RallyIQ

ATP · Right-handed · 176 charted matches · 2015–2026

Andrey Rublev

Archetype: Ad-court T server · Two-fisted driver

Against an average opponent

Serve points won 66.9% ±2.3 raw 66.4% · tour 63.4% · 13,040 points
Return points won 39.1% ±2.5 raw 37.2% · tour 36.6% · 13,699 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 ±0.04 better than 64% of ATP · raw +0.03
Shot selection −0.01 ±0.06 better than 52% of ATP · raw ±0.00
Execution +0.89 ±0.28 better than 94% of ATP · raw +0.92
Tactical adaptability +0.01 first serves toward what's working, set to set · 170 matches
Adaptation speed +0.20 same, every two to three service games · per 100 first serves
Long-rally execution +0.14 ±0.40 shot 9 on v own earlier rally shots · 7,327 shots · better than 85% of ATP
Points left on the table 2.39 per 100 shots vs best direction · lower than 74% 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 61,662 shots.

Shot expected value

The share of points Andrey Rublev 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 · 4,173 shots

OptionUsedWin %Tour
BH crosscourt 42% 48.5%±2.0 47.6%
BH through the middle 23% 46.1%±2.6 43.7%
BH down the line 14% 47.7%±3.4 46.4%
FH inside-out 6% 55.7%±5.0 51.8%
BH slice through the middle 5% 28.8%±5.0 35.1%
BH slice crosscourt 5% 31.6%±5.2 42.5%
FH inside-in 3% 61.3%±6.3 54.7%
BH slice down the line 1% 38.2%±10.7 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 3,135 shots

OptionUsedWin %Tour
FH crosscourt 26% 57.8%±2.8 52.7%
FH down the line 26% 59.4%±2.8 51.5%
BH through the middle 14% 47.6%±3.9 46.8%
FH through the middle 13% 50.5%±3.9 47.0%
BH crosscourt 12% 49.7%±4.1 49.1%
BH down the line 6% 59.8%±5.6 48.3%
FH down the line + approach 2% 70.7%±9.1 70.5%
FH slice through the middle 0% 39.0%±14.0 34.4%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 2,577 shots

OptionUsedWin %Tour
BH crosscourt 42% 47.4%±2.5 48.0%
BH through the middle 22% 46.7%±3.4 43.8%
BH down the line 15% 53.2%±4.0 46.5%
BH slice crosscourt 6% 48.5%±6.3 42.1%
BH slice through the middle 5% 28.6%±6.0 35.1%
FH inside-out 4% 48.8%±7.3 52.6%
FH inside-in 3% 55.7%±8.1 54.3%
BH slice down the line 1% 36.5%±10.4 35.8%

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

position worth 44% to the average player · 2,133 shots

OptionUsedWin %Tour
FH crosscourt 38% 50.4%±2.9 46.6%
FH down the line 24% 48.6%±3.6 44.7%
FH through the middle 21% 48.3%±3.8 41.5%
FH slice through the middle 11% 20.5%±4.2 24.5%
FH slice down the line 3% 28.4%±8.0 25.6%
FH slice crosscourt 3% 36.0%±8.8 30.9%
FH down the line + approach 1% 77.7%±12.1 69.3%

Serve under pressure

Pressure predictability index +2 How much less varied Andrey Rublev's first-serve direction gets on break points. Positive means easier to read. Based on 923 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 44% 56% ▲ 74% / 73%
Body 5% 3% 68% / 63%
T 51% 41% ▼ 80% / 75%

6,623 normal · 213 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 52% 48% 77% / 73%
Body 4% 4% 68% / 63%
T 44% 48% 73% / 72%

5,476 normal · 710 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% 67.4%±1.4 n=3,008 57% ▲
Body5% 65.0%±4.0 n=354 0% ▼
T51% 66.9%±1.3 n=3,474 43% ▼

Consistent with an optimal mix (p = 0.58).
Optimal mix: +0.3 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide52% 66.5%±1.4 n=3,206 65% ▲
Body4% 60.1%±5.0 n=229 0% ▼
T44% 65.2%±1.5 n=2,751 35% ▼

Consistent with an optimal mix (p = 0.14).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.34 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±1.4 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. (6,021 repeats, 6,649 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 285 40% +3.0±4.5
1stAd courtT 1,607 26% −1.8±1.8
1stAd courtWide 2,083 28% +0.7±1.6
1stDeuce courtBody 318 40% +2.9±4.3
1stDeuce courtT 2,072 28% +2.6±1.6
1stDeuce courtWide 2,076 26% −1.1±1.6
2ndAd courtBody 773 53% +3.5±2.9
2ndAd courtT 407 49% +0.1±3.9
2ndAd courtWide 1,388 52% +3.9±2.2
2ndDeuce courtBody 744 53% +3.8±3.0
2ndDeuce courtT 1,370 53% +3.0±2.2
2ndDeuce courtWide 560 48% +0.3±3.4

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 3.1% · won 66% · −2.6±3.8 vs own baseline
  2. T serve (deuce court) → FH crosscourt used 3.6% · won 65% · −4.0±3.6 vs own baseline
  3. Wide serve (deuce court) → FH down the line used 3.4% · won 64% · −4.2±3.7 vs own baseline
  4. T serve (ad court) → FH crosscourt used 2.9% · won 64% · −4.9±4.0 vs own baseline
  5. T serve (deuce court) → FH down the line used 3.6% · won 64% · −5.1±3.6 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 3.4% · won 51% · +7.5±4.2 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, mid used 3.2% · won 47% · +3.7±4.3 vs own baseline
  3. vs T serve (deuce court) → BH crosscourt used 2.4% · won 45% · +1.3±4.9 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, short used 2.5% · won 45% · +1.1±4.8 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt used 4.9% · won 44% · +0.2±3.5 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 2.1% · won 71% · +20.3±4.2 vs own baseline
  2. FH down the line → FH down the line used 1.9% · won 63% · +13.2±4.6 vs own baseline
  3. FH crosscourt → FH down the line used 3.9% · won 58% · +7.9±3.4 vs own baseline
  4. BH through the middle → FH down the line used 2.0% · won 57% · +6.5±4.6 vs own baseline
  5. BH down the line → FH down the line used 1.8% · won 57% · +6.7±4.9 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH slice through the middle → FH down the line used 0.4% · won 71% · +19.1±6.3 vs own baseline · +12.2 vs tour on the same sequence Disrupted by Alexander Bublik (4/6), Daniil Medvedev (4/6)
  2. FH down the line → BH slice through the middle → FH crosscourt used 0.3% · won 68% · +16.9±7.4 vs own baseline · +10.5 vs tour on the same sequence Disrupted by Daniel Altmaier (4/6), Stefanos Tsitsipas (6/7)
  3. Wide serve → FH slice through the middle return → FH down the line used 0.2% · won 70% · +18.7±7.9 vs own baseline · +10.2 vs tour on the same sequence Disrupted by Alex De Minaur (7/8), Alexander Bublik (7/7)
  4. Wide serve → BH slice through the middle return → FH crosscourt used 0.1% · won 74% · +23.0±8.8 vs own baseline · +12.0 vs tour on the same sequence Disrupted by Christopher Eubanks (5/6)
  5. FH down the line → BH down the line → FH crosscourt used 0.2% · won 71% · +19.8±8.5 vs own baseline · +32.0 vs tour on the same sequence
  6. BH down the line → FH slice through the middle → FH down the line used 0.2% · won 69% · +17.7±8.1 vs own baseline · +15.6 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 2nd serve · deuce court+5.6225
FH to their forehand · return+3.9911
Wide 1st serve · deuce court+3.02,950
T 2nd serve · ad court+2.7263
FH to their backhand · return+2.3637

Most exposed to

BH to their forehand · return−5.3698
FH to their forehand · return−4.1801
FH volley to their forehand · rally−3.8176
FH slice to their backhand · return +1−2.9122
FH volley to their backhand · rally−2.6120

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +2.10, Miomir Kecmanovic +1.86, Jack Draper +1.71, Nishesh Basavareddy +1.71, Casper Ruud +1.68

Favourable matchups

Miomir Kecmanovic +1.88, Fabian Marozsan +1.83, Pedro Martinez +1.83, Roberto Carballes Baena +1.69, Alexander Shevchenko +1.67

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.

Run-around forehands30%
FH down the line35%
T serves · deuce51%
T serves · ad44%
Forehand share55%
BH down the line23%
1st serve in63%
Deep returns29%
Wide serves · ad52%
Wide serves · deuce44%
Point-ending shots24.0%
Through the middle24%
Avg rally length3.8
Unforced errors / shot9.3%
Serve & volley1%
Backhand slice13%
Chipped returns8%
Drop shots / shot0.3%
Points at net5%

Plays most like

  1. Thanasi Kokkinakis 2013–2024 plan v
  2. Kyle Edmund 2016–2023 plan v
  3. Juan Pablo Varillas 2021–2025 plan v
  4. Borna Coric 2015–2025 plan v
  5. David Goffin 2013–2025 plan v
  6. Robin Soderling 2004–2011 plan v
  7. Aleksandar Vukic 2019–2025 plan v
  8. Karen Khachanov 2015–2026 plan v

Closest from another era

  1. Juan Carlos Ferrero 2000–2009
  2. Magnus Norman 2000–2001
  3. Jim Courier 1989–1999

Charted matches