RallyIQ

ATP · Right-handed · 48 charted matches · 2019–2026

Miomir Kecmanovic

Archetype: Grinder · Ad-court T server

Against an average opponent

Serve points won 63.6% ±2.5 raw 62.7% · tour 63.4% · 3,978 points
Return points won 38.0% ±2.6 raw 35.1% · tour 36.6% · 3,919 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 −0.06 ±0.09 better than 43% of ATP · raw −0.05
Shot selection −0.28 ±0.10 better than 25% of ATP · raw −0.27
Execution +1.00 ±0.38 better than 95% of ATP · raw +1.10
Tactical adaptability +0.29 first serves toward what's working, set to set · 45 matches
Adaptation speed +0.13 same, every two to three service games · per 100 first serves
Long-rally execution −0.06 ±0.51 shot 9 on v own earlier rally shots · 3,154 shots · better than 67% of ATP
Points left on the table 2.31 per 100 shots vs best direction · lower than 84% 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 21,395 shots.

Shot expected value

The share of points Miomir Kecmanovic 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 · 1,387 shots

OptionUsedWin %Tour
BH crosscourt 43% 47.0%±3.3 47.6%
BH through the middle 23% 46.6%±4.4 43.7%
BH down the line 10% 54.7%±6.6 46.4%
BH slice crosscourt 9% 37.2%±6.7 42.5%
BH slice through the middle 5% 35.6%±8.3 35.1%
FH inside-out 4% 55.9%±9.5 51.8%
FH inside-in 4% 55.0%±9.9 54.7%
BH slice down the line 1% 31.7%±12.8 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 1,311 shots

OptionUsedWin %Tour
FH crosscourt 28% 56.2%±4.1 52.7%
FH through the middle 20% 50.5%±5.0 47.0%
BH through the middle 15% 51.6%±5.6 46.8%
BH crosscourt 14% 51.9%±5.8 49.1%
FH down the line 14% 54.1%±5.8 51.5%
BH down the line 4% 48.3%±9.3 48.3%
FH down the line + approach 1% 73.3%±12.0 70.5%
BH slice through the middle 1% 46.9%±14.1 44.8%

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

position worth 44% to the average player · 981 shots

OptionUsedWin %Tour
FH crosscourt 37% 48.4%±4.2 46.6%
FH through the middle 28% 43.3%±4.8 41.5%
FH down the line 22% 44.0%±5.3 44.7%
FH slice through the middle 6% 25.5%±7.9 24.5%
FH slice crosscourt 3% 24.4%±10.0 30.9%
FH down the line + approach 2% 75.3%±11.7 69.3%
FH slice down the line 2% 25.4%±11.9 25.6%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 895 shots

OptionUsedWin %Tour
BH crosscourt 45% 46.4%±4.0 48.0%
BH through the middle 22% 42.7%±5.5 43.8%
BH down the line 14% 56.1%±6.8 46.5%
BH slice crosscourt 7% 31.5%±8.3 42.1%
BH slice through the middle 5% 36.1%±10.1 35.1%
FH inside-in 2% 55.7%±12.8 54.3%
FH inside-out 2% 44.9%±13.1 52.6%
BH slice down the line 2% 43.3%±13.8 35.8%

Serve under pressure

Pressure predictability index −4 How much less varied Miomir Kecmanovic's first-serve direction gets on break points. Positive means easier to read. Based on 346 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 41% 42% 68% / 73%
Body 15% 21% 61% / 63%
T 43% 37% 73% / 75%

2,000 normal · 81 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 45% 44% 71% / 73%
Body 13% 18% 65% / 63%
T 42% 38% 68% / 72%

1,626 normal · 265 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
Wide41% 62.4%±2.7 n=863 42%
Body16% 59.2%±4.3 n=323 2% ▼
T43% 65.1%±2.6 n=895 56% ▲

Consistent with an optimal mix (p = 0.09).
Optimal mix: +0.9 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide45% 63.8%±2.7 n=847 58% ▲
Body14% 59.1%±4.7 n=261 1% ▼
T41% 61.7%±2.8 n=783 41%

Consistent with an optimal mix (p = 0.27).
Optimal mix: +0.7 per 100 first serves.

Exploitability 0.82 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: −0.3±3.3 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. (1,377 repeats, 2,501 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 127 42% +5.1±6.5
1stAd courtT 477 27% −1.1±3.2
1stAd courtWide 554 27% −0.7±3.0
1stDeuce courtBody 146 42% +5.3±6.1
1stDeuce courtT 519 20% −4.9±2.8
1stDeuce courtWide 687 24% −2.9±2.6
2ndAd courtBody 260 52% +2.6±4.8
2ndAd courtT 111 48% −1.2±6.9
2ndAd courtWide 330 53% +4.6±4.3
2ndDeuce courtBody 278 47% −1.7±4.7
2ndDeuce courtT 301 51% +1.3±4.5
2ndDeuce courtWide 127 49% +1.2±6.6

Signature patterns

Recurring sequences that win more than Miomir Kecmanovic'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 67% · +1.7±6.3 vs own baseline
  2. Wide serve (deuce court) → FH crosscourt used 2.2% · won 62% · −2.8±7.5 vs own baseline
  3. T serve (ad court) → FH down the line used 2.1% · won 61% · −4.0±7.8 vs own baseline
  4. T serve (deuce court) → FH through the middle used 2.2% · won 59% · −6.3±7.7 vs own baseline
  5. Wide serve (deuce court) → FH down the line used 2.4% · won 59% · −6.5±7.4 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 4.3% · won 46% · +6.4±6.6 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, deep used 2.8% · won 47% · +7.6±7.8 vs own baseline
  3. vs wide serve (deuce court) → FH crosscourt, mid used 2.1% · won 46% · +6.9±8.7 vs own baseline
  4. vs wide serve (deuce court) → FH through the middle, deep used 3.0% · won 45% · +5.1±7.6 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, short used 3.4% · won 42% · +2.5±7.1 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.5% · won 59% · +9.8±7.8 vs own baseline
  2. BH through the middle → FH crosscourt used 3.4% · won 55% · +6.0±5.7 vs own baseline
  3. FH crosscourt → FH crosscourt used 4.0% · won 54% · +4.2±5.3 vs own baseline
  4. BH down the line → FH crosscourt used 1.9% · won 55% · +5.2±7.2 vs own baseline
  5. BH crosscourt → FH crosscourt used 3.9% · won 53% · +3.6±5.4 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Miomir Kecmanovic 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 58% · +7.9±6.8 vs own baseline · +6.4 vs tour on the same sequence Disrupted by Tomas Martin Etcheverry (3/8), Alex De Minaur (4/9)
  2. FH crosscourt → FH crosscourt → FH down the line + approach used 0.2% · won 69% · +18.7±11.7 vs own baseline · +23.7 vs tour on the same sequence
  3. BH crosscourt → BH slice through the middle → FH crosscourt used 0.2% · won 65% · +15.1±11.1 vs own baseline · +23.0 vs tour on the same sequence Disrupted by Lorenzo Musetti (4/6)
  4. FH down the line → BH through the middle → FH crosscourt used 0.4% · won 60% · +10.2±9.4 vs own baseline · +10.7 vs tour on the same sequence
  5. FH down the line → BH slice through the middle → FH crosscourt used 0.2% · won 62% · +12.6±11.0 vs own baseline · +11.1 vs tour on the same sequence
  6. FH down the line → BH crosscourt → BH down the line used 0.2% · won 62% · +12.6±11.0 vs own baseline · +25.6 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

FH to their backhand · return+4.5196
BH to their forehand · return +1+3.5137
BH to their forehand · return+3.3139
BH to their forehand · rally+3.2558
FH to their forehand · return +1+3.2255

Most exposed to

FH to their forehand · rally−4.11,487
FH to their forehand · return−4.0306
FH to their backhand · serve +1−3.7675
FH to their forehand · serve +1−3.3481
FH to their backhand · return−3.0311

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +3.10, Nishesh Basavareddy +2.65, Jack Draper +2.63, Roberto Bautista Agut +2.60, Casper Ruud +2.55

Favourable matchups

Fabian Marozsan +2.68, Pedro Martinez +2.62, Roberto Carballes Baena +2.59, Alexander Shevchenko +2.53, Roberto Bautista Agut +2.52

Active players who are best at the shot in the top weakness: Roberto Carballes Baena, Roberto Bautista Agut, Pedro Martinez, Camilo Ugo Carabelli, Holger Rune

Tactical fingerprint

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

Deep returns35%
Avg rally length4.5
Through the middle28%
T serves · ad41%
1st serve in62%
Forehand share54%
Run-around forehands19%
Drop shots / shot1.4%
Wide serves · deuce41%
T serves · deuce43%
Chipped returns12%
Backhand slice16%
Serve & volley0%
BH down the line17%
Points at net7%
Wide serves · ad45%
FH down the line27%
Point-ending shots19.0%
Unforced errors / shot7.3%

Plays most like

  1. Ilya Ivashka 2018–2023 plan v
  2. Gael Monfils 2005–2026 plan v
  3. Taylor Fritz 2016–2026 plan v
  4. Emil Ruusuvuori 2021–2024 plan v
  5. Novak Djokovic 2005–2026 plan v
  6. Marcos Giron 2018–2026 plan v
  7. Botic Van De Zandschulp 2019–2026 plan v
  8. Nuno Borges 2021–2026 plan v

Closest from another era

  1. Guillermo Canas 2001–2007
  2. Magnus Norman 2000–2001
  3. Andy Roddick 2001–2012

Charted matches