RallyIQ

WTA · Right-handed · 20 charted matches · 2021–2026

Magdalena Frech

Archetype: Ad-court slider · Avoids the wide serve

Against an average opponent

Serve points won 56.9% ±2.9 raw 55.6% · tour 56.3% · 1,437 points
Return points won 44.4% ±2.9 raw 42.4% · tour 43.7% · 1,467 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 ±0.09 better than 78% of WTA · raw +0.15
Shot selection −0.42 ±0.11 better than 15% of WTA · raw −0.41
Execution +1.36 ±0.49 better than 96% of WTA · raw +1.48
Tactical adaptability +0.18 first serves toward what's working, set to set · 20 matches
Adaptation speed +0.19 same, every two to three service games · per 100 first serves
Points left on the table 2.39 per 100 shots vs best direction · lower than 78% 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 8,747 shots.

Shot expected value

The share of points Magdalena Frech 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 · 630 shots

OptionUsedWin %Tour
BH crosscourt 42% 43.0%±4.8 47.6%
BH through the middle 20% 41.0%±6.8 43.3%
BH down the line 10% 44.9%±9.1 46.8%
BH slice crosscourt 9% 36.6%±9.2 40.4%
BH slice through the middle 8% 27.6%±8.7 34.4%
BH drop shot crosscourt 4% 37.2%±11.6 47.5%
BH slice down the line 2% 34.4%±13.6 31.7%
BH lob through the middle 2% 20.7%±12.0 27.1%

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

position worth 43% to the average player · 550 shots

OptionUsedWin %Tour
FH crosscourt 44% 45.9%±5.1 46.7%
FH through the middle 28% 39.2%±6.1 41.3%
FH down the line 21% 42.9%±7.0 44.9%
FH slice through the middle 3% 22.7%±11.0 29.2%
FH lob through the middle 3% 31.1%±12.9 29.4%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 488 shots

OptionUsedWin %Tour
FH crosscourt 23% 49.7%±7.2 52.7%
FH down the line 21% 54.9%±7.4 52.2%
FH through the middle 15% 44.7%±8.5 45.8%
BH crosscourt 14% 44.5%±8.7 50.9%
BH through the middle 12% 48.4%±9.4 46.2%
BH down the line 7% 51.9%±11.2 50.0%
BH slice through the middle 5% 51.1%±12.5 44.8%

Long rally, 9+: drive to your backhand side

position worth 44% to the average player · 451 shots

OptionUsedWin %Tour
BH crosscourt 35% 46.4%±6.1 47.9%
BH through the middle 18% 34.5%±7.7 42.7%
BH slice crosscourt 13% 30.9%±8.5 38.7%
BH slice through the middle 11% 36.2%±9.4 33.4%
BH down the line 10% 49.8%±10.4 46.7%
BH drop shot crosscourt 4% 43.7%±13.6 48.7%
BH lob through the middle 3% 34.0%±13.8 29.4%
BH slice down the line 2% 31.6%±13.7 34.0%

Serve under pressure

Pressure predictability index −4 How much less varied Magdalena Frech's first-serve direction gets on break points. Positive means easier to read. Based on 173 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 37% 40% 62% / 66%
Body 12% 12% 59% / 57%
T 51% 48% 63% / 68%

702 normal · 42 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 41% 66% / 66%
Body 12% 17% 48% / 56%
T 39% 42% 56% / 64%

556 normal · 131 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
Wide37% 56.8%±4.7 n=275 34% ▼
Body12% 55.9%±7.4 n=92 0% ▼
T51% 58.6%±4.0 n=377 66% ▲

Consistent with an optimal mix (p = 0.78).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide47% 57.6%±4.3 n=325 62% ▲
Body13% 47.1%±7.5 n=89 0% ▼
T40% 51.3%±4.7 n=273 38% ▼

Off equilibrium (p = 0.033): serve wide more. Gap 3.9 points per 100 first serves.
Optimal mix: +0.8 per 100 first serves.

Exploitability 0.60 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: −4.1±4.1 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. (552 repeats, 839 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 118 39% −4.6±6.6
1stAd courtT 155 32% −3.3±5.7
1stAd courtWide 188 34% −0.8±5.3
1stDeuce courtBody 131 43% +0.1±6.4
1stDeuce courtT 153 29% −3.4±5.5
1stDeuce courtWide 196 32% −2.1±5.1
2ndAd courtBody 104 61% +5.8±6.9
2ndAd courtT 35 56% +1.1±10.1
2ndAd courtWide 101 60% +6.8±7.0
2ndDeuce courtBody 155 54% −0.2±6.0
2ndDeuce courtT 74 54% −2.4±8.0
2ndDeuce courtWide 50 56% +2.6±9.1

Signature patterns

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

Serve → +1

  1. Body serve (deuce court) → BH through the middle used 2.0% · won 61% · +2.6±10.9 vs own baseline
  2. Wide serve (ad court) → FH down the line used 2.2% · won 60% · +2.3±10.7 vs own baseline
  3. T serve (ad court) → BH crosscourt used 3.2% · won 59% · +1.0±9.6 vs own baseline
  4. Wide serve (deuce court) → FH crosscourt used 2.3% · won 58% · +0.2±10.6 vs own baseline
  5. T serve (deuce court) → FH crosscourt used 5.0% · won 58% · −0.1±8.3 vs own baseline

Return

  1. vs T serve (ad court) → FH through the middle, deep used 3.7% · won 51% · +5.6±10.2 vs own baseline
  2. vs wide serve (deuce court) → FH through the middle, deep used 3.4% · won 50% · +4.9±10.5 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, mid used 4.1% · won 49% · +4.1±9.9 vs own baseline
  4. vs body serve (deuce court) → BH through the middle, deep used 3.5% · won 49% · +4.1±10.4 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, mid used 4.7% · won 49% · +3.5±9.5 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.9% · won 54% · +10.8±9.8 vs own baseline
  2. FH down the line → FH down the line used 1.5% · won 55% · +11.4±10.4 vs own baseline
  3. BH crosscourt → FH down the line used 2.0% · won 51% · +7.9±9.7 vs own baseline
  4. BH crosscourt → FH crosscourt used 3.0% · won 50% · +6.0±8.5 vs own baseline
  5. BH slice through the middle → BH crosscourt used 1.2% · won 52% · +8.4±11.2 vs own baseline

Discovered sequences

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

  1. FH down the line → BH through the middle → FH down the line used 0.5% · won 55% · +11.0±11.7 vs own baseline · +13.6 vs tour on the same sequence Disrupted by Laura Pigossi (5/6)
  2. FH crosscourt → FH down the line → BH crosscourt used 0.9% · won 52% · +8.1±10.0 vs own baseline · +7.3 vs tour on the same sequence Disrupted by Daria Kasatkina (2/6)
  3. Wide serve → FH crosscourt return, mid → FH down the line used 0.5% · won 53% · +9.1±12.0 vs own baseline · +13.5 vs tour on the same sequence
  4. FH down the line → BH through the middle → FH crosscourt used 0.5% · won 53% · +9.1±12.0 vs own baseline · +6.6 vs tour on the same sequence Disrupted by Laura Pigossi (6/7)
  5. FH down the line → BH slice through the middle → FH crosscourt used 0.3% · won 55% · +10.9±12.9 vs own baseline · +8.8 vs tour on the same sequence
  6. FH down the line → FH crosscourt → BH crosscourt used 0.4% · won 54% · +9.4±12.5 vs own baseline · +18.3 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+4.6164
BH to their forehand · rally+3.4301
FH to the middle · rally+2.5423
BH to the middle · rally+2.5324
BH to the middle · return+2.3302

Most exposed to

FH to their backhand · rally−3.6667
FH to their backhand · return +1−3.3135
FH to their backhand · serve +1−2.2222
BH to their backhand · return +1−2.1149
FH to their forehand · rally−2.0798

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +3.78, Caroline Wozniacki +3.67, Angelique Kerber +3.17, Daria Kasatkina +3.09, Sara Errani +2.95

Favourable matchups

Sara Errani +3.25, Angelique Kerber +3.12, Marie Bouzkova +2.92, Elina Avanesyan +2.57, Linda Fruhvirtova +2.49

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 · deuce51%
Avg rally length5.0
Deep returns39%
Wide serves · ad47%
Drop shots / shot2.1%
Chipped returns15%
Backhand slice21%
1st serve in63%
T serves · ad40%
BH down the line21%
FH down the line29%
Serve & volley0%
Forehand share53%
Run-around forehands5%
Through the middle27%
Wide serves · deuce37%
Points at net4%
Unforced errors / shot7.3%
Point-ending shots16.3%

Plays most like

  1. Linda Fruhvirtova 2022–2025 plan v
  2. Dinara Safina 2007–2011 plan v
  3. Jaqueline Cristian 2021–2026 plan v
  4. Vera Zvonareva 2003–2020 plan v
  5. Elina Svitolina 2013–2026 plan v
  6. Caroline Wozniacki 2008–2024 plan v
  7. Victoria Azarenka 2009–2025 plan v
  8. Daria Kasatkina 2015–2026 plan v

Closest from another era

  1. Elena Dementieva 1999–2010
  2. Monica Seles 1990–2003
  3. Marion Bartoli 2003–2013

Charted matches