RallyIQ

ATP · Right-handed · 99 charted matches · 2017–2026

Alexander Bublik

Archetype: High-risk · Runs around the backhand

Against an average opponent

Serve points won 65.4% ±2.3 raw 63.6% · tour 63.4% · 7,466 points
Return points won 36.8% ±2.3 raw 33.6% · tour 36.6% · 7,004 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 −0.07 ±0.06 better than 39% of ATP · raw −0.06
Shot selection −0.42 ±0.11 better than 15% of ATP · raw −0.42
Execution −0.93 ±0.38 better than 26% of ATP · raw −0.83
Tactical adaptability ±0.00 first serves toward what's working, set to set · 89 matches
Adaptation speed −0.01 same, every two to three service games · per 100 first serves
Points left on the table 2.88 per 100 shots vs best direction · lower than 26% 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 30,986 shots.

Shot expected value

The share of points Alexander Bublik 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 · 1,201 shots

OptionUsedWin %Tour
BH crosscourt 39% 46.9%±3.7 47.6%
BH through the middle 22% 36.6%±4.7 43.7%
BH down the line 11% 40.3%±6.5 46.4%
BH slice through the middle 7% 27.3%±7.0 35.1%
BH slice crosscourt 7% 40.3%±7.8 42.5%
BH drop shot down the line 5% 41.9%±9.4 47.2%
BH slice down the line 2% 33.5%±11.4 37.1%
FH inside-out 1% 44.9%±14.5 51.8%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 1,144 shots

OptionUsedWin %Tour
FH crosscourt 20% 44.5%±5.1 52.7%
FH down the line 14% 41.7%±6.0 51.5%
BH crosscourt 14% 49.1%±6.1 49.1%
BH through the middle 13% 39.9%±6.1 46.8%
FH through the middle 11% 36.6%±6.6 47.0%
BH down the line 5% 45.7%±9.3 48.3%
FH drop shot down the line 5% 58.1%±9.2 56.5%
BH drop shot down the line 3% 42.6%±11.6 49.4%

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

position worth 44% to the average player · 996 shots

OptionUsedWin %Tour
FH crosscourt 30% 47.6%±4.6 46.6%
FH down the line 28% 41.7%±4.7 44.7%
FH through the middle 18% 38.4%±5.6 41.5%
FH slice through the middle 11% 26.1%±6.2 24.5%
FH slice down the line 4% 23.0%±9.2 25.6%
FH slice crosscourt 3% 39.1%±11.5 30.9%
FH drop shot down the line 3% 42.0%±12.1 49.6%
FH drop shot crosscourt 2% 48.7%±13.0 52.5%

Return +1: drive to your backhand side

position worth 44% to the average player · 920 shots

OptionUsedWin %Tour
BH crosscourt 35% 39.7%±4.3 46.9%
BH through the middle 28% 42.5%±4.9 43.0%
BH down the line 11% 43.0%±7.3 44.2%
BH slice through the middle 9% 25.0%±6.9 32.6%
BH slice crosscourt 8% 42.0%±8.2 40.9%
BH slice down the line 2% 28.5%±11.6 33.3%
BH drop shot down the line 2% 51.0%±13.3 46.9%
BH drop shot down the line + approach 1% 57.0%±14.6 58.3%

Serve under pressure

Pressure predictability index +3 How much less varied Alexander Bublik's first-serve direction gets on break points. Positive means easier to read. Based on 628 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 41% 40% 77% / 73%
Body 6% 6% 60% / 63%
T 53% 54% 76% / 75%

3,753 normal · 144 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 51% 80% / 73%
Body 9% 7% 65% / 63%
T 42% 43% 72% / 72%

3,071 normal · 484 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
Wide41% 65.5%±1.9 n=1,583 54% ▲
Body6% 59.4%±5.0 n=232 0% ▼
T53% 64.2%±1.7 n=2,082 46% ▼

Consistent with an optimal mix (p = 0.10).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide49% 63.2%±1.9 n=1,758 63% ▲
Body9% 59.3%±4.4 n=312 0% ▼
T42% 62.6%±2.0 n=1,485 37% ▼

Consistent with an optimal mix (p = 0.34).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.49 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: +0.6±1.9 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. (3,266 repeats, 3,988 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 222 36% −0.8±5.0
1stAd courtT 994 28% +0.2±2.3
1stAd courtWide 832 24% −3.0±2.4
1stDeuce courtBody 269 34% −2.6±4.5
1stDeuce courtT 1,094 22% −2.8±2.0
1stDeuce courtWide 984 26% −1.1±2.3
2ndAd courtBody 507 48% −1.7±3.5
2ndAd courtT 274 47% −2.6±4.7
2ndAd courtWide 488 44% −4.8±3.6
2ndDeuce courtBody 556 47% −2.5±3.4
2ndDeuce courtT 501 46% −3.6±3.6
2ndDeuce courtWide 274 47% −1.2±4.7

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.0% · won 69% · −2.3±6.1 vs own baseline
  2. T serve (deuce court) → FH crosscourt used 2.8% · won 57% · −13.8±5.7 vs own baseline
  3. T serve (ad court) → FH crosscourt used 3.4% · won 55% · −16.5±5.2 vs own baseline
  4. T serve (deuce court) → BH crosscourt used 2.4% · won 51% · −20.1±6.0 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 2.2% · won 40% · +3.4±6.6 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, mid used 3.0% · won 39% · +2.9±5.8 vs own baseline
  3. vs T serve (ad court) → FH slice through the middle used 3.6% · won 35% · −1.1±5.2 vs own baseline
  4. vs T serve (deuce court) → BH through the middle used 4.4% · won 35% · −1.4±4.7 vs own baseline
  5. vs wide serve (ad court) → BH through the middle used 3.6% · won 34% · −2.5±5.1 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH crosscourt used 3.6% · won 52% · +9.7±6.4 vs own baseline
  2. FH down the line → BH crosscourt used 2.7% · won 51% · +9.0±7.1 vs own baseline
  3. BH crosscourt → FH down the line used 2.0% · won 51% · +9.7±8.0 vs own baseline
  4. FH down the line → FH crosscourt used 1.8% · won 50% · +7.7±8.3 vs own baseline
  5. FH crosscourt → FH down the line used 3.9% · won 47% · +5.0±6.1 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Alexander Bublik 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 crosscourt → BH crosscourt used 0.6% · won 53% · +7.8±8.3 vs own baseline · +6.6 vs tour on the same sequence Disrupted by Jannik Sinner (4/9), Hubert Hurkacz (4/9)
  2. Wide serve → BH through the middle return → FH crosscourt used 0.2% · won 59% · +14.2±11.9 vs own baseline · +15.4 vs tour on the same sequence
  3. BH crosscourt → BH through the middle → FH down the line used 0.3% · won 57% · +11.8±11.0 vs own baseline · +15.3 vs tour on the same sequence Disrupted by Alex De Minaur (8/8)
  4. Body serve → BH through the middle return, mid → BH crosscourt used 0.2% · won 56% · +10.6±11.7 vs own baseline · +17.0 vs tour on the same sequence
  5. FH crosscourt → FH slice through the middle → FH down the line used 0.2% · won 56% · +11.4±12.4 vs own baseline · +9.7 vs tour on the same sequence
  6. T serve → BH through the middle return, short → FH crosscourt used 0.1% · won 57% · +11.7±12.7 vs own baseline · +16.5 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

Wide 1st serve · deuce court+2.71,571
BH to their forehand · serve +1+2.6223
BH volley to their forehand · rally+2.2123
T 1st serve · ad court+1.71,472
Wide 1st serve · ad court+1.61,748

Most exposed to

BH to their forehand · return +1−7.6242
FH to their forehand · return +1−2.1469
FH to their backhand · return +1−2.0366
BH volley to their backhand · rally−1.8130
FH to their backhand · rally−1.5976

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +1.61, Jack Draper +1.18, Miomir Kecmanovic +0.99, Roberto Bautista Agut +0.82, Pedro Martinez +0.81

Favourable matchups

Fabian Marozsan +0.09, Pedro Martinez −0.01, Miomir Kecmanovic −0.03, Roberto Bautista Agut −0.04, Alexander Shevchenko −0.08

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.

Drop shots / shot7.6%
Chipped returns32%
Unforced errors / shot13.0%
T serves · deuce53%
Point-ending shots30.4%
Deep returns32%
FH down the line33%
T serves · ad42%
Serve & volley12%
Through the middle25%
Points at net12%
Backhand slice20%
Wide serves · ad49%
1st serve in61%
Forehand share52%
BH down the line18%
Wide serves · deuce41%
Run-around forehands9%
Avg rally length3.3

Plays most like

  1. Yannick Hanfmann 2021–2025 plan v
  2. Fabian Marozsan 2021–2026 plan v
  3. Nick Kyrgios 2013–2025 plan v
  4. Jerzy Janowicz 2012–2020 plan v
  5. Matteo Arnaldi 2022–2025 plan v
  6. Otto Virtanen 2022–2025 plan v
  7. Hamad Medjedovic 2023–2026 plan v
  8. Sergiy Stakhovsky 2010–2022 plan v

Closest from another era

  1. Tommy Haas 1996–2017
  2. Gustavo Kuerten 1997–2007
  3. Marat Safin 1998–2009

Charted matches