RallyIQ

ATP · Right-handed · 52 charted matches · 2015–2025

Borna Coric

Archetype: Ad-court T server · Two-fisted driver

Against an average opponent

Serve points won 66.3% ±2.5 raw 64.0% · tour 63.4% · 3,801 points
Return points won 36.8% ±2.6 raw 33.7% · tour 36.6% · 3,818 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 +0.17 ±0.06 better than 91% of ATP · raw +0.17
Shot selection −0.12 ±0.13 better than 37% of ATP · raw −0.12
Execution −0.53 ±0.35 better than 43% of ATP · raw −0.56
Tactical adaptability −0.16 first serves toward what's working, set to set · 49 matches
Adaptation speed +0.01 same, every two to three service games · per 100 first serves
Long-rally execution −0.06 ±0.54 shot 9 on v own earlier rally shots · 2,551 shots · better than 66% of ATP
Points left on the table 2.25 per 100 shots vs best direction · lower than 88% 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 18,821 shots.

Shot expected value

The share of points Borna Coric 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 · 1,120 shots

OptionUsedWin %Tour
BH crosscourt 51% 46.3%±3.4 47.6%
BH through the middle 21% 46.6%±5.1 43.7%
BH down the line 9% 48.6%±7.4 46.4%
BH slice crosscourt 8% 36.7%±7.5 42.5%
FH inside-out 3% 51.5%±10.7 51.8%
BH slice through the middle 2% 32.0%±11.2 35.1%
FH inside-in 1% 54.3%±14.3 54.7%
BH slice down the line 1% 34.7%±14.3 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 995 shots

OptionUsedWin %Tour
FH crosscourt 25% 51.1%±5.0 52.7%
FH down the line 21% 47.7%±5.5 51.5%
BH crosscourt 16% 46.1%±6.1 49.1%
FH through the middle 15% 43.0%±6.2 47.0%
BH through the middle 12% 42.1%±6.8 46.8%
BH down the line 4% 46.1%±10.6 48.3%
FH down the line + approach 2% 68.5%±11.9 70.5%
BH crosscourt + approach 1% 63.0%±14.3 67.7%

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

position worth 44% to the average player · 806 shots

OptionUsedWin %Tour
FH crosscourt 47% 48.7%±4.1 46.6%
FH down the line 23% 46.3%±5.8 44.7%
FH through the middle 22% 42.1%±5.8 41.5%
FH slice through the middle 4% 19.1%±9.0 24.5%
FH slice crosscourt 2% 28.3%±12.3 30.9%
FH down the line + approach 2% 73.1%±12.5 69.3%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 719 shots

OptionUsedWin %Tour
BH crosscourt 46% 41.7%±4.3 48.0%
BH through the middle 20% 46.8%±6.4 43.8%
BH down the line 12% 46.6%±7.9 46.5%
BH slice crosscourt 8% 35.1%±8.7 42.1%
BH slice through the middle 5% 37.5%±10.6 35.1%
FH inside-out 4% 52.2%±12.0 52.6%
BH slice down the line 2% 31.7%±13.5 35.8%

Serve under pressure

Pressure predictability index −1 How much less varied Borna Coric's first-serve direction gets on break points. Positive means easier to read. Based on 325 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 42% 43% 71% / 73%
Body 6% 2% 58% / 63%
T 52% 55% 73% / 75%

1,898 normal · 88 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 50% 47% 73% / 73%
Body 6% 8% 59% / 63%
T 44% 45% 72% / 72%

1,569 normal · 237 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
Wide42% 64.0%±2.7 n=835 34% ▼
Body5% 53.7%±7.0 n=109 0% ▼
T52% 65.0%±2.4 n=1,042 66% ▲

Off equilibrium (p = 0.010): serve T more. Gap 1.0 points per 100 first serves.
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide49% 63.3%±2.6 n=891 42% ▼
Body6% 60.1%±6.8 n=110 0% ▼
T45% 66.0%±2.7 n=805 58% ▲

Consistent with an optimal mix (p = 0.22).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.49 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±2.5 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. (1,691 repeats, 1,999 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 85 41% +4.0±7.5
1stAd courtT 438 26% −1.9±3.3
1stAd courtWide 535 24% −3.1±3.0
1stDeuce courtBody 73 44% +7.0±8.0
1stDeuce courtT 498 24% −1.5±3.0
1stDeuce courtWide 650 22% −5.2±2.6
2ndAd courtBody 254 49% −0.5±4.9
2ndAd courtT 134 44% −5.5±6.4
2ndAd courtWide 382 46% −2.1±4.0
2ndDeuce courtBody 271 50% +1.4±4.7
2ndDeuce courtT 271 46% −3.2±4.7
2ndDeuce courtWide 223 44% −3.6±5.1

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.3% · won 65% · −1.6±7.4 vs own baseline
  2. T serve (deuce court) → FH down the line used 3.9% · won 59% · −7.4±6.2 vs own baseline
  3. Wide serve (deuce court) → FH down the line used 2.9% · won 57% · −9.2±7.1 vs own baseline
  4. T serve (ad court) → FH crosscourt used 2.5% · won 57% · −10.1±7.6 vs own baseline
  5. Wide serve (deuce court) → FH crosscourt used 2.4% · won 55% · −11.2±7.7 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, deep used 3.2% · won 61% · +24.2±7.4 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, deep used 2.6% · won 51% · +13.5±8.2 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 2.9% · won 48% · +11.1±7.9 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 4.6% · won 46% · +8.7±6.5 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, short used 4.0% · won 45% · +8.2±6.9 vs own baseline

Rally, consecutive own shots

  1. BH down the line → FH crosscourt used 1.1% · won 54% · +7.6±9.5 vs own baseline
  2. FH crosscourt → BH crosscourt used 4.2% · won 50% · +3.4±5.7 vs own baseline
  3. FH through the middle → FH crosscourt used 2.2% · won 51% · +4.4±7.5 vs own baseline
  4. FH crosscourt → FH through the middle used 2.4% · won 50% · +3.6±7.3 vs own baseline
  5. FH down the line → BH down the line used 1.3% · won 51% · +4.8±9.1 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Borna Coric 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 0.2% · won 62% · +14.5±11.5 vs own baseline · +19.5 vs tour on the same sequence
  2. Wide serve → BH crosscourt return, mid → FH inside-out used 0.2% · won 61% · +13.0±12.5 vs own baseline · +26.4 vs tour on the same sequence
  3. T serve → FH down the line return, mid → BH crosscourt used 0.2% · won 61% · +13.0±12.5 vs own baseline · +30.3 vs tour on the same sequence
  4. T serve → FH through the middle return, mid → FH down the line used 0.4% · won 56% · +8.3±10.2 vs own baseline · +9.6 vs tour on the same sequence Disrupted by Roger Federer (2/8)
  5. FH down the line → BH slice crosscourt → BH crosscourt used 0.5% · won 55% · +6.8±9.6 vs own baseline · +6.2 vs tour on the same sequence Disrupted by Dominic Thiem (3/6), Stan Wawrinka (4/6)
  6. BH crosscourt → BH slice crosscourt → FH inside-in used 0.4% · won 55% · +7.3±10.0 vs own baseline · +4.1 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

Wide 2nd serve · ad court+2.1395
T 2nd serve · deuce court+1.5355
BH to the middle · serve +1+1.3196
Body 2nd serve · ad court+1.3155
Body 2nd serve · deuce court+0.7188

Most exposed to

FH to the middle · return +1−1.9193
BH to their backhand · serve +1−1.9326
Wide 1st serve · deuce court−1.8963
Wide 2nd serve · ad court−1.7371
BH slice to their backhand · return−1.6166

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Miomir Kecmanovic +1.34, Rafael Nadal +1.17, Nishesh Basavareddy +1.10, Casper Ruud +1.09, Roberto Bautista Agut +1.09

Favourable matchups

Miomir Kecmanovic +0.29, Fabian Marozsan +0.22, Roberto Carballes Baena +0.16, Pedro Martinez +0.13, Roberto Bautista Agut −0.01

Active players who are best at the shot in the top weakness: Brandon Nakashima, Diego Schwartzman, Alejandro Davidovich Fokina, Daniil Medvedev, Sebastian Baez

Tactical fingerprint

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

T serves · deuce52%
T serves · ad45%
Deep returns30%
FH down the line32%
1st serve in63%
Avg rally length4.1
Unforced errors / shot10.5%
Forehand share54%
Run-around forehands18%
Drop shots / shot1.4%
Wide serves · ad49%
Wide serves · deuce42%
Serve & volley4%
Point-ending shots22.0%
Points at net9%
Backhand slice14%
Chipped returns9%
Through the middle22%
BH down the line15%

Plays most like

  1. Sebastian Korda 2021–2026 plan v
  2. David Goffin 2013–2025 plan v
  3. Nicolas Almagro 2006–2019 plan v
  4. Jack Draper 2022–2026 plan v
  5. Taylor Fritz 2016–2026 plan v
  6. Juan Martin Del Potro 2007–2022 plan v
  7. Andrey Rublev 2015–2026 plan v
  8. Laslo Djere 2018–2026 plan v

Closest from another era

  1. Marat Safin 1998–2009
  2. Juan Carlos Ferrero 2000–2009
  3. Magnus Norman 2000–2001

Charted matches