RallyIQ

WTA · Left-handed · 30 charted matches · 2021–2026

Alexandra Eala

Archetype: Ad-court T server · Rallies through the middle

Against an average opponent

Serve points won 55.6% ±2.9 raw 54.2% · tour 56.3% · 1,824 points
Return points won 46.8% ±2.9 raw 45.3% · tour 43.7% · 1,970 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 −0.02 ±0.07 better than 50% of WTA · raw −0.02
Shot selection +0.35 ±0.15 better than 83% of WTA · raw +0.36
Execution +0.51 ±0.45 better than 79% of WTA · raw +0.61
Tactical adaptability +0.19 first serves toward what's working, set to set · 30 matches
Adaptation speed −0.01 same, every two to three service games · per 100 first serves
Points left on the table 2.89 per 100 shots vs best direction · lower than 16% 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 9,057 shots.

Shot expected value

The share of points Alexandra Eala 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 · 543 shots

OptionUsedWin %Tour
FH crosscourt 22% 48.6%±7.0 52.7%
FH down the line 20% 50.3%±7.2 52.2%
FH through the middle 17% 41.2%±7.7 45.8%
BH through the middle 15% 44.5%±8.0 46.2%
BH crosscourt 15% 62.3%±7.9 50.9%
BH down the line 7% 50.0%±10.8 50.0%

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

position worth 45% to the average player · 531 shots

OptionUsedWin %Tour
BH crosscourt 41% 51.5%±5.4 47.6%
BH through the middle 31% 43.5%±6.0 43.3%
BH down the line 12% 49.2%±9.1 46.8%
FH inside-out 3% 46.1%±13.3 52.5%
FH inside-in 3% 53.3%±14.1 55.6%
BH slice through the middle 2% 36.0%±13.7 34.4%
BH slice crosscourt 2% 30.6%±13.2 40.4%

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

position worth 43% to the average player · 404 shots

OptionUsedWin %Tour
FH crosscourt 45% 52.7%±5.8 46.7%
FH through the middle 22% 41.5%±7.8 41.3%
FH down the line 22% 52.8%±7.9 44.9%
FH slice through the middle 4% 26.6%±12.0 29.2%
BH inside-in 2% 51.3%±15.0 47.0%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 328 shots

OptionUsedWin %Tour
FH crosscourt 25% 48.3%±8.2 54.0%
FH down the line 18% 55.8%±9.1 53.3%
BH through the middle 18% 36.6%±8.9 46.3%
BH crosscourt 18% 54.5%±9.3 52.5%
FH through the middle 13% 37.7%±10.0 45.5%
BH down the line 6% 55.5%±12.9 51.0%

Serve under pressure

Pressure predictability index +3 How much less varied Alexandra Eala's first-serve direction gets on break points. Positive means easier to read. Based on 220 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 29% 38% ▲ 66% / 66%
Body 30% 18% ▼ 56% / 57%
T 41% 45% 55% / 68%

889 normal · 56 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 39% 40% 61% / 66%
Body 27% 21% 55% / 56%
T 35% 39% 62% / 64%

708 normal · 164 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
Wide30% 56.8%±4.6 n=281 45% ▲
Body29% 50.7%±4.7 n=273 16% ▼
T41% 50.8%±4.0 n=391 39% ▼

Consistent with an optimal mix (p = 0.14).
Optimal mix: +0.7 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide39% 56.7%±4.2 n=339 54% ▲
Body26% 55.0%±5.1 n=224 11% ▼
T35% 55.6%±4.4 n=309 35%

Consistent with an optimal mix (p = 0.89).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.54 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: −2.4±4.5 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. (495 repeats, 1,262 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 124 49% +4.9±6.6
1stAd courtT 220 41% +5.5±5.1
1stAd courtWide 222 36% +1.4±5.0
1stDeuce courtBody 143 41% −1.1±6.2
1stDeuce courtT 209 27% −5.5±4.7
1stDeuce courtWide 277 39% +4.8±4.6
2ndAd courtBody 146 53% −1.9±6.2
2ndAd courtT 126 61% +5.5±6.4
2ndAd courtWide 101 57% +3.0±7.1
2ndDeuce courtBody 184 58% +3.2±5.6
2ndDeuce courtT 64 58% +2.3±8.4
2ndDeuce courtWide 146 52% −1.4±6.2

Signature patterns

Recurring sequences that win more than Alexandra Eala'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 4.5% · won 63% · +6.1±7.8 vs own baseline
  2. Body serve (ad court) → FH down the line used 3.6% · won 62% · +4.8±8.6 vs own baseline
  3. T serve (deuce court) → BH crosscourt used 3.1% · won 61% · +3.9±9.0 vs own baseline
  4. T serve (ad court) → FH crosscourt used 2.0% · won 55% · −2.0±10.4 vs own baseline
  5. Body serve (deuce court) → FH through the middle used 2.4% · won 53% · −3.9±9.9 vs own baseline

Return

  1. vs T serve (ad court) → BH through the middle, deep used 4.3% · won 58% · +9.9±8.5 vs own baseline
  2. vs wide serve (deuce court) → BH through the middle, deep used 4.1% · won 57% · +8.4±8.6 vs own baseline
  3. vs wide serve (ad court) → FH crosscourt, deep used 2.6% · won 58% · +9.9±10.0 vs own baseline
  4. vs T serve (ad court) → BH crosscourt, mid used 2.4% · won 58% · +9.5±10.2 vs own baseline
  5. vs wide serve (ad court) → FH through the middle, deep used 3.2% · won 55% · +6.3±9.5 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → BH crosscourt used 4.0% · won 57% · +6.6±8.8 vs own baseline
  2. FH down the line → BH crosscourt used 4.6% · won 56% · +5.5±8.5 vs own baseline
  3. BH crosscourt → FH crosscourt used 5.0% · won 56% · +5.1±8.2 vs own baseline
  4. FH crosscourt → FH down the line used 7.5% · won 55% · +4.0±7.0 vs own baseline
  5. FH through the middle → FH crosscourt used 2.0% · won 55% · +4.0±10.9 vs own baseline

Discovered sequences

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

  1. FH crosscourt → BH through the middle → BH crosscourt used 0.7% · won 62% · +13.1±10.7 vs own baseline · +22.1 vs tour on the same sequence
  2. Wide serve → BH crosscourt return, mid → FH down the line used 0.5% · won 61% · +11.4±12.0 vs own baseline · +24.0 vs tour on the same sequence
  3. BH crosscourt → FH down the line → FH crosscourt used 0.7% · won 58% · +8.7±11.0 vs own baseline · +16.4 vs tour on the same sequence
  4. FH down the line → FH crosscourt → BH crosscourt used 1.5% · won 55% · +5.9±8.9 vs own baseline · +9.2 vs tour on the same sequence Disrupted by Iva Jovic (4/9), Magda Linette (4/6)
  5. BH through the middle → BH through the middle → FH crosscourt used 0.5% · won 58% · +8.8±11.8 vs own baseline · +19.3 vs tour on the same sequence
  6. BH crosscourt → FH crosscourt → BH crosscourt used 1.4% · won 53% · +4.1±9.0 vs own baseline · +7.0 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 · return+5.4332
BH to their forehand · rally+4.4452
BH to their forehand · return +1+4.2149
FH to their backhand · return+3.1258
FH to their forehand · serve +1+2.0277

Most exposed to

FH to their forehand · return +1−5.1143
BH to their forehand · serve +1−4.5158
FH to their forehand · serve +1−4.3277
BH to their forehand · return−3.8256
FH to their forehand · rally−3.1423

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Caroline Wozniacki +3.67, Sara Sorribes Tormo +3.35, Angelique Kerber +3.12, Daria Kasatkina +2.99, Linda Fruhvirtova +2.78

Favourable matchups

Sara Errani +3.69, Angelique Kerber +3.53, Elina Avanesyan +3.06, Marie Bouzkova +2.97, Linda Fruhvirtova +2.54

Active players who are best at the shot in the top weakness: Sara Errani, Paula Badosa, Victoria Azarenka, Linda Noskova, Sara Sorribes Tormo

Tactical fingerprint

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

Deep returns37%
T serves · deuce41%
FH down the line32%
Point-ending shots26.4%
1st serve in64%
Run-around forehands9%
Through the middle30%
Forehand share54%
Serve & volley0%
T serves · ad35%
Wide serves · ad39%
Drop shots / shot1.2%
Chipped returns7%
Unforced errors / shot9.7%
Points at net5%
Backhand slice8%
Avg rally length3.9
BH down the line17%
Wide serves · deuce30%

Plays most like

  1. Diana Shnaider 2022–2026 plan v
  2. Jasmine Paolini 2016–2026 plan v
  3. Jaqueline Cristian 2021–2026 plan v
  4. Dominika Cibulkova 2009–2019 plan v
  5. Anna Blinkova 2019–2026 plan v
  6. Eugenie Bouchard 2013–2023 plan v
  7. Marta Kostyuk 2018–2026 plan v
  8. Nao Hibino 2016–2025 plan v

Closest from another era

  1. Daniela Hantuchova 2002–2015
  2. Elena Dementieva 1999–2010
  3. Jelena Dokic 2000–2009

Charted matches