RallyIQ

WTA · Left-handed · 14 charted matches · 2007–2018

Kate Makarova

Archetype: Forehand line-changer · Backhand line-changer

Against an average opponent

Serve points won 57.0% ±3.1 raw 54.7% · tour 56.3% · 1,067 points
Return points won 43.9% ±3.2 raw 39.6% · tour 43.7% · 930 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 ±0.08 better than 43% of WTA · raw −0.07
Shot selection −0.02 ±0.17 better than 44% of WTA · raw −0.03
Execution −0.16 ±0.83 better than 54% of WTA · raw −0.21
Tactical adaptability −0.02 first serves toward what's working, set to set · 14 matches
Adaptation speed +0.18 same, every two to three service games · per 100 first serves
Points left on the table 2.73 per 100 shots vs best direction · lower than 29% of WTA

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 5,037 shots.

Shot expected value

The share of points Kate Makarova 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 forehand side

position worth 43% to the average player · 317 shots

OptionUsedWin %Tour
FH crosscourt 37% 36.0%±6.7 46.7%
FH down the line 30% 55.6%±7.6 44.9%
FH through the middle 21% 48.0%±8.9 41.3%
FH slice through the middle 7% 25.2%±10.9 29.2%
FH slice crosscourt 5% 28.9%±12.4 31.9%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 291 shots

OptionUsedWin %Tour
BH crosscourt 23% 52.5%±8.9 50.9%
FH down the line 21% 47.5%±9.1 52.2%
FH crosscourt 20% 47.5%±9.4 52.7%
BH through the middle 16% 44.3%±10.1 46.2%
FH through the middle 11% 42.6%±11.3 45.8%
BH down the line 10% 38.8%±11.5 50.0%

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

position worth 45% to the average player · 289 shots

OptionUsedWin %Tour
BH crosscourt 40% 46.0%±7.0 47.6%
BH down the line 29% 46.9%±8.1 46.8%
BH through the middle 24% 40.1%±8.5 43.3%
BH slice through the middle 5% 29.1%±12.8 34.4%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 208 shots

OptionUsedWin %Tour
BH crosscourt 27% 53.3%±9.4 52.5%
BH through the middle 21% 47.3%±10.3 46.3%
FH down the line 16% 49.4%±11.2 53.3%
FH crosscourt 14% 49.6%±11.6 54.0%
FH through the middle 11% 45.5%±12.6 45.5%
BH down the line 11% 60.0%±12.4 51.0%

Serve under pressure

Pressure predictability index +3 How much less varied Kate Makarova's first-serve direction gets on break points. Positive means easier to read. Based on 150 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 26% 19% 67% / 66%
Body 25% 16% ▼ 55% / 57%
T 50% 65% ▲ 62% / 68%

514 normal · 31 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 26% 33% 57% / 66%
Body 37% 28% ▼ 51% / 56%
T 37% 39% 71% / 64%

398 normal · 119 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. A direction loses 0.19 points per 100 serves for every 10 points of habitual usage, measured from WTA 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
Wide26% 57.2%±6.3 n=139 41% ▲
Body24% 49.5%±6.5 n=131 9% ▼
T50% 54.5%±4.7 n=275 50%

Consistent with an optimal mix (p = 0.26).
Optimal mix: +0.8 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide28% 55.2%±6.2 n=143 28%
Body35% 49.6%±5.7 n=179 19% ▼
T38% 60.7%±5.4 n=195 53% ▲

Off equilibrium (p = 0.034): serve T more. Gap 5.3 points per 100 first serves.
Optimal mix: +1.2 per 100 first serves.

Exploitability 0.96 points per 100 first serves What the optimal mix would win over the current one, both courts. More exploitable than 100% of WTA servers. Tested on matches they weren't fitted on, WTA mixes picked this way win 0.42 per 100 first serves on average.

Repeating the previous direction to the same court: +5.0±5.3 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. (396 repeats, 638 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 59 50% +5.7±8.7
1stAd courtT 118 33% −2.7±6.4
1stAd courtWide 113 30% −4.1±6.3
1stDeuce courtBody 69 40% −2.4±8.1
1stDeuce courtT 120 32% −0.4±6.3
1stDeuce courtWide 109 30% −4.4±6.4
2ndAd courtBody 65 53% −1.9±8.4
2ndAd courtT 40 49% −5.7±9.8
2ndAd courtWide 50 56% +2.8±9.1
2ndDeuce courtBody 88 48% −6.7±7.6
2ndDeuce courtT 68 53% −3.2±8.3
2ndDeuce courtWide 25 53% −0.8±11.1

Signature patterns

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

Serve → +1

  1. Body serve (ad court) → FH crosscourt used 2.6% · won 59% · +1.4±11.2 vs own baseline
  2. Body serve (deuce court) → BH down the line used 2.9% · won 58% · ±0.0±10.9 vs own baseline
  3. T serve (ad court) → FH crosscourt used 2.2% · won 57% · −1.1±11.6 vs own baseline
  4. Wide serve (ad court) → BH crosscourt used 3.3% · won 56% · −1.3±10.6 vs own baseline
  5. T serve (deuce court) → BH down the line used 2.5% · won 54% · −3.3±11.4 vs own baseline

Return

  1. vs wide serve (ad court) → FH through the middle, deep used 4.9% · won 50% · +3.1±11.5 vs own baseline
  2. vs T serve (deuce court) → FH through the middle, deep used 5.6% · won 49% · +2.1±11.1 vs own baseline
  3. vs body serve (deuce court) → FH through the middle, deep used 4.5% · won 48% · +1.1±11.7 vs own baseline
  4. vs T serve (ad court) → BH through the middle, mid used 8.3% · won 48% · +0.7±9.9 vs own baseline
  5. vs T serve (deuce court) → FH through the middle, mid used 7.0% · won 46% · −1.1±10.5 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → BH down the line used 6.8% · won 51% · +6.4±8.8 vs own baseline
  2. FH crosscourt → FH down the line used 8.5% · won 50% · +5.7±8.1 vs own baseline
  3. BH crosscourt → BH crosscourt used 4.0% · won 52% · +7.6±10.4 vs own baseline
  4. BH through the middle → BH crosscourt used 2.7% · won 53% · +8.0±11.4 vs own baseline
  5. BH down the line → FH down the line used 3.6% · won 50% · +5.1±10.7 vs own baseline

Discovered sequences

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

  1. FH crosscourt → BH crosscourt → FH down the line used 1.7% · won 55% · +8.6±10.1 vs own baseline · +11.7 vs tour on the same sequence Disrupted by Dominika Cibulkova (3/7), Caroline Wozniacki (6/9)
  2. BH crosscourt → FH crosscourt → BH crosscourt used 1.3% · won 53% · +6.7±11.0 vs own baseline · +9.9 vs tour on the same sequence Disrupted by Dominika Cibulkova (4/8), Venus Williams (7/8)
  3. BH crosscourt → BH crosscourt → BH down the line used 0.7% · won 55% · +8.9±12.8 vs own baseline · +20.7 vs tour on the same sequence Disrupted by Angelique Kerber (8/11)
  4. FH crosscourt → FH crosscourt → FH down the line used 1.0% · won 52% · +6.0±11.7 vs own baseline · +10.6 vs tour on the same sequence Disrupted by Lucie Safarova (3/8), Angelique Kerber (11/16)
  5. BH through the middle → FH crosscourt → BH crosscourt used 0.7% · won 50% · +4.0±12.9 vs own baseline · +8.0 vs tour on the same sequence Disrupted by Venus Williams (5/7)
  6. BH crosscourt → FH down the line → FH crosscourt used 0.8% · won 49% · +2.9±12.4 vs own baseline · +3.5 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 · rally+2.7246
BH to the middle · return+1.8173
T 1st serve · ad court+1.5195
Wide 1st serve · ad court+1.5143
T 1st serve · deuce court+0.6275

Most exposed to

FH to their backhand · rally−3.0269
Wide 1st serve · ad court−2.5170
FH to their forehand · rally−2.4304
BH to their forehand · rally−1.8199
BH to their backhand · rally−1.5139

Active players who are best at the shot in the top weakness: Clara Burel, Victoria Jimenez Kasintseva, Sara Sorribes Tormo, Arianne Hartono, Angelique Kerber

Tactical fingerprint

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

T serves · deuce50%
BH down the line26%
FH down the line35%
1st serve in67%
Unforced errors / shot12.5%
Point-ending shots24.8%
T serves · ad38%
Serve & volley0%
Deep returns32%
Forehand share53%
Avg rally length4.0
Points at net6%
Chipped returns6%
Through the middle26%
Backhand slice6%
Drop shots / shot0.7%
Run-around forehands1%
Wide serves · ad28%
Wide serves · deuce26%

Plays most like

  1. Simona Halep 2013–2022 plan v
  2. Katerina Siniakova 2015–2026 plan v
  3. Vera Zvonareva 2003–2020 plan v
  4. Alexandra Eala 2021–2026 plan v
  5. Ashlyn Krueger 2023–2026 plan v
  6. Venus Williams 1997–2026 plan v
  7. Garbine Muguruza 2013–2023 plan v
  8. Victoria Azarenka 2009–2025 plan v

Closest from another era

  1. Monica Seles 1990–2003
  2. Jennifer Capriati 1990–2002
  3. Arantxa Sanchez Vicario 1988–2001

Charted matches