RallyIQ

ATP · Right-handed · 12 charted matches · 2022–2026

Mariano Navone

Archetype: Avoids the wide serve · Ad-court slider

Against an average opponent

Serve points won 60.4% ±3.4 raw 55.6% · tour 63.4% · 1,067 points
Return points won 39.8% ±3.5 raw 43.1% · tour 36.6% · 1,036 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 −0.01 ±0.09 better than 54% of ATP · raw −0.01
Shot selection −0.08 ±0.23 better than 43% of ATP · raw −0.07
Execution +0.24 ±0.59 better than 77% of ATP · raw +0.35
Tactical adaptability +0.11 first serves toward what's working, set to set · 12 matches
Adaptation speed +0.18 same, every two to three service games · per 100 first serves
Points left on the table 2.33 per 100 shots vs best direction · lower than 81% 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 6,774 shots.

Shot expected value

The share of points Mariano Navone 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 · 570 shots

OptionUsedWin %Tour
BH crosscourt 51% 54.9%±4.7 47.6%
BH through the middle 26% 45.4%±6.3 43.7%
BH down the line 10% 50.4%±9.4 46.4%
FH inside-out 4% 63.0%±11.8 51.8%
FH inside-in 4% 36.4%±12.4 54.7%
BH slice crosscourt 2% 42.6%±14.0 42.5%
BH slice through the middle 2% 36.5%±13.8 35.1%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 427 shots

OptionUsedWin %Tour
BH crosscourt 49% 51.1%±5.4 48.0%
BH through the middle 23% 44.8%±7.5 43.8%
BH down the line 15% 43.0%±9.0 46.5%
FH inside-in 4% 53.9%±13.9 54.3%
BH slice crosscourt 3% 36.5%±13.6 42.1%
FH inside-out 3% 53.3%±14.7 52.6%
BH slice through the middle 2% 30.1%±13.8 35.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 399 shots

OptionUsedWin %Tour
FH crosscourt 27% 51.6%±7.3 52.7%
FH down the line 26% 45.0%±7.3 51.5%
BH crosscourt 19% 50.3%±8.4 49.1%
FH through the middle 12% 51.3%±9.9 47.0%
BH through the middle 12% 36.4%±9.7 46.8%
BH down the line 4% 46.3%±13.7 48.3%

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

position worth 44% to the average player · 381 shots

OptionUsedWin %Tour
FH crosscourt 41% 49.3%±6.3 46.6%
FH down the line 30% 48.5%±7.1 44.7%
FH through the middle 21% 49.8%±8.3 41.5%
FH slice through the middle 4% 19.2%±10.8 24.5%

Serve under pressure

Pressure predictability index +3 How much less varied Mariano Navone's first-serve direction gets on break points. Positive means easier to read. Based on 130 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 32% 32% 64% / 73%
Body 18% 29% ▲ 50% / 63%
T 50% 39% ▼ 65% / 75%

525 normal · 28 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 51% 58% 62% / 73%
Body 20% 23% 59% / 63%
T 29% 20% ▼ 67% / 72%

412 normal · 102 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
Wide32% 55.9%±5.6 n=179 45% ▲
Body18% 44.8%±7.1 n=101 5% ▼
T49% 58.0%±4.7 n=273 50%

Off equilibrium (p = 0.004): serve T more. Gap 3.1 points per 100 first serves.
Optimal mix: +0.9 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide52% 57.5%±4.7 n=268 52%
Body20% 54.9%±7.0 n=105 7% ▼
T27% 56.6%±6.2 n=141 41% ▲

Consistent with an optimal mix (p = 0.82).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.75 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±4.3 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. (449 repeats, 594 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 21 49% +12.2±11.5
1stAd courtT 111 36% +7.7±6.6
1stAd courtWide 188 39% +11.8±5.4
1stDeuce courtBody 32 39% +2.0±10.2
1stDeuce courtT 126 36% +10.5±6.3
1stDeuce courtWide 183 31% +3.9±5.2
2ndAd courtBody 38 48% −1.1±10.0
2ndAd courtT 19 49% −0.7±11.7
2ndAd courtWide 123 50% +1.6±6.6
2ndDeuce courtBody 55 56% +7.1±8.9
2ndDeuce courtT 55 52% +2.0±8.9
2ndDeuce courtWide 85 51% +2.7±7.7

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH inside-in used 2.8% · won 64% · +7.0±10.7 vs own baseline
  2. Body serve (ad court) → FH down the line used 3.3% · won 61% · +4.3±10.5 vs own baseline
  3. Wide serve (ad court) → BH crosscourt used 4.7% · won 60% · +3.0±9.4 vs own baseline
  4. Wide serve (deuce court) → BH crosscourt used 2.5% · won 60% · +2.9±11.2 vs own baseline
  5. Wide serve (ad court) → FH crosscourt used 3.4% · won 58% · +1.7±10.5 vs own baseline

Return

  1. vs wide serve (ad court) → BH through the middle, deep used 5.1% · won 53% · +5.4±10.3 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, mid used 9.7% · won 51% · +3.4±8.3 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 4.3% · won 50% · +3.0±10.8 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, short used 3.8% · won 49% · +2.1±11.1 vs own baseline
  5. vs wide serve (deuce court) → FH crosscourt, mid used 4.5% · won 48% · +0.5±10.7 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → BH crosscourt used 7.9% · won 55% · +5.8±6.1 vs own baseline
  2. FH crosscourt → BH crosscourt used 2.9% · won 58% · +8.5±9.1 vs own baseline
  3. BH down the line → FH down the line used 1.3% · won 61% · +11.7±11.1 vs own baseline
  4. FH through the middle → BH crosscourt used 3.0% · won 56% · +6.4±9.0 vs own baseline
  5. BH crosscourt → FH crosscourt used 5.8% · won 54% · +4.6±7.1 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Mariano Navone 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 crosscourt used 2.8% · won 58% · +7.9±6.8 vs own baseline · +11.3 vs tour on the same sequence Disrupted by Joao Fonseca (7/14), Botic Van De Zandschulp (16/32)
  2. FH crosscourt → FH down the line → BH crosscourt used 0.6% · won 60% · +9.8±11.3 vs own baseline · +20.4 vs tour on the same sequence Disrupted by Brandon Nakashima (5/7), Lorenzo Musetti (6/7)
  3. FH through the middle → FH down the line → BH crosscourt used 0.6% · won 60% · +10.2±11.5 vs own baseline · +24.6 vs tour on the same sequence Disrupted by Lorenzo Musetti (4/7)
  4. FH down the line → BH through the middle → FH crosscourt used 0.9% · won 57% · +6.6±10.4 vs own baseline · +6.5 vs tour on the same sequence Disrupted by Joao Fonseca (3/7), Brandon Nakashima (3/7)
  5. BH through the middle → FH down the line → BH crosscourt used 1.0% · won 56% · +6.2±10.1 vs own baseline · +13.3 vs tour on the same sequence Disrupted by Botic Van De Zandschulp (3/8), Lorenzo Musetti (8/14)
  6. BH crosscourt → FH inside-out → BH crosscourt used 0.7% · won 57% · +6.7±11.3 vs own baseline · +16.0 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 the middle · return+1.9182
BH to the middle · rally+1.5353
BH to their backhand · rally+1.4659
BH to the middle · return+1.2237
BH to their backhand · serve +1+1.0190

Most exposed to

BH to their backhand · return−3.6241
BH to the middle · return−3.1314
FH to the middle · return−2.3152
Wide 2nd serve · ad court−1.8123
BH to their backhand · rally−1.2548

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Miomir Kecmanovic +1.71, Rafael Nadal +1.69, Daniil Medvedev +1.50, Nishesh Basavareddy +1.48, Jack Draper +1.42

Favourable matchups

Miomir Kecmanovic +1.60, Roberto Carballes Baena +1.46, Pedro Martinez +1.37, Arthur Rinderknech +1.34, Fabian Marozsan +1.32

Active players who are best at the shot in the top weakness: Ugo Humbert, Miomir Kecmanovic, Casper Ruud, Zhizhen Zhang, Bernard Tomic

Tactical fingerprint

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

Avg rally length5.5
1st serve in70%
FH down the line34%
Deep returns32%
T serves · deuce49%
Wide serves · ad52%
Run-around forehands21%
Forehand share52%
Through the middle24%
Serve & volley1%
Drop shots / shot0.8%
Points at net8%
Backhand slice10%
Chipped returns6%
Unforced errors / shot8.0%
BH down the line13%
Point-ending shots16.5%
T serves · ad27%
Wide serves · deuce32%

Plays most like

  1. Roberto Bautista Agut 2013–2026 plan v
  2. Pablo Andujar 2013–2023 plan v
  3. Federico Coria 2019–2025 plan v
  4. Roberto Carballes Baena 2017–2024 plan v
  5. Rafael Nadal 2003–2024 plan v
  6. Nikolay Davydenko 2002–2014 plan v
  7. Juan Carlos Ferrero 2000–2009 plan v
  8. Novak Djokovic 2005–2026 plan v

Closest from another era

  1. Nikolay Davydenko 2002–2014
  2. Juan Carlos Ferrero 2000–2009
  3. Gaston Gaudio 2002–2005

Charted matches