RallyIQ

WTA · Right-handed · 12 charted matches · 2023–2026

Alina Korneeva

Archetype: Ad-court slider · Avoids the wide serve

Against an average opponent

Serve points won 57.0% ±3.8 raw 54.6% · tour 56.3% · 831 points
Return points won 49.1% ±3.9 raw 50.6% · tour 43.7% · 850 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 −0.01 ±0.10 better than 51% of WTA · raw −0.01
Shot selection +0.25 ±0.25 better than 73% of WTA · raw +0.26
Execution +0.66 ±0.76 better than 84% of WTA · raw +0.70
Tactical adaptability −0.05 first serves toward what's working, set to set · 12 matches
Adaptation speed −0.17 same, every two to three service games · per 100 first serves
Points left on the table 2.48 per 100 shots vs best direction · lower than 67% 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 5,154 shots.

Shot expected value

The share of points Alina Korneeva 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 50% to the average player · 340 shots

OptionUsedWin %Tour
FH down the line 26% 46.2%±7.9 52.2%
FH crosscourt 22% 53.8%±8.5 52.7%
BH crosscourt 15% 52.4%±9.8 50.9%
FH through the middle 15% 47.4%±9.8 45.8%
BH through the middle 12% 45.4%±10.6 46.2%
BH down the line 6% 56.4%±13.1 50.0%

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

position worth 45% to the average player · 288 shots

OptionUsedWin %Tour
BH crosscourt 42% 44.3%±6.9 47.6%
BH through the middle 31% 41.5%±7.7 43.3%
BH down the line 14% 45.6%±10.6 46.8%
BH slice through the middle 6% 34.8%±12.9 34.4%
BH slice crosscourt 5% 46.0%±13.9 40.4%

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

position worth 43% to the average player · 257 shots

OptionUsedWin %Tour
FH crosscourt 53% 54.1%±6.6 46.7%
FH down the line 21% 48.0%±9.5 44.9%
FH through the middle 21% 49.7%±9.6 41.3%

Long rally, 9+: drive to your forehand side

position worth 44% to the average player · 202 shots

OptionUsedWin %Tour
FH crosscourt 45% 49.4%±7.8 47.0%
FH down the line 23% 52.7%±10.0 46.4%
FH through the middle 23% 48.9%±10.1 41.5%
FH slice through the middle 6% 33.9%±13.8 29.3%

Serve under pressure

Pressure predictability index +7 How much less varied Alina Korneeva's first-serve direction gets on break points. Positive means easier to read. Based on 103 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 36% 30% 66% / 66%
Body 36% 30% 54% / 57%
T 28% 40% ▲ 66% / 68%

412 normal · 20 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 46% 58% ▲ 59% / 66%
Body 27% 20% 62% / 56%
T 27% 22% 70% / 64%

313 normal · 83 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
Wide36% 57.8%±6.0 n=154 48% ▲
Body36% 53.3%±6.1 n=154 21% ▼
T29% 57.1%±6.6 n=124 31% ▲

Consistent with an optimal mix (p = 0.58).
Optimal mix: +0.7 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide48% 52.7%±5.5 n=191 49%
Body26% 52.7%±7.2 n=101 10% ▼
T26% 54.8%±7.1 n=104 41% ▲

Consistent with an optimal mix (p = 0.89).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.64 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: −0.2±7.9 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. (252 repeats, 552 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 84 49% +5.4±7.7
1stAd courtT 87 49% +13.8±7.6
1stAd courtWide 94 40% +5.3±7.2
1stDeuce courtBody 87 48% +5.1±7.6
1stDeuce courtT 60 36% +4.1±8.3
1stDeuce courtWide 137 40% +5.6±6.2
2ndAd courtBody 87 54% −0.8±7.6
2ndAd courtT 12 58% +3.3±12.5
2ndAd courtWide 47 51% −2.8±9.4
2ndDeuce courtBody 94 62% +7.1±7.2
2ndDeuce courtT 17 57% +1.0±11.9
2ndDeuce courtWide 44 64% +9.9±9.2

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH down the line used 4.3% · won 58% · +0.7±10.8 vs own baseline
  2. Body serve (deuce court) → FH crosscourt used 5.7% · won 57% · −1.2±10.0 vs own baseline
  3. Body serve (ad court) → FH crosscourt used 3.3% · won 56% · −2.2±11.5 vs own baseline
  4. Wide serve (ad court) → BH crosscourt used 3.3% · won 56% · −2.2±11.5 vs own baseline
  5. T serve (deuce court) → BH crosscourt used 3.3% · won 56% · −2.2±11.5 vs own baseline

Return

  1. vs T serve (ad court) → FH through the middle, mid used 4.5% · won 66% · +10.5±11.1 vs own baseline
  2. vs body serve (deuce court) → BH through the middle, deep used 5.7% · won 63% · +7.0±10.6 vs own baseline
  3. vs body serve (ad court) → BH through the middle, mid used 4.3% · won 61% · +5.8±11.5 vs own baseline
  4. vs wide serve (ad court) → BH through the middle, deep used 4.7% · won 59% · +3.4±11.3 vs own baseline
  5. vs body serve (ad court) → BH through the middle, deep used 4.9% · won 58% · +2.3±11.2 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → BH through the middle used 3.0% · won 57% · +4.5±10.3 vs own baseline
  2. BH through the middle → FH through the middle used 2.4% · won 56% · +4.4±10.9 vs own baseline
  3. FH crosscourt → FH crosscourt used 6.0% · won 54% · +2.3±8.3 vs own baseline
  4. FH down the line → FH crosscourt used 3.7% · won 54% · +1.7±9.8 vs own baseline
  5. BH through the middle → FH crosscourt used 5.8% · won 53% · +1.3±8.4 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH crosscourt → FH crosscourt used 2.0% · won 57% · +7.8±9.0 vs own baseline · +12.4 vs tour on the same sequence Disrupted by Mirra Andreeva (13/26), Sara Sorribes Tormo (7/9)
  2. FH crosscourt → FH crosscourt → FH through the middle used 1.1% · won 59% · +9.1±10.7 vs own baseline · +22.4 vs tour on the same sequence Disrupted by Mirra Andreeva (6/12)
  3. FH crosscourt → FH through the middle → FH down the line used 1.2% · won 57% · +7.1±10.6 vs own baseline · +8.1 vs tour on the same sequence Disrupted by Sara Sorribes Tormo (10/17)
  4. BH through the middle → FH crosscourt → FH crosscourt used 0.9% · won 56% · +6.2±11.4 vs own baseline · +17.0 vs tour on the same sequence Disrupted by Mirra Andreeva (8/12), Sara Sorribes Tormo (6/7)
  5. BH crosscourt → BH through the middle → FH crosscourt used 1.2% · won 54% · +4.6±10.7 vs own baseline · +3.7 vs tour on the same sequence Disrupted by Mirra Andreeva (6/16), Sara Sorribes Tormo (6/7)
  6. BH down the line → FH crosscourt → FH crosscourt used 0.6% · won 56% · +6.2±12.6 vs own baseline · +16.8 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 forehand · return+3.6132
FH to the middle · return+2.5159
FH to their backhand · serve +1+2.3138
FH to their backhand · rally+1.8345
FH to their forehand · rally+1.2420

Most exposed to

FH to the middle · rally−3.2237
BH to the middle · return−2.6199
BH to their forehand · rally−1.8165
FH to the middle · serve +1−1.0125
FH to their forehand · rally−0.7371

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +3.46, Caroline Wozniacki +3.02, Daria Kasatkina +2.45, Angelique Kerber +2.26, Tatjana Maria +2.20

Favourable matchups

Sara Errani +2.75, Angelique Kerber +2.56, Marie Bouzkova +2.41, Linda Fruhvirtova +2.12, Magdalena Frech +2.03

Active players who are best at the shot in the top weakness: Sara Sorribes Tormo, Caroline Wozniacki, Linda Fruhvirtova, Daria Kasatkina, Magdalena Frech

Tactical fingerprint

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

Avg rally length5.0
Deep returns40%
FH down the line35%
Points at net11%
Wide serves · ad48%
Forehand share55%
Drop shots / shot1.8%
Serve & volley1%
BH down the line20%
Backhand slice13%
1st serve in61%
Point-ending shots22.7%
Chipped returns7%
Run-around forehands4%
Unforced errors / shot9.6%
Through the middle27%
Wide serves · deuce36%
T serves · deuce29%
T serves · ad26%

Plays most like

  1. Sara Bejlek 2022–2026 plan v
  2. Emma Navarro 2019–2026 plan v
  3. Marta Kostyuk 2018–2026 plan v
  4. Victoria Azarenka 2009–2025 plan v
  5. Nao Hibino 2016–2025 plan v
  6. Flavia Pennetta 2006–2015 plan v
  7. Magda Linette 2016–2026 plan v
  8. Leylah Fernandez 2020–2026 plan v

Closest from another era

  1. Dinara Safina 2007–2011
  2. Elena Dementieva 1999–2010
  3. Daniela Hantuchova 2002–2015

Charted matches