakness: Nishesh Basavareddy, Alex Michelsen, Jaume Munar, Jenson Brooksby, Pedro Martinez

Tactical fingerprint

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

Run-around forehands35%
Deep returns35%
Forehand share58%
FH down the line35%
Wide serves · deuce48%
1st serve in63%
T serves · ad41%
Backhand slice26%
T serves · deuce47%
Wide serves · ad52%
Unforced errors / shot10.4%
Point-ending shots24.7%
BH down the line21%
Chipped returns12%
Serve & volley0%
Avg rally length3.6
Through the middle22%
Drop shots / shot0.5%
Points at net6%

Plays most like

  1. Andrey Rublev 2015–2026 plan v
  2. Kyle Edmund 2016–2023 plan v
  3. J J Wolf 2022–2024 plan v
  4. Felix Auger Aliassime 2017–2026 plan v
  5. Dominic Thiem 2011–2024 plan v
  6. Alexei Popyrin 2019–2026 plan v
  7. Lloyd Harris 2019–2024 plan v
  8. Marin Cilic 2009–2026 plan v

Closest from another era

  1. Magnus Norman 2000–2001
  2. Sebastien Grosjean 1999–2005
  3. Jim Courier 1989–1999

Charted matches