RallyIQ

ATP · Right-handed · 8 charted matches · 2022–2025

Luca Nardi

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 61.3% ±3.5 raw 58.1% · tour 63.4% · 613 points
Return points won 34.8% ±3.6 raw 29.7% · tour 36.6% · 543 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 ±0.12 better than 59% of ATP · raw ±0.00
Shot selection −0.20 ±0.39 better than 30% of ATP · raw −0.22
Execution −1.30 ±1.09 better than 16% of ATP · raw −1.55
Points left on the table 2.26 per 100 shots vs best direction · lower than 87% 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 3,030 shots.

Shot expected value

The share of points Luca Nardi 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 · 216 shots

OptionUsedWin %Tour
BH crosscourt 48% 45.1%±7.4 47.6%
BH through the middle 26% 39.9%±9.2 43.7%
BH slice crosscourt 9% 43.7%±12.9 42.5%
BH slice through the middle 6% 31.3%±13.5 35.1%
BH down the line 5% 37.6%±14.5 46.4%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 139 shots

OptionUsedWin %Tour
FH crosscourt 25% 51.9%±11.1 52.7%
BH through the middle 22% 48.7%±11.6 46.8%
BH crosscourt 18% 46.3%±12.2 49.1%
FH down the line 18% 47.3%±12.2 51.5%
FH through the middle 17% 48.6%±12.4 47.0%

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

position worth 44% to the average player · 121 shots

OptionUsedWin %Tour
FH crosscourt 44% 44.3%±9.6 46.6%
FH down the line 26% 47.0%±11.5 44.7%
FH through the middle 25% 36.6%±11.2 41.5%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 101 shots

OptionUsedWin %Tour
BH crosscourt 47% 32.2%±9.4 48.0%
BH through the middle 22% 54.2%±12.6 43.8%
BH down the line 15% 55.1%±13.8 46.5%
BH slice crosscourt 12% 38.8%±14.2 42.1%

Serve under pressure

Pressure predictability index +3 How much less varied Luca Nardi's first-serve direction gets on break points. Positive means easier to read. Based on 64 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 45% 58% ▲ 69% / 73%
Body 16% 17% 63% / 63%
T 38% 25% ▼ 71% / 75%

306 normal · 12 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 50% 44% 73% / 73%
Body 14% 12% 54% / 63%
T 36% 44% ▲ 69% / 72%

243 normal · 52 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% 58.2%±6.1 n=146 59% ▲
Body16% 57.3%±9.0 n=52 3% ▼
T38% 57.8%±6.6 n=120 38%

Consistent with an optimal mix (p = 0.98).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide49% 61.0%±6.1 n=145 61% ▲
Body14% 50.1%±9.8 n=40 0% ▼
T37% 59.0%±6.8 n=110 39% ▲

Consistent with an optimal mix (p = 0.10).
Optimal mix: +0.7 per 100 first serves.

Exploitability 0.57 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: +8.8±6.9 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. (206 repeats, 391 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 23 28% −8.5±10.2
1stAd courtT 56 23% −5.5±7.4
1stAd courtWide 70 23% −4.1±6.9
1stDeuce courtBody 38 35% −1.4±9.5
1stDeuce courtT 74 24% −1.5±6.8
1stDeuce courtWide 82 22% −5.6±6.4
2ndAd courtBody 49 45% −4.0±9.2
2ndAd courtT 22 38% −11.2±11.1
2ndAd courtWide 33 37% −11.0±10.0
2ndDeuce courtBody 38 47% −2.4±10.0
2ndDeuce courtT 41 48% −1.9±9.8
2ndDeuce courtWide 17 60% +12.4±11.7

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 7.6% · won 67% · +1.2±10.5 vs own baseline
  2. Body serve (deuce court) → BH crosscourt used 7.0% · won 63% · −2.0±10.9 vs own baseline
  3. T serve (deuce court) → BH crosscourt used 6.7% · won 57% · −8.5±11.3 vs own baseline

Return

  1. Not enough data

Rally, consecutive own shots

  1. BH through the middle → FH crosscourt used 6.9% · won 56% · +8.0±10.7 vs own baseline
  2. BH crosscourt → FH crosscourt used 5.4% · won 51% · +2.9±11.5 vs own baseline
  3. FH crosscourt → FH down the line used 4.9% · won 51% · +2.9±11.8 vs own baseline
  4. FH crosscourt → FH crosscourt used 5.1% · won 50% · +1.9±11.6 vs own baseline
  5. BH crosscourt → BH through the middle used 6.4% · won 45% · −2.5±11.0 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Luca Nardi 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 1.0% · won 56% · +10.4±13.0 vs own baseline · +20.2 vs tour on the same sequence
  2. BH through the middle → FH crosscourt → FH crosscourt used 1.4% · won 54% · +8.4±12.0 vs own baseline · +18.7 vs tour on the same sequence Disrupted by Carlos Alcaraz (5/6)
  3. FH crosscourt → FH crosscourt → FH down the line used 1.4% · won 52% · +6.3±12.0 vs own baseline · +12.3 vs tour on the same sequence Disrupted by Novak Djokovic (3/7)
  4. FH crosscourt → FH crosscourt → FH crosscourt used 1.5% · won 49% · +3.1±11.9 vs own baseline · +3.4 vs tour on the same sequence
  5. BH crosscourt → BH crosscourt → BH down the line used 1.1% · won 49% · +2.9±12.7 vs own baseline · +5.3 vs tour on the same sequence Disrupted by Novak Djokovic (3/6)
  6. BH crosscourt → BH crosscourt → BH through the middle used 1.2% · won 48% · +1.8±12.6 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

BH to the middle · rally+0.8125
Wide 1st serve · ad court−0.6145
FH to their forehand · rally−0.8184
FH to their backhand · rally−2.0121
T 1st serve · deuce court−2.5120

Most exposed to

BH to the middle · return−0.8126
FH to their forehand · rally−0.1172
T 1st serve · deuce court+0.3126
BH to their backhand · rally+0.3190
FH to their backhand · rally+0.7159

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.

Drop shots / shot2.5%
Unforced errors / shot11.1%
Through the middle27%
Wide serves · deuce46%
1st serve in62%
Deep returns28%
Avg rally length4.1
Chipped returns16%
Point-ending shots23.1%
Wide serves · ad49%
T serves · ad37%
Run-around forehands16%
Points at net10%
Serve & volley1%
Backhand slice15%
Forehand share50%
FH down the line27%
T serves · deuce38%
BH down the line12%

Plays most like

  1. Alejandro Tabilo 2021–2026 plan v
  2. Alexandre Muller 2023–2025 plan v
  3. Gregoire Barrere 2016–2024 plan v
  4. Ilya Ivashka 2018–2023 plan v
  5. Jannik Sinner 2013–2026 plan v
  6. Pablo Carreno Busta 2015–2026 plan v
  7. Carlos Alcaraz 2019–2026 plan v
  8. Alexander Shevchenko 2023–2026 plan v

Closest from another era

  1. Ivan Ljubicic 2003–2011
  2. Magnus Norman 2000–2001
  3. David Nalbandian 2002–2012

Charted matches