RallyIQ

ATP · Right-handed · 84 charted matches · 2009–2026

Marin Cilic

Archetype: High-risk · Runs around the backhand

Against an average opponent

Serve points won 66.8% ±2.3 raw 63.5% · tour 63.4% · 7,500 points
Return points won 37.4% ±2.4 raw 34.3% · tour 36.6% · 7,399 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 +0.14 ±0.05 better than 87% of ATP · raw +0.13
Shot selection +0.28 ±0.08 better than 78% of ATP · raw +0.28
Execution −1.01 ±0.32 better than 25% of ATP · raw −1.13
Tactical adaptability +0.18 first serves toward what's working, set to set · 83 matches
Adaptation speed +0.06 same, every two to three service games · per 100 first serves
Long-rally execution −0.14 ±0.51 shot 9 on v own earlier rally shots · 3,503 shots · better than 58% of ATP
Points left on the table 2.18 per 100 shots vs best direction · lower than 93% 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 35,879 shots.

Shot expected value

The share of points Marin Cilic 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 · 1,974 shots

OptionUsedWin %Tour
BH crosscourt 47% 42.3%±2.6 47.6%
BH through the middle 21% 40.0%±3.8 43.7%
BH down the line 8% 44.4%±6.1 46.4%
BH slice crosscourt 7% 41.8%±6.6 42.5%
FH inside-out 6% 55.5%±6.8 51.8%
BH slice through the middle 4% 32.3%±7.9 35.1%
FH inside-in 3% 60.2%±9.1 54.7%
BH slice down the line 1% 37.0%±11.6 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 1,744 shots

OptionUsedWin %Tour
FH down the line 27% 52.4%±3.7 51.5%
FH crosscourt 25% 48.9%±3.9 52.7%
FH through the middle 14% 40.9%±4.9 47.0%
BH through the middle 11% 38.7%±5.5 46.8%
BH crosscourt 11% 48.7%±5.7 49.1%
BH down the line 4% 47.8%±8.9 48.3%
BH slice through the middle 2% 36.1%±10.4 44.8%
FH down the line + approach 2% 66.2%±11.0 70.5%

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

position worth 44% to the average player · 1,402 shots

OptionUsedWin %Tour
FH crosscourt 44% 41.4%±3.2 46.6%
FH down the line 26% 45.3%±4.2 44.7%
FH through the middle 21% 41.1%±4.6 41.5%
FH slice through the middle 4% 18.2%±7.0 24.5%
FH down the line + approach 2% 71.8%±11.3 69.3%
FH slice down the line 1% 17.0%±10.3 25.6%
FH slice crosscourt 1% 20.5%±11.2 30.9%

Return +1: drive to your backhand side

position worth 44% to the average player · 1,147 shots

OptionUsedWin %Tour
BH crosscourt 43% 43.1%±3.6 46.9%
BH through the middle 23% 41.0%±4.8 43.0%
BH down the line 9% 46.3%±7.3 44.2%
BH slice crosscourt 9% 46.0%±7.5 40.9%
BH slice through the middle 8% 25.9%±6.9 32.6%
FH inside-out 4% 56.3%±10.4 51.7%
FH inside-in 2% 51.7%±12.7 53.6%
BH slice down the line 1% 30.2%±13.4 33.3%

Serve under pressure

Pressure predictability index ±0 How much less varied Marin Cilic's first-serve direction gets on break points. Positive means easier to read. Based on 659 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 50% 54% 73% / 73%
Body 4% 3% 58% / 63%
T 46% 43% 80% / 75%

3,751 normal · 149 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 53% 52% 76% / 73%
Body 7% 8% 63% / 63%
T 40% 40% 76% / 72%

3,055 normal · 510 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
Wide50% 63.2%±1.8 n=1,960 41% ▼
Body4% 58.3%±5.8 n=165 0% ▼
T46% 64.6%±1.9 n=1,775 59% ▲

Consistent with an optimal mix (p = 0.61).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide53% 63.7%±1.8 n=1,887 66% ▲
Body7% 61.3%±4.7 n=263 0% ▼
T40% 63.5%±2.1 n=1,415 34% ▼

Consistent with an optimal mix (p = 0.69).
Optimal mix: +0.3 per 100 first serves.

Exploitability 0.32 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±2.2 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. (3,394 repeats, 3,903 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 245 41% +3.8±4.9
1stAd courtT 911 29% +0.7±2.4
1stAd courtWide 1,080 24% −3.2±2.1
1stDeuce courtBody 283 33% −4.1±4.4
1stDeuce courtT 1,057 26% +0.9±2.2
1stDeuce courtWide 1,203 26% −0.9±2.1
2ndAd courtBody 454 49% −0.7±3.7
2ndAd courtT 264 51% +1.3±4.8
2ndAd courtWide 583 48% −0.8±3.3
2ndDeuce courtBody 522 44% −4.9±3.5
2ndDeuce courtT 450 48% −1.4±3.8
2ndDeuce courtWide 322 46% −2.5±4.4

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 3.2% · won 63% · −3.7±5.0 vs own baseline
  2. T serve (ad court) → FH crosscourt used 2.1% · won 61% · −6.2±6.1 vs own baseline
  3. T serve (deuce court) → FH crosscourt used 3.1% · won 58% · −9.4±5.2 vs own baseline
  4. Body serve (deuce court) → FH down the line used 2.1% · won 49% · −17.6±6.2 vs own baseline
  5. T serve (deuce court) → FH down the line used 3.8% · won 54% · −13.3±4.8 vs own baseline

Return

  1. vs wide serve (deuce court) → FH through the middle, deep used 2.3% · won 52% · +14.6±6.3 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, mid used 3.5% · won 49% · +11.6±5.3 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, short used 2.3% · won 50% · +13.4±6.3 vs own baseline
  4. vs wide serve (deuce court) → FH crosscourt, mid used 2.2% · won 50% · +13.4±6.4 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, mid used 4.6% · won 46% · +8.9±4.6 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 4.3% · won 52% · +6.6±4.5 vs own baseline
  2. FH down the line → FH inside-out used 1.8% · won 55% · +9.8±6.6 vs own baseline
  3. FH down the line → FH crosscourt used 2.2% · won 51% · +6.1±6.1 vs own baseline
  4. FH down the line → FH down the line used 1.8% · won 50% · +4.8±6.6 vs own baseline
  5. FH through the middle → FH down the line used 1.4% · won 50% · +4.8±7.2 vs own baseline

Discovered sequences

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

  1. FH down the line → BH slice crosscourt → FH inside-out used 0.6% · won 57% · +10.2±7.0 vs own baseline · +4.4 vs tour on the same sequence Disrupted by Bernard Tomic (3/6), Grigor Dimitrov (5/9)
  2. FH inside-out → BH slice through the middle → FH crosscourt used 0.1% · won 67% · +20.7±11.3 vs own baseline · +29.5 vs tour on the same sequence
  3. Body serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 60% · +13.7±9.3 vs own baseline · +11.3 vs tour on the same sequence Disrupted by Novak Djokovic (8/10)
  4. Wide serve → BH through the middle return, mid → FH crosscourt used 0.4% · won 58% · +11.4±8.6 vs own baseline · +3.7 vs tour on the same sequence Disrupted by Novak Djokovic (7/8)
  5. Wide serve → BH crosscourt return, mid → FH inside-in used 0.2% · won 61% · +14.4±10.4 vs own baseline · +11.1 vs tour on the same sequence
  6. FH crosscourt → FH slice through the middle → FH down the line used 0.2% · won 62% · +15.2±10.7 vs own baseline · +11.6 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 their forehand · serve +1+1.0283
T 2nd serve · deuce court+0.9770
BH to their forehand · return+0.8326
T 1st serve · deuce court+0.71,775
FH to their forehand · serve +1+0.51,141

Most exposed to

FH to their forehand · return +1−1.7478
FH to their forehand · serve +1−1.5791
Wide 1st serve · deuce court−1.21,775
BH to their forehand · return +1−1.2271
BH to the middle · return +1−1.2457

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +1.88, Miomir Kecmanovic +1.63, Nishesh Basavareddy +1.46, Pedro Martinez +1.43, Casper Ruud +1.40

Favourable matchups

Fabian Marozsan −0.12, Miomir Kecmanovic −0.16, Roberto Carballes Baena −0.27, Pedro Martinez −0.28, Alexander Shevchenko −0.40

Active players who are best at the shot in the top weakness: Sebastian Baez, Jaume Munar, Miomir Kecmanovic, Jan Lennard Struff, Tomas Martin Etcheverry

Tactical fingerprint

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

Unforced errors / shot12.6%
Wide serves · deuce50%
Forehand share57%
Run-around forehands26%
Point-ending shots27.8%
FH down the line34%
Wide serves · ad53%
Deep returns29%
T serves · ad40%
T serves · deuce46%
Serve & volley2%
Backhand slice16%
Avg rally length3.7
Drop shots / shot1.0%
Points at net8%
Through the middle22%
BH down the line16%
Chipped returns7%
1st serve in57%

Plays most like

  1. Kyle Edmund 2016–2023 plan v
  2. Sebastian Ofner 2022–2025 plan v
  3. Lloyd Harris 2019–2024 plan v
  4. Roman Safiullin 2017–2025 plan v
  5. Arthur Fils 2023–2026 plan v
  6. Aleksandar Vukic 2019–2025 plan v
  7. Sam Querrey 2010–2022 plan v
  8. Thanasi Kokkinakis 2013–2024 plan v

Closest from another era

  1. Magnus Norman 2000–2001
  2. Sebastien Grosjean 1999–2005
  3. Yevgeny Kafelnikov 1994–2002

Charted matches