RallyIQ

ATP · Right-handed · 196 charted matches · 2014–2026

Alexander Zverev

Archetype: Grinder · Ad-court T server

Against an average opponent

Serve points won 68.0% ±2.1 raw 66.3% · tour 63.4% · 15,652 points
Return points won 39.1% ±2.3 raw 36.0% · tour 36.6% · 16,212 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 +0.04 ±0.04 better than 68% of ATP · raw +0.03
Shot selection +0.09 ±0.06 better than 64% of ATP · raw +0.08
Execution +0.83 ±0.20 better than 92% of ATP · raw +0.72
Tactical adaptability +0.12 first serves toward what's working, set to set · 191 matches
Adaptation speed +0.12 same, every two to three service games · per 100 first serves
Long-rally execution −0.25 ±0.34 shot 9 on v own earlier rally shots · 12,165 shots · better than 45% of ATP
Points left on the table 2.45 per 100 shots vs best direction · lower than 67% 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 82,911 shots.

Shot expected value

The share of points Alexander Zverev 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 · 4,815 shots

OptionUsedWin %Tour
BH crosscourt 50% 48.7%±1.7 47.6%
BH through the middle 22% 43.1%±2.5 43.7%
BH down the line 13% 48.6%±3.3 46.4%
BH slice through the middle 4% 31.3%±5.2 35.1%
BH slice crosscourt 4% 30.6%±5.2 42.5%
FH inside-in 2% 49.9%±8.6 54.7%
FH inside-out 1% 51.6%±8.9 51.8%
BH slice down the line 1% 31.7%±10.3 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 4,350 shots

OptionUsedWin %Tour
FH down the line 21% 48.6%±2.7 51.5%
FH crosscourt 19% 54.7%±2.8 52.7%
BH crosscourt 17% 51.0%±3.0 49.1%
FH through the middle 16% 48.0%±3.1 47.0%
BH through the middle 14% 51.1%±3.3 46.8%
BH down the line 7% 52.0%±4.5 48.3%
FH down the line + approach 1% 75.9%±8.4 70.5%
BH crosscourt + approach 1% 65.8%±10.6 67.7%

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

position worth 44% to the average player · 4,304 shots

OptionUsedWin %Tour
FH crosscourt 43% 47.8%±1.9 46.6%
FH through the middle 27% 44.9%±2.4 41.5%
FH down the line 20% 43.2%±2.7 44.7%
FH slice through the middle 5% 25.5%±4.8 24.5%
FH slice crosscourt 2% 25.2%±6.5 30.9%
FH down the line + approach 1% 72.1%±9.2 69.3%
FH slice down the line 1% 25.2%±9.9 25.6%
FH through the middle + approach 0% 64.6%±14.4 56.9%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 3,386 shots

OptionUsedWin %Tour
BH crosscourt 48% 50.9%±2.0 48.0%
BH through the middle 22% 44.2%±3.0 43.8%
BH down the line 11% 44.1%±4.0 46.5%
BH slice crosscourt 6% 37.7%±5.2 42.1%
BH slice through the middle 6% 28.8%±5.0 35.1%
FH inside-in 1% 52.3%±10.7 54.3%
FH inside-out 1% 59.9%±11.3 52.6%
BH slice down the line 1% 29.5%±10.8 35.8%

Serve under pressure

Pressure predictability index −7 How much less varied Alexander Zverev's first-serve direction gets on break points. Positive means easier to read. Based on 1103 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 46% 51% 74% / 73%
Body 6% 6% 62% / 63%
T 48% 42% 77% / 75%

7,918 normal · 272 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 45% 39% 75% / 73%
Body 7% 12% 64% / 63%
T 48% 49% 73% / 72%

6,598 normal · 831 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
Wide46% 68.3%±1.2 n=3,774 59% ▲
Body6% 59.4%±3.6 n=484 0% ▼
T48% 67.2%±1.2 n=3,932 41% ▼

Off equilibrium (p < 0.001): serve wide more. Gap 1.0 points per 100 first serves.
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide44% 65.6%±1.4 n=3,284 51% ▲
Body8% 63.3%±3.2 n=571 0% ▼
T48% 65.4%±1.3 n=3,574 49%

Consistent with an optimal mix (p = 0.52).
Optimal mix: +0.3 per 100 first serves.

Exploitability 0.48 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: +0.2±1.3 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. (5,666 repeats, 9,563 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 429 35% −1.7±3.7
1stAd courtT 2,155 29% +1.5±1.6
1stAd courtWide 2,169 26% −1.7±1.5
1stDeuce courtBody 500 40% +3.1±3.5
1stDeuce courtT 2,152 26% +1.1±1.5
1stDeuce courtWide 2,882 26% −0.7±1.3
2ndAd courtBody 1,067 49% −0.3±2.5
2ndAd courtT 589 51% +2.2±3.3
2ndAd courtWide 1,290 50% +2.1±2.3
2ndDeuce courtBody 1,046 50% +1.2±2.5
2ndDeuce courtT 974 51% +1.8±2.6
2ndDeuce courtWide 939 48% +0.1±2.6

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.3% · won 65% · −4.6±4.1 vs own baseline
  2. T serve (deuce court) → FH crosscourt used 2.8% · won 60% · −9.4±3.8 vs own baseline
  3. T serve (ad court) → FH crosscourt used 2.3% · won 58% · −12.0±4.2 vs own baseline
  4. Wide serve (deuce court) → FH down the line used 2.3% · won 57% · −12.9±4.2 vs own baseline
  5. T serve (ad court) → FH down the line used 2.3% · won 56% · −13.9±4.2 vs own baseline

Return

  1. vs wide serve (deuce court) → FH through the middle, deep used 2.2% · won 53% · +14.6±4.4 vs own baseline
  2. vs T serve (ad court) → FH through the middle, deep used 2.0% · won 53% · +14.1±4.6 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, deep used 2.0% · won 53% · +14.0±4.7 vs own baseline
  4. vs T serve (ad court) → FH through the middle, mid used 3.0% · won 50% · +11.4±3.9 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, mid used 4.1% · won 47% · +8.6±3.3 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH crosscourt used 3.6% · won 52% · +5.1±2.9 vs own baseline
  2. BH crosscourt → BH crosscourt used 5.8% · won 50% · +2.9±2.2 vs own baseline
  3. FH down the line → FH crosscourt used 1.5% · won 52% · +5.3±4.4 vs own baseline
  4. FH through the middle → FH crosscourt used 2.4% · won 51% · +3.9±3.5 vs own baseline
  5. BH crosscourt → BH down the line used 2.9% · won 50% · +3.4±3.2 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 Zverev wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.

  1. T serve → FH through the middle return, short → FH crosscourt + approach used 0.1% · won 69% · +21.0±9.4 vs own baseline · +11.8 vs tour on the same sequence Disrupted by Rafael Nadal (4/6)
  2. BH through the middle → BH through the middle → FH crosscourt used 0.2% · won 63% · +14.8±7.8 vs own baseline · +17.2 vs tour on the same sequence Disrupted by Daniil Medvedev (3/7), Novak Djokovic (3/6)
  3. Wide serve → BH through the middle return, mid → FH crosscourt used 0.2% · won 61% · +12.8±7.1 vs own baseline · +5.6 vs tour on the same sequence Disrupted by Dominic Thiem (3/8), Jannik Sinner (8/18)
  4. Wide serve → FH crosscourt return, short → FH down the line + approach used 0.1% · won 69% · +20.4±10.7 vs own baseline · +11.4 vs tour on the same sequence
  5. Wide serve → BH crosscourt return, mid → BH down the line used 0.1% · won 61% · +12.8±8.4 vs own baseline · +15.2 vs tour on the same sequence Disrupted by Jannik Sinner (4/7), Daniil Medvedev (8/13)
  6. FH through the middle → BH through the middle → FH crosscourt used 0.2% · won 60% · +11.7±8.1 vs own baseline · +12.7 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

Smash to their backhand · rally+3.8182
Wide 1st serve · deuce court+3.13,753
BH to their forehand · serve +1+2.8991
T 1st serve · ad court+2.43,555
BH drop shot to their forehand · rally+2.4154

Most exposed to

FH drop shot to their backhand · serve +1−8.5145
BH volley to their backhand · rally−5.6226
BH volley to their forehand · rally−4.8260
FH volley to their forehand · serve +1−3.4124
BH drop shot to their forehand · rally−3.3276

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 +1.98, Pedro Martinez +1.79, Nishesh Basavareddy +1.77, Roberto Bautista Agut +1.74

Favourable matchups

Fabian Marozsan +1.80, Pedro Martinez +1.77, Miomir Kecmanovic +1.77, Roberto Carballes Baena +1.64, Alexander Shevchenko +1.64

Active players who are best at the shot in the top weakness: Lorenzo Musetti, Carlos Alcaraz, Alexander Bublik

Tactical fingerprint

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

1st serve in69%
T serves · ad48%
Avg rally length4.3
T serves · deuce48%
Wide serves · deuce46%
FH down the line32%
Through the middle25%
Deep returns26%
BH down the line19%
Points at net11%
Serve & volley3%
Forehand share51%
Drop shots / shot1.0%
Unforced errors / shot8.6%
Point-ending shots20.6%
Backhand slice12%
Chipped returns7%
Wide serves · ad44%
Run-around forehands8%

Plays most like

  1. Denis Istomin 2006–2021 plan v
  2. Novak Djokovic 2005–2026 plan v
  3. Nikolay Davydenko 2002–2014 plan v
  4. Karen Khachanov 2015–2026 plan v
  5. Daniil Medvedev 2017–2026 plan v
  6. Borna Coric 2015–2025 plan v
  7. Taro Daniel 2014–2024 plan v
  8. Alexandre Muller 2023–2025 plan v

Closest from another era

  1. Andrei Pavel 1999–2006
  2. Jiri Novak 1996–2004
  3. Michael Chang 1989–1998

Charted matches