RallyIQ

ATP · Right-handed · 222 charted matches · 2019–2026

Carlos Alcaraz

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 68.1% ±2.1 raw 66.5% · tour 63.4% · 17,668 points
Return points won 43.2% ±2.4 raw 41.2% · tour 36.6% · 19,237 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 +0.08 ±0.03 better than 77% of ATP · raw +0.08
Shot selection +0.20 ±0.07 better than 73% of ATP · raw +0.20
Execution +0.54 ±0.21 better than 85% of ATP · raw +0.55
Tactical adaptability +0.11 first serves toward what's working, set to set · 219 matches
Adaptation speed +0.13 same, every two to three service games · per 100 first serves
Long-rally execution −0.64 ±0.37 shot 9 on v own earlier rally shots · 8,923 shots · better than 8% of ATP
Points left on the table 2.43 per 100 shots vs best direction · lower than 70% 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 91,583 shots.

Shot expected value

The share of points Carlos Alcaraz 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 · 6,709 shots

OptionUsedWin %Tour
BH crosscourt 42% 50.6%±1.5 47.6%
BH through the middle 17% 48.1%±2.4 43.7%
BH down the line 11% 52.0%±3.0 46.4%
BH slice crosscourt 7% 48.4%±3.8 42.5%
FH inside-out 6% 55.8%±3.9 51.8%
FH inside-in 5% 59.7%±4.4 54.7%
BH slice through the middle 4% 34.9%±4.8 35.1%
BH slice down the line 2% 48.1%±6.4 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 4,103 shots

OptionUsedWin %Tour
FH crosscourt 31% 58.1%±2.3 52.7%
FH down the line 18% 56.2%±3.0 51.5%
FH through the middle 14% 49.8%±3.4 47.0%
BH crosscourt 12% 51.3%±3.7 49.1%
BH through the middle 9% 48.6%±4.3 46.8%
BH down the line 3% 54.4%±6.4 48.3%
FH drop shot down the line 3% 64.8%±7.1 56.5%
FH down the line + approach 2% 70.5%±7.6 70.5%

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

position worth 44% to the average player · 3,751 shots

OptionUsedWin %Tour
FH crosscourt 43% 50.2%±2.0 46.6%
FH down the line 20% 50.0%±3.0 44.7%
FH through the middle 19% 43.0%±3.0 41.5%
FH slice through the middle 7% 32.2%±4.6 24.5%
FH slice crosscourt 4% 39.1%±6.5 30.9%
FH slice down the line 3% 30.4%±6.9 25.6%
FH down the line + approach 1% 76.5%±8.2 69.3%
FH drop shot down the line 1% 59.0%±10.0 49.6%

Return +1: drive to your backhand side

position worth 44% to the average player · 3,731 shots

OptionUsedWin %Tour
BH crosscourt 44% 51.5%±2.0 46.9%
BH through the middle 19% 48.2%±3.1 43.0%
BH down the line 9% 45.7%±4.4 44.2%
BH slice crosscourt 9% 49.0%±4.4 40.9%
BH slice through the middle 5% 31.9%±5.2 32.6%
FH inside-out 4% 57.9%±6.5 51.7%
FH inside-in 3% 54.6%±7.0 53.6%
BH slice down the line 2% 37.0%±7.6 33.3%

Serve under pressure

Pressure predictability index −2 How much less varied Carlos Alcaraz's first-serve direction gets on break points. Positive means easier to read. Based on 1204 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 46% 46% 73% / 73%
Body 17% 20% 67% / 63%
T 37% 35% 77% / 75%

8,977 normal · 301 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 51% 72% / 73%
Body 16% 20% 66% / 63%
T 35% 29% 72% / 72%

7,445 normal · 903 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% 67.7%±1.2 n=4,259 54% ▲
Body18% 65.9%±1.9 n=1,624 4% ▼
T37% 67.3%±1.3 n=3,395 42% ▲

Consistent with an optimal mix (p = 0.41).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide49% 65.7%±1.2 n=4,127 50%
Body16% 64.3%±2.1 n=1,351 3% ▼
T34% 66.4%±1.4 n=2,870 47% ▲

Consistent with an optimal mix (p = 0.35).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.48 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: +0.8±1.2 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. (6,083 repeats, 11,101 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 523 42% +4.6±3.4
1stAd courtT 2,219 35% +6.6±1.7
1stAd courtWide 3,013 33% +5.5±1.4
1stDeuce courtBody 581 39% +1.9±3.2
1stDeuce courtT 2,753 32% +7.4±1.5
1stDeuce courtWide 2,970 34% +6.3±1.4
2ndAd courtBody 1,204 53% +3.8±2.3
2ndAd courtT 579 50% +0.4±3.3
2ndAd courtWide 1,683 55% +6.8±2.0
2ndDeuce courtBody 1,344 52% +3.4±2.2
2ndDeuce courtT 1,517 55% +5.3±2.1
2ndDeuce courtWide 827 50% +2.0±2.8

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH crosscourt used 2.3% · won 66% · −2.6±3.8 vs own baseline
  2. Wide serve (deuce court) → FH down the line used 2.7% · won 64% · −4.9±3.6 vs own baseline
  3. Wide serve (ad court) → FH crosscourt used 3.3% · won 63% · −5.9±3.3 vs own baseline
  4. Wide serve (ad court) → BH crosscourt used 2.7% · won 58% · −11.0±3.7 vs own baseline
  5. T serve (deuce court) → FH down the line used 2.7% · won 58% · −11.1±3.7 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, deep used 2.2% · won 57% · +13.9±4.1 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, mid used 4.4% · won 53% · +9.4±3.0 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, mid used 2.8% · won 53% · +9.4±3.7 vs own baseline
  4. vs T serve (deuce court) → BH crosscourt, mid used 2.0% · won 54% · +10.4±4.3 vs own baseline
  5. vs T serve (ad court) → FH through the middle, mid used 2.2% · won 52% · +9.0±4.1 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.3% · won 59% · +7.4±4.8 vs own baseline
  2. BH crosscourt → FH crosscourt used 4.3% · won 55% · +3.7±2.7 vs own baseline
  3. BH crosscourt → FH inside-out used 1.4% · won 57% · +5.5±4.7 vs own baseline
  4. BH crosscourt → FH inside-in used 1.1% · won 57% · +6.0±5.2 vs own baseline
  5. FH crosscourt → FH crosscourt used 3.1% · won 55% · +3.5±3.2 vs own baseline

Discovered sequences

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

  1. Wide serve → BH through the middle return, mid → FH crosscourt used 0.4% · won 62% · +9.5±5.4 vs own baseline · +4.8 vs tour on the same sequence · −11.1 v lefties Disrupted by Jesper De Jong (2/6), Daniil Medvedev (10/16)
  2. Wide serve → BH through the middle return, short → FH crosscourt used 0.1% · won 72% · +18.7±8.7 vs own baseline · +15.7 vs tour on the same sequence Disrupted by Jannik Sinner (5/6), Jack Draper (5/6)
  3. Wide serve → BH through the middle return → FH volley crosscourt used 0.1% · won 73% · +20.5±9.2 vs own baseline · +13.6 vs tour on the same sequence
  4. FH crosscourt → FH through the middle → FH crosscourt used 0.4% · won 61% · +8.2±5.4 vs own baseline · +7.4 vs tour on the same sequence Disrupted by Alexander Zverev (10/21), Novak Djokovic (9/16)
  5. FH down the line → BH slice through the middle → FH crosscourt used 0.1% · won 72% · +19.5±9.8 vs own baseline · +24.6 vs tour on the same sequence
  6. FH crosscourt → FH through the middle → BH crosscourt + approach used 0.1% · won 69% · +16.6±9.2 vs own baseline · +9.0 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 drop shot to their forehand · rally+6.3169
FH volley to the middle · rally+5.3157
FH volley to their backhand · serve +1+5.2182
BH volley to their forehand · rally+4.9334
Smash to their forehand · rally+4.1207

Most exposed to

FH slice to their backhand · return +1−1.5128
FH slice to their backhand · return−1.3126
FH to the middle · return−1.12,901
BH slice to their backhand · return +1−0.9423
Smash to their forehand · rally−0.9222

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +0.72, Miomir Kecmanovic +0.63, Casper Ruud +0.38, Jack Draper +0.37, Nishesh Basavareddy +0.35

Favourable matchups

Fabian Marozsan +2.35, Miomir Kecmanovic +2.26, Pedro Martinez +2.18, Roberto Carballes Baena +2.10, Alexander Shevchenko +2.03

Active players who are best at the shot in the top weakness: Rafael Nadal, Novak Djokovic, Hubert Hurkacz

Tactical fingerprint

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

Drop shots / shot3.7%
1st serve in65%
Run-around forehands27%
Point-ending shots26.4%
Wide serves · deuce46%
Forehand share55%
Avg rally length4.0
Deep returns27%
Unforced errors / shot9.8%
Wide serves · ad49%
Serve & volley6%
Points at net11%
Backhand slice18%
FH down the line29%
Chipped returns10%
BH down the line17%
Through the middle22%
T serves · ad34%
T serves · deuce37%

Plays most like

  1. Francisco Cerundolo 2020–2025 plan v
  2. Fabian Marozsan 2021–2026 plan v
  3. Alejandro Tabilo 2021–2026 plan v
  4. Luca Nardi 2022–2025 plan v
  5. Zizou Bergs 2021–2026 plan v
  6. Stefanos Tsitsipas 2016–2026 plan v
  7. Lorenzo Sonego 2019–2025 plan v
  8. Tallon Griekspoor 2018–2026 plan v

Closest from another era

  1. Magnus Norman 2000–2001
  2. Andre Agassi 1988–2006
  3. Carlos Moya 1997–2007

Charted matches