RallyIQ

ATP · Right-handed · 8 charted matches · 2013–2022

Ricardas Berankis

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

Against an average opponent

Serve points won 61.7% ±3.7 raw 55.8% · tour 63.4% · 611 points
Return points won 38.4% ±3.7 raw 36.1% · tour 36.6% · 554 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 ±0.13 better than 47% of ATP · raw −0.04
Shot selection +0.30 ±0.24 better than 79% of ATP · raw +0.29
Execution −1.82 ±0.66 better than 6% of ATP · raw −1.87

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 2,752 shots.

Shot expected value

The share of points Ricardas Berankis 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 · 139 shots

OptionUsedWin %Tour
BH crosscourt 32% 50.0%±10.2 47.6%
BH down the line 26% 54.1%±11.0 46.4%
BH through the middle 24% 45.8%±11.2 43.7%
BH slice crosscourt 9% 39.1%±14.2 42.5%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 133 shots

OptionUsedWin %Tour
FH down the line 22% 51.6%±11.7 51.5%
FH crosscourt 20% 49.0%±12.1 52.7%
FH through the middle 17% 38.1%±12.2 47.0%
BH through the middle 13% 38.8%±13.2 46.8%
BH crosscourt 11% 50.9%±13.9 49.1%
BH down the line 8% 48.8%±15.0 48.3%

Serve +1: mid-depth return to your middle

position worth 54% to the average player · 102 shots

OptionUsedWin %Tour
FH crosscourt 22% 55.2%±12.6 56.0%
FH through the middle 19% 44.8%±13.1 47.3%
FH down the line 18% 54.4%±13.3 53.4%
BH crosscourt 16% 52.5%±13.7 49.5%
BH through the middle 15% 44.1%±13.8 47.3%

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

position worth 44% to the average player · 86 shots

OptionUsedWin %Tour
FH crosscourt 40% 43.2%±11.1 46.6%
FH down the line 40% 42.5%±11.1 44.7%
FH through the middle 21% 37.6%±12.9 41.5%

Serve under pressure

Pressure predictability index +8 How much less varied Ricardas Berankis's first-serve direction gets on break points. Positive means easier to read. Based on 71 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 31% 31% 64% / 73%
Body 15% 19% 59% / 63%
T 54% 50% 70% / 75%

303 normal · 16 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 40% 40% 63% / 73%
Body 12% 5% 52% / 63%
T 49% 55% 68% / 72%

232 normal · 55 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
Wide31% 54.5%±7.2 n=99 44% ▲
Body15% 53.1%±9.2 n=49 2% ▼
T54% 58.3%±5.7 n=171 54%

Consistent with an optimal mix (p = 0.56).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide40% 55.7%±6.8 n=114 37% ▼
Body10% 46.6%±10.6 n=30 0% ▼
T50% 58.2%±6.2 n=143 63% ▲

Consistent with an optimal mix (p = 0.09).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.55 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: +1.2±6.2 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. (231 repeats, 359 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 21 26% −11.3±10.1
1stAd courtT 73 30% +1.5±7.4
1stAd courtWide 80 29% +2.0±7.1
1stDeuce courtBody 29 34% −2.8±10.1
1stDeuce courtT 67 25% +0.2±7.3
1stDeuce courtWide 82 27% −0.3±6.9
2ndAd courtBody 34 50% +0.3±10.3
2ndAd courtT 21 53% +3.2±11.5
2ndAd courtWide 34 46% −2.3±10.3
2ndDeuce courtBody 45 54% +5.3±9.5
2ndDeuce courtT 32 47% −3.1±10.4
2ndDeuce courtWide 35 51% +3.3±10.2

Signature patterns

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

Serve → +1

  1. Body serve (deuce court) → BH crosscourt used 7.4% · won 56% · −9.9±11.0 vs own baseline

Return

  1. Not enough data

Rally, consecutive own shots

  1. BH crosscourt → BH down the line used 10.8% · won 45% · −0.1±11.8 vs own baseline
  2. FH crosscourt → FH down the line used 10.8% · won 41% · −4.1±11.7 vs own baseline

Discovered sequences

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

  1. BH crosscourt → BH crosscourt → BH down the line used 1.2% · won 51% · +3.3±12.9 vs own baseline · +8.6 vs tour on the same sequence Disrupted by Gael Monfils (3/6)
  2. FH crosscourt → FH crosscourt → FH down the line used 1.2% · won 39% · −8.9±12.6 vs own baseline · −21.8 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

T 1st serve · deuce court−1.5171
FH to their backhand · rally−1.5135
T 1st serve · ad court−2.0143

Most exposed to

BH to the middle · return−2.3144
BH to their backhand · rally−1.6128
Wide 1st serve · deuce court−0.3125
Wide 1st serve · ad court±0.0136
FH to their backhand · rally+1.6120

Active players who are best at the shot in the top weakness: Juan Carlos Prado Angelo, Cameron Norrie, Daniil Medvedev, Dusan Lajovic, Ugo Humbert

Tactical fingerprint

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

Deep returns40%
T serves · ad50%
Unforced errors / shot13.0%
T serves · deuce54%
Point-ending shots29.6%
FH down the line35%
BH down the line26%
Points at net13%
Drop shots / shot1.5%
Through the middle25%
Chipped returns14%
Backhand slice17%
Forehand share51%
Serve & volley0%
Run-around forehands14%
Avg rally length3.5
1st serve in57%
Wide serves · ad40%
Wide serves · deuce31%

Plays most like

  1. Zhizhen Zhang 2019–2026 plan v
  2. Denis Kudla 2014–2021 plan v
  3. Tomas Machac 2020–2026 plan v
  4. Lucas Pouille 2015–2024 plan v
  5. Benjamin Bonzi 2021–2025 plan v
  6. Kevin Anderson 2011–2022 plan v
  7. Peter Gojowczyk 2014–2022 plan v
  8. Ethan Quinn 2024–2026 plan v

Closest from another era

  1. Thomas Enqvist 1993–2001
  2. Malivai Washington 1992–1996
  3. Guy Forget 1991–1996

Charted matches