RallyIQ

ATP · Left-handed · 48 charted matches · 2015–2026

Cameron Norrie

Archetype: Avoids the wide serve · Ad-court slider

Against an average opponent

Serve points won 64.8% ±2.4 raw 62.7% · tour 63.4% · 3,755 points
Return points won 36.1% ±2.5 raw 33.9% · tour 36.6% · 3,619 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 −0.04 ±0.08 better than 46% of ATP · raw −0.04
Shot selection +0.49 ±0.17 better than 92% of ATP · raw +0.49
Execution +0.02 ±0.39 better than 69% of ATP · raw +0.03
Tactical adaptability +0.01 first serves toward what's working, set to set · 47 matches
Adaptation speed +0.03 same, every two to three service games · per 100 first serves
Long-rally execution +0.43 ±0.51 shot 9 on v own earlier rally shots · 2,689 shots · better than 97% of ATP
Points left on the table 2.83 per 100 shots vs best direction · lower than 28% 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 19,600 shots.

Shot expected value

The share of points Cameron Norrie 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 middle

position worth 51% to the average player · 1,125 shots

OptionUsedWin %Tour
FH crosscourt 32% 55.5%±4.2 52.7%
FH through the middle 18% 53.9%±5.6 47.0%
FH down the line 14% 57.4%±6.2 51.5%
BH through the middle 12% 49.0%±6.5 46.8%
BH crosscourt 11% 49.5%±7.0 49.1%
BH down the line 8% 48.7%±8.0 48.3%
FH crosscourt + approach 3% 79.5%±9.5 69.9%
BH down the line + approach 1% 69.3%±12.8 66.2%

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

position worth 46% to the average player · 1,115 shots

OptionUsedWin %Tour
BH crosscourt 45% 45.0%±3.6 47.6%
BH through the middle 23% 45.3%±5.0 43.7%
BH down the line 10% 50.2%±7.1 46.4%
FH through the middle 5% 52.2%±9.8 45.2%
FH inside-in 4% 53.6%±10.0 54.7%
FH inside-out 4% 43.6%±10.1 51.8%
BH down the line + approach 3% 67.1%±10.8 66.2%
BH slice through the middle 3% 39.6%±11.6 35.1%

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

position worth 44% to the average player · 1,101 shots

OptionUsedWin %Tour
FH crosscourt 46% 47.5%±3.6 46.6%
FH down the line 19% 42.9%±5.4 44.7%
FH through the middle 19% 47.0%±5.5 41.5%
FH slice through the middle 4% 26.5%±9.4 24.5%
BH inside-in 3% 43.0%±11.3 46.7%
BH inside-out 2% 40.6%±11.8 45.4%
FH slice crosscourt 2% 33.7%±11.6 30.9%
BH through the middle 2% 51.4%±12.4 43.1%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 698 shots

OptionUsedWin %Tour
BH crosscourt 47% 46.4%±4.4 48.0%
BH through the middle 19% 42.2%±6.6 43.8%
BH down the line 11% 42.0%±8.3 46.5%
FH inside-in 5% 51.6%±11.4 54.3%
FH through the middle 4% 37.7%±11.2 46.1%
BH slice through the middle 4% 28.3%±10.9 35.1%
FH inside-out 3% 58.0%±12.2 52.6%
BH slice down the line 3% 38.5%±12.3 35.8%

Serve under pressure

Pressure predictability index +11 How much less varied Cameron Norrie's first-serve direction gets on break points. Positive means easier to read. Based on 337 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 37% 45% 70% / 73%
Body 9% 6% 63% / 63%
T 53% 49% 67% / 75%

1,885 normal · 80 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 62% 61% 71% / 73%
Body 9% 2% 64% / 63%
T 29% 36% 79% / 72%

1,531 normal · 257 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
Wide37% 60.8%±2.9 n=736 51% ▲
Body9% 57.5%±5.6 n=182 0% ▼
T53% 60.1%±2.5 n=1,047 49% ▼

Consistent with an optimal mix (p = 0.63).
Optimal mix: +0.2 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide62% 64.0%±2.3 n=1,110 57% ▼
Body8% 60.9%±6.1 n=144 0% ▼
T30% 69.7%±3.2 n=534 43% ▲

Off equilibrium (p = 0.018): serve T more. Gap 4.2 points per 100 first serves.
Optimal mix: +0.9 per 100 first serves.

Exploitability 0.54 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: ±0.0±3.0 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. (1,495 repeats, 2,162 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 91 37% +0.3±7.2
1stAd courtT 458 31% +3.4±3.5
1stAd courtWide 515 21% −5.9±2.9
1stDeuce courtBody 129 38% +1.0±6.3
1stDeuce courtT 524 21% −3.7±2.9
1stDeuce courtWide 606 25% −1.7±2.8
2ndAd courtBody 187 48% −1.1±5.6
2ndAd courtT 258 50% +0.6±4.8
2ndAd courtWide 207 46% −2.6±5.3
2ndDeuce courtBody 221 48% −0.5±5.2
2ndDeuce courtT 121 51% +1.2±6.7
2ndDeuce courtWide 296 48% −0.1±4.6

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → BH crosscourt used 3.2% · won 63% · −2.7±6.7 vs own baseline
  2. T serve (deuce court) → FH down the line used 3.3% · won 59% · −7.0±6.8 vs own baseline
  3. Wide serve (deuce court) → FH crosscourt used 2.1% · won 55% · −10.6±8.1 vs own baseline
  4. Body serve (deuce court) → FH crosscourt used 2.6% · won 56% · −9.6±7.5 vs own baseline
  5. T serve (deuce court) → BH crosscourt used 2.1% · won 54% · −12.0±8.1 vs own baseline

Return

  1. vs T serve (ad court) → BH through the middle, deep used 3.0% · won 53% · +14.7±7.8 vs own baseline
  2. vs wide serve (deuce court) → BH crosscourt, deep used 2.3% · won 47% · +9.1±8.6 vs own baseline
  3. vs T serve (ad court) → BH through the middle, mid used 3.7% · won 44% · +5.7±7.1 vs own baseline
  4. vs wide serve (deuce court) → BH crosscourt, mid used 5.6% · won 43% · +4.6±6.0 vs own baseline
  5. vs wide serve (deuce court) → BH crosscourt, short used 3.1% · won 43% · +4.7±7.6 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH crosscourt used 8.0% · won 52% · +3.7±4.3 vs own baseline
  2. FH crosscourt → FH through the middle used 4.1% · won 53% · +4.2±5.8 vs own baseline
  3. FH through the middle → FH through the middle used 2.3% · won 54% · +5.5±7.4 vs own baseline
  4. BH down the line → FH crosscourt used 2.2% · won 54% · +5.2±7.6 vs own baseline
  5. FH crosscourt → FH down the line used 5.6% · won 52% · +3.1±5.1 vs own baseline

Discovered sequences

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

  1. FH crosscourt → BH through the middle → FH crosscourt used 1.7% · won 62% · +11.2±5.9 vs own baseline · +10.6 vs tour on the same sequence Disrupted by Francisco Cerundolo (1/6), Gael Monfils (4/14)
  2. T serve → BH through the middle return, mid → FH crosscourt used 0.7% · won 60% · +9.6±8.4 vs own baseline · +9.1 vs tour on the same sequence Disrupted by Egor Gerasimov (4/7), Daniil Medvedev (5/8)
  3. FH through the middle → BH through the middle → FH down the line used 0.3% · won 61% · +10.3±10.6 vs own baseline · +18.6 vs tour on the same sequence Disrupted by Albert Ramos (5/7)
  4. FH crosscourt → BH slice through the middle → FH crosscourt used 0.2% · won 62% · +11.2±11.5 vs own baseline · +16.2 vs tour on the same sequence
  5. BH through the middle → FH through the middle → FH through the middle used 0.3% · won 60% · +9.6±10.8 vs own baseline · +20.7 vs tour on the same sequence Disrupted by Peter Gojowczyk (3/6), Benoit Paire (5/6)
  6. FH crosscourt → BH through the middle → FH through the middle used 0.9% · won 56% · +5.8±7.9 vs own baseline · +11.0 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

BH to the middle · return+2.9671
BH to their backhand · return +1+2.3151
FH to their backhand · return +1+1.6388
BH to their forehand · rally+1.61,134
BH to the middle · rally+1.4711

Most exposed to

FH to their forehand · serve +1−3.9616
BH to the middle · return−3.3983
BH to their forehand · return−2.7448
BH slice to the middle · return−2.5197
BH to their forehand · serve +1−2.4201

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +2.94, Jack Draper +2.50, Miomir Kecmanovic +2.33, Roberto Bautista Agut +2.10, Pedro Martinez +2.08

Favourable matchups

Pedro Martinez +2.01, Alexander Shevchenko +1.97, Miomir Kecmanovic +1.90, Fabian Marozsan +1.88, Adrian Mannarino +1.80

Active players who are best at the shot in the top weakness: Luciano Darderi, Brandon Nakashima, Milos Raonic, Francisco Cerundolo, Rinky Hijikata

Tactical fingerprint

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

Wide serves · ad62%
T serves · deuce53%
Forehand share59%
1st serve in64%
Avg rally length4.3
Through the middle26%
Deep returns28%
Drop shots / shot1.6%
Points at net10%
Run-around forehands16%
BH down the line19%
Unforced errors / shot9.1%
Serve & volley1%
Point-ending shots21.0%
Chipped returns9%
Backhand slice9%
Wide serves · deuce37%
T serves · ad30%
FH down the line24%

Plays most like

  1. Cristian Garin 2018–2025 plan v
  2. Albert Ramos 2014–2025 plan v
  3. Federico Delbonis 2013–2023 plan v
  4. Pablo Cuevas 2015–2021 plan v
  5. Daniel Elahi Galan 2020–2025 plan v
  6. Jannik Sinner 2013–2026 plan v
  7. Gael Monfils 2005–2026 plan v
  8. Thiago Monteiro 2019–2026 plan v

Closest from another era

  1. Gaston Gaudio 2002–2005
  2. Juan Carlos Ferrero 2000–2009
  3. Nicolas Massu 2000–2009

Charted matches