RallyIQ

ATP · Right-handed · 9 charted matches · 1999–2006

Andrei Pavel

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 65.4% ±3.3 raw 62.3% · tour 63.4% · 741 points
Return points won 37.1% ±3.5 raw 32.9% · tour 36.6% · 678 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 −0.18 ±0.09 better than 16% of ATP · raw −0.19
Shot selection +0.06 ±0.31 better than 60% of ATP · raw +0.05
Execution +0.16 ±0.60 better than 75% of ATP · raw +0.04
Points left on the table 3.10 per 100 shots vs best direction · lower than 15% 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 3,281 shots.

Shot expected value

The share of points Andrei Pavel 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 · 149 shots

OptionUsedWin %Tour
BH crosscourt 38% 54.6%±9.4 47.6%
BH through the middle 28% 46.4%±10.4 43.7%
BH down the line 10% 52.2%±13.9 46.4%
BH slice through the middle 9% 29.5%±12.9 35.1%
BH slice crosscourt 7% 37.1%±14.3 42.5%

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

position worth 44% to the average player · 144 shots

OptionUsedWin %Tour
FH crosscourt 44% 49.2%±9.0 46.6%
FH through the middle 33% 42.2%±9.9 41.5%
FH down the line 23% 41.4%±11.1 44.7%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 118 shots

OptionUsedWin %Tour
FH through the middle 29% 47.0%±11.2 47.0%
FH crosscourt 24% 51.1%±11.9 52.7%
FH down the line 18% 49.5%±12.8 51.5%
BH crosscourt 10% 46.3%±14.5 49.1%
BH through the middle 8% 51.2%±15.0 46.8%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 98 shots

OptionUsedWin %Tour
BH crosscourt 37% 47.5%±11.0 48.0%
BH through the middle 22% 49.4%±12.7 43.8%
BH slice crosscourt 15% 44.1%±13.8 42.1%
BH down the line 11% 42.9%±14.6 46.5%

Serve under pressure

Pressure predictability index −1 How much less varied Andrei Pavel's first-serve direction gets on break points. Positive means easier to read. Based on 55 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 43% 40% 71% / 73%
Body 8% 20% ▲ 67% / 63%
T 50% 40% ▼ 79% / 75%

357 normal · 5 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 52% 62% ▲ 65% / 73%
Body 4% 6% 62% / 63%
T 44% 32% ▼ 60% / 72%

297 normal · 50 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
Wide43% 64.3%±5.8 n=154 37% ▼
Body8% 62.5%±10.4 n=29 0% ▼
T49% 68.6%±5.3 n=179 63% ▲

Consistent with an optimal mix (p = 0.39).
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide53% 58.1%±5.5 n=185 66% ▲
Body4% 54.6%±12.2 n=15 0% ▼
T42% 53.6%±6.2 n=147 34% ▼

Consistent with an optimal mix (p = 0.30).
Optimal mix: +0.1 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: −0.5±7.2 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. (316 repeats, 375 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 12 36% −1.0±12.2
1stAd courtT 89 27% −0.8±6.7
1stAd courtWide 88 25% −2.5±6.5
1stDeuce courtBody 11 32% −5.0±12.0
1stDeuce courtT 91 22% −3.2±6.2
1stDeuce courtWide 101 21% −6.5±5.8
2ndAd courtBody 25 56% +6.6±11.0
2ndAd courtT 19 42% −6.9±11.6
2ndAd courtWide 80 53% +4.8±7.8
2ndDeuce courtBody 48 51% +1.9±9.3
2ndDeuce courtT 52 46% −3.5±9.1
2ndDeuce courtWide 37 45% −2.7±10.0

Signature patterns

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

Serve → +1

  1. Not enough data

Return

  1. Not enough data

Rally, consecutive own shots

  1. BH through the middle → FH crosscourt used 7.7% · won 51% · +2.7±10.8 vs own baseline
  2. BH crosscourt → BH crosscourt used 6.1% · won 51% · +2.7±11.5 vs own baseline
  3. FH crosscourt → FH through the middle used 5.5% · won 51% · +2.8±11.8 vs own baseline
  4. BH crosscourt → FH crosscourt used 5.5% · won 51% · +2.8±11.8 vs own baseline
  5. FH through the middle → BH crosscourt used 6.1% · won 49% · +0.8±11.5 vs own baseline

Discovered sequences

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

  1. BH through the middle → FH crosscourt → FH crosscourt used 1.6% · won 55% · +4.7±11.6 vs own baseline · +15.1 vs tour on the same sequence Disrupted by Andre Agassi (6/10)
  2. FH crosscourt → FH crosscourt → FH through the middle used 1.3% · won 50% · −0.2±12.3 vs own baseline · +5.4 vs tour on the same sequence Disrupted by Jiri Novak (5/8)
  3. BH crosscourt → BH crosscourt → BH crosscourt used 1.3% · won 50% · −0.2±12.3 vs own baseline · +1.6 vs tour on the same sequence Disrupted by Andre Agassi (5/12)
  4. FH down the line → BH crosscourt → BH crosscourt used 1.4% · won 50% · −0.2±12.0 vs own baseline · +1.1 vs tour on the same sequence Disrupted by Andre Agassi (5/10)
  5. FH crosscourt → FH crosscourt → FH crosscourt used 1.4% · won 50% · −0.2±12.0 vs own baseline · +1.2 vs tour on the same sequence
  6. FH through the middle → FH crosscourt → FH crosscourt used 1.1% · won 44% · −6.2±12.6 vs own baseline · −10.6 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

FH to their backhand · rally+0.7129
BH to their backhand · rally+0.4151
T 1st serve · deuce court+0.2179
Wide 1st serve · deuce court+0.1154
FH to the middle · rally−0.2143

Most exposed to

T 1st serve · ad court−2.7127
T 1st serve · deuce court−0.4150
FH to the middle · return−0.3124
FH to their forehand · rally−0.3218
Wide 1st serve · ad court+0.1167

Active players who are best at the shot in the top weakness: Reilly Opelka, Milos Raonic, Nick Kyrgios, Nicolas Jarry, Giovanni Mpetshi Perricard

Tactical fingerprint

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

Through the middle32%
Chipped returns24%
Points at net16%
T serves · deuce49%
Serve & volley18%
T serves · ad42%
Wide serves · ad53%
BH down the line23%
1st serve in62%
Point-ending shots24.4%
Forehand share53%
Wide serves · deuce43%
Drop shots / shot1.3%
Avg rally length3.8
Backhand slice17%
FH down the line29%
Unforced errors / shot8.9%
Run-around forehands8%
Deep returns18%

Plays most like

  1. Ivan Ljubicic 2003–2011 plan v
  2. Paolo Lorenzi 2014–2019 plan v
  3. Roger Federer 1998–2021 plan v
  4. Gael Monfils 2005–2026 plan v
  5. Richard Gasquet 2002–2025 plan v
  6. Andreas Seppi 2008–2021 plan v
  7. Flavio Cobolli 2022–2026 plan v
  8. Mackenzie Mcdonald 2015–2025 plan v

Closest from another era

  1. Flavio Cobolli 2022–2026
  2. Mackenzie Mcdonald 2015–2025
  3. Jiri Lehecka 2019–2026

Charted matches