RallyIQ

ATP · Right-handed · 125 charted matches · 2019–2026

Lorenzo Musetti

Archetype: Avoids the wide serve · Ad-court slider

Against an average opponent

Serve points won 64.9% ±2.3 raw 63.1% · tour 63.4% · 10,155 points
Return points won 40.2% ±2.4 raw 37.7% · tour 36.6% · 10,356 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 −0.02 ±0.04 better than 50% of ATP · raw −0.02
Shot selection −0.57 ±0.10 better than 9% of ATP · raw −0.56
Execution +0.48 ±0.22 better than 83% of ATP · raw +0.55
Tactical adaptability +0.14 first serves toward what's working, set to set · 123 matches
Adaptation speed ±0.00 same, every two to three service games · per 100 first serves
Long-rally execution −0.16 ±0.39 shot 9 on v own earlier rally shots · 7,165 shots · better than 55% of ATP
Points left on the table 2.74 per 100 shots vs best direction · lower than 35% 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 55,041 shots.

Shot expected value

The share of points Lorenzo Musetti 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 · 4,384 shots

OptionUsedWin %Tour
BH crosscourt 25% 49.6%±2.5 47.6%
BH slice crosscourt 18% 44.5%±2.9 42.5%
BH through the middle 13% 45.3%±3.3 43.7%
BH down the line 11% 47.4%±3.6 46.4%
BH slice through the middle 9% 43.5%±4.0 35.1%
FH inside-out 8% 55.4%±4.2 51.8%
BH slice down the line 4% 41.3%±5.5 37.1%
FH inside-in 4% 58.6%±5.9 54.7%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 2,564 shots

OptionUsedWin %Tour
BH crosscourt 26% 49.4%±3.1 48.0%
BH slice crosscourt 23% 46.8%±3.3 42.1%
BH through the middle 13% 45.3%±4.4 43.8%
BH down the line 11% 46.5%±4.7 46.5%
BH slice through the middle 10% 42.6%±4.8 35.1%
BH slice down the line 5% 42.4%±6.5 35.8%
FH inside-out 5% 57.9%±6.9 52.6%
FH inside-in 3% 57.0%±8.2 54.3%

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

position worth 44% to the average player · 2,539 shots

OptionUsedWin %Tour
FH crosscourt 38% 50.2%±2.6 46.6%
FH through the middle 25% 42.1%±3.2 41.5%
FH down the line 24% 42.8%±3.2 44.7%
FH slice through the middle 4% 28.6%±6.9 24.5%
FH slice crosscourt 3% 27.3%±7.9 30.9%
FH slice down the line 2% 20.5%±8.3 25.6%
FH down the line + approach 1% 73.3%±10.0 69.3%
FH lob through the middle 1% 25.9%±11.3 23.0%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 2,299 shots

OptionUsedWin %Tour
FH down the line 25% 56.5%±3.3 51.5%
FH crosscourt 21% 54.2%±3.7 52.7%
FH through the middle 18% 50.8%±3.9 47.0%
BH through the middle 6% 44.2%±6.7 46.8%
BH down the line 6% 48.1%±6.7 48.3%
BH slice through the middle 5% 43.4%±6.8 44.8%
BH crosscourt 5% 44.2%±7.3 49.1%
BH slice crosscourt 4% 44.4%±7.5 47.0%

Serve under pressure

Pressure predictability index +7 How much less varied Lorenzo Musetti's first-serve direction gets on break points. Positive means easier to read. Based on 814 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 41% 44% 70% / 73%
Body 9% 8% 64% / 63%
T 49% 48% 72% / 75%

5,129 normal · 194 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 54% 61% 69% / 73%
Body 9% 6% 61% / 63%
T 37% 33% 69% / 72%

4,211 normal · 620 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% 63.2%±1.7 n=2,196 38% ▼
Body9% 62.2%±3.5 n=496 0% ▼
T49% 65.0%±1.5 n=2,631 62% ▲

Consistent with an optimal mix (p = 0.26).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide55% 62.3%±1.5 n=2,658 50% ▼
Body8% 58.8%±3.9 n=396 0% ▼
T37% 62.4%±1.9 n=1,777 50% ▲

Consistent with an optimal mix (p = 0.31).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.44 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: −0.9±1.7 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. (4,407 repeats, 5,499 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 253 37% +0.5±4.7
1stAd courtT 1,264 29% +0.7±2.1
1stAd courtWide 1,639 32% +5.1±1.9
1stDeuce courtBody 354 39% +2.1±4.1
1stDeuce courtT 1,466 29% +3.6±1.9
1stDeuce courtWide 1,613 28% +0.9±1.8
2ndAd courtBody 364 50% +0.6±4.1
2ndAd courtT 243 54% +5.2±5.0
2ndAd courtWide 1,189 48% −0.1±2.4
2ndDeuce courtBody 642 53% +4.1±3.2
2ndDeuce courtT 845 51% +1.7±2.8
2ndDeuce courtWide 477 49% +1.3±3.7

Signature patterns

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

Serve → +1

  1. Wide serve (deuce court) → FH crosscourt used 2.4% · won 62% · −3.2±4.9 vs own baseline
  2. T serve (ad court) → FH down the line used 2.2% · won 61% · −3.9±5.2 vs own baseline
  3. Wide serve (ad court) → FH crosscourt used 2.3% · won 61% · −4.6±5.0 vs own baseline
  4. T serve (deuce court) → FH crosscourt used 3.8% · won 59% · −5.8±4.1 vs own baseline
  5. T serve (ad court) → FH crosscourt used 2.2% · won 57% · −8.6±5.3 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 4.8% · won 49% · +9.6±3.8 vs own baseline
  2. vs T serve (ad court) → FH through the middle, mid used 2.4% · won 52% · +12.5±5.3 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 2.3% · won 51% · +11.3±5.4 vs own baseline
  4. vs wide serve (ad court) → BH through the middle, deep used 2.2% · won 48% · +7.8±5.5 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, short used 2.1% · won 46% · +6.5±5.6 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH crosscourt used 2.7% · won 56% · +7.6±4.2 vs own baseline
  2. FH down the line → FH crosscourt used 1.1% · won 58% · +9.2±6.2 vs own baseline
  3. BH crosscourt → FH crosscourt used 1.8% · won 55% · +7.1±5.1 vs own baseline
  4. FH down the line → FH inside-out used 1.1% · won 57% · +8.6±6.3 vs own baseline
  5. FH through the middle → FH down the line used 1.6% · won 54% · +5.5±5.4 vs own baseline

Discovered sequences

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

  1. BH crosscourt → BH through the middle → FH crosscourt used 0.3% · won 62% · +12.4±7.4 vs own baseline · +12.1 vs tour on the same sequence Disrupted by Novak Djokovic (8/13), Alex De Minaur (8/10)
  2. FH through the middle → FH through the middle → FH through the middle used 0.3% · won 62% · +12.3±7.9 vs own baseline · +19.1 vs tour on the same sequence Disrupted by Alex De Minaur (3/6), Taylor Fritz (4/6)
  3. FH down the line → BH crosscourt → BH crosscourt used 0.7% · won 57% · +7.5±5.4 vs own baseline · +8.9 vs tour on the same sequence Disrupted by Carlos Alcaraz (5/14), Mariano Navone (3/8)
  4. T serve → BH through the middle return, mid → FH down the line used 0.5% · won 59% · +9.2±6.5 vs own baseline · +6.9 vs tour on the same sequence Disrupted by Stefanos Tsitsipas (3/9), Novak Djokovic (5/12)
  5. BH crosscourt → BH crosscourt → FH inside-in used 0.2% · won 62% · +12.9±8.7 vs own baseline · +12.2 vs tour on the same sequence Disrupted by Roberto Carballes Baena (3/7), Mariano Navone (4/7)
  6. T serve → BH through the middle return, mid → FH crosscourt used 0.4% · won 57% · +8.0±7.0 vs own baseline · +4.7 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

FH drop shot to their backhand · serve +1+3.3253
BH to their backhand · return +1+2.8720
BH lob to the middle · rally+2.7149
FH to the middle · serve +1+2.2815
FH to the middle · return +1+1.9630

Most exposed to

BH to their backhand · return +1−1.41,114
BH to the middle · return−1.42,173
FH volley to their forehand · rally−1.4262
BH volley to their forehand · rally−0.8301
Wide 2nd serve · ad court−0.61,187

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +0.74, Miomir Kecmanovic +0.68, Nishesh Basavareddy +0.44, Daniil Medvedev +0.43, Casper Ruud +0.43

Favourable matchups

Miomir Kecmanovic +1.98, Fabian Marozsan +1.92, Roberto Bautista Agut +1.83, Pedro Martinez +1.82, Roberto Carballes Baena +1.78

Active players who are best at the shot in the top weakness: Jesper De Jong, Sebastian Baez, Nishesh Basavareddy, Cameron Norrie, Marcos Giron

Tactical fingerprint

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

Backhand slice38%
BH down the line27%
Drop shots / shot2.8%
1st serve in65%
Avg rally length4.5
Chipped returns24%
Run-around forehands26%
Wide serves · ad55%
T serves · deuce49%
Deep returns30%
Forehand share54%
Through the middle25%
FH down the line29%
Serve & volley3%
T serves · ad37%
Wide serves · deuce41%
Points at net9%
Point-ending shots20.1%
Unforced errors / shot8.1%

Plays most like

  1. Dominic Thiem 2011–2024 plan v
  2. Pedro Martinez 2019–2026 plan v
  3. Learner Tien 2022–2026 plan v
  4. Dusan Lajovic 2014–2025 plan v
  5. Marton Fucsovics 2018–2026 plan v
  6. Philipp Kohlschreiber 2008–2019 plan v
  7. Novak Djokovic 2005–2026 plan v
  8. Robin Haase 2012–2024 plan v

Closest from another era

  1. Tommy Haas 1996–2017
  2. Fernando Gonzalez 2000–2010
  3. David Nalbandian 2002–2012

Charted matches