RallyIQ

WTA · Right-handed · 8 charted matches · 2012–2021

Christina Mchale

Archetype: Forehand line-changer · Backhand line-changer

Against an average opponent

Serve points won 55.2% ±3.5 raw 53.6% · tour 56.3% · 608 points
Return points won 43.7% ±3.6 raw 39.6% · tour 43.7% · 573 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 −0.14 ±0.15 better than 27% of WTA · raw −0.14
Shot selection −0.33 ±0.30 better than 20% of WTA · raw −0.33
Execution −1.07 ±0.98 better than 17% of WTA · raw −1.05
Points left on the table 2.82 per 100 shots vs best direction · lower than 22% 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 3,138 shots.

Shot expected value

The share of points Christina Mchale 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 45% to the average player · 195 shots

OptionUsedWin %Tour
BH through the middle 35% 45.7%±8.7 43.3%
BH crosscourt 27% 46.6%±9.7 47.6%
BH down the line 15% 44.7%±11.6 46.8%
BH slice through the middle 10% 35.6%±12.6 34.4%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 167 shots

OptionUsedWin %Tour
FH down the line 40% 52.8%±8.9 52.2%
FH crosscourt 19% 54.0%±11.5 52.7%
BH through the middle 13% 41.1%±12.5 46.2%
FH through the middle 13% 46.7%±12.8 45.8%
BH down the line 9% 51.4%±13.9 50.0%
BH crosscourt 7% 47.4%±14.5 50.9%

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

position worth 43% to the average player · 130 shots

OptionUsedWin %Tour
FH down the line 36% 40.3%±9.9 44.9%
FH crosscourt 29% 42.0%±10.7 46.7%
FH through the middle 25% 44.7%±11.3 41.3%

Long rally, 9+: drive to your backhand side

position worth 44% to the average player · 88 shots

OptionUsedWin %Tour
BH through the middle 32% 49.0%±11.9 42.7%
BH crosscourt 24% 42.9%±12.7 47.9%
BH down the line 22% 47.0%±13.1 46.7%
BH slice crosscourt 14% 36.7%±14.0 38.7%

Serve under pressure

Pressure predictability index +3 How much less varied Christina Mchale's first-serve direction gets on break points. Positive means easier to read. Based on 69 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 44% 47% 63% / 66%
Body 20% 7% ▼ 58% / 57%
T 36% 47% ▲ 57% / 68%

296 normal · 15 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 40% 30% ▼ 60% / 66%
Body 25% 30% 54% / 56%
T 35% 41% 66% / 64%

241 normal · 54 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
Wide44% 56.7%±6.3 n=137 59% ▲
Body19% 52.3%±8.7 n=59 4% ▼
T37% 54.7%±6.8 n=115 37%

Consistent with an optimal mix (p = 0.70).
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide38% 51.4%±6.9 n=112 38%
Body26% 51.1%±7.9 n=77 11% ▼
T36% 54.0%±7.0 n=106 51% ▲

Consistent with an optimal mix (p = 0.83).
Optimal mix: +0.7 per 100 first serves.

Exploitability 0.65 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: +4.4±4.2 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. (248 repeats, 342 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 38 38% −5.4±9.7
1stAd courtT 81 34% −1.6±7.4
1stAd courtWide 43 31% −3.9±8.9
1stDeuce courtBody 35 43% +0.1±10.1
1stDeuce courtT 57 33% +0.8±8.3
1stDeuce courtWide 85 30% −4.3±7.0
2ndAd courtBody 58 51% −4.5±8.8
2ndAd courtT 28 54% −0.7±10.8
2ndAd courtWide 28 47% −6.9±10.8
2ndDeuce courtBody 65 50% −4.6±8.4
2ndDeuce courtT 31 57% +1.0±10.4
2ndDeuce courtWide 23 57% +3.1±11.2

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → BH crosscourt used 4.9% · won 55% · −3.1±11.7 vs own baseline
  2. Wide serve (deuce court) → FH down the line used 6.2% · won 50% · −8.0±11.1 vs own baseline

Return

  1. Not enough data

Rally, consecutive own shots

  1. FH down the line → BH through the middle used 5.7% · won 49% · +2.3±11.4 vs own baseline
  2. FH crosscourt → FH down the line used 5.2% · won 49% · +2.3±11.6 vs own baseline
  3. BH through the middle → FH through the middle used 4.9% · won 48% · +1.3±11.7 vs own baseline
  4. FH down the line → FH down the line used 5.7% · won 47% · +0.4±11.4 vs own baseline
  5. FH crosscourt → FH crosscourt used 5.4% · won 46% · −0.6±11.5 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH through the middle → FH down the line used 1.1% · won 53% · +6.3±12.9 vs own baseline · +8.9 vs tour on the same sequence Disrupted by Georgina Garcia Perez (5/7)
  2. FH down the line → BH crosscourt → BH through the middle used 1.6% · won 51% · +4.8±11.6 vs own baseline · +12.2 vs tour on the same sequence
  3. FH crosscourt → FH crosscourt → FH crosscourt used 1.2% · won 51% · +5.0±12.4 vs own baseline · +9.6 vs tour on the same sequence Disrupted by Georgina Garcia Perez (5/7)
  4. FH down the line → BH through the middle → FH down the line used 1.4% · won 49% · +2.8±12.1 vs own baseline · −0.7 vs tour on the same sequence Disrupted by Ana Ivanovic (4/6)
  5. BH crosscourt → BH through the middle → FH down the line used 1.0% · won 49% · +2.6±13.0 vs own baseline · ±0.0 vs tour on the same sequence
  6. FH down the line → BH crosscourt → BH crosscourt used 1.1% · won 45% · −1.0±12.8 vs own baseline · −4.6 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

BH to the middle · rally+2.2130
Wide 1st serve · deuce court±0.0137
FH to their forehand · rally−1.7178
FH to their backhand · rally−2.6222

Most exposed to

BH to the middle · return−2.8133
BH to their backhand · rally−2.2161
Wide 1st serve · deuce court−0.9130
FH to the middle · return±0.0135
T 1st serve · ad court+0.7134

Active players who are best at the shot in the top weakness: Sara Sorribes Tormo, Maja Chwalinska, Daria Saville, Daria Kasatkina, Caroline Wozniacki

Tactical fingerprint

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

FH down the line42%
Forehand share57%
Chipped returns21%
BH down the line25%
1st serve in66%
Wide serves · deuce44%
Run-around forehands10%
Through the middle30%
Backhand slice18%
Avg rally length4.2
T serves · deuce37%
Unforced errors / shot10.5%
Serve & volley0%
T serves · ad36%
Wide serves · ad38%
Points at net6%
Point-ending shots22.0%
Drop shots / shot0.7%
Deep returns26%

Plays most like

  1. Shelby Rogers 2014–2024 plan v
  2. Elise Mertens 2018–2026 plan v
  3. Svetlana Kuznetsova 2004–2021 plan v
  4. Cristina Bucsa 2016–2026 plan v
  5. Victoria Azarenka 2009–2025 plan v
  6. Victoria Mboko 2022–2026 plan v
  7. Mirra Andreeva 2022–2026 plan v
  8. Simona Halep 2013–2022 plan v

Closest from another era

  1. Martina Hingis 1996–2007
  2. Monica Seles 1990–2003
  3. Lindsay Davenport 1995–2006

Charted matches