RallyIQ

WTA · Left-handed · 9 charted matches · 2022–2026

Robin Montgomery

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

Against an average opponent

Serve points won 58.5% ±3.7 raw 58.0% · tour 56.3% · 550 points
Return points won 43.0% ±3.7 raw 41.7% · tour 43.7% · 559 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 −0.38 ±0.19 better than 2% of WTA · raw −0.37
Shot selection +0.05 ±0.23 better than 50% of WTA · raw +0.08
Execution −1.17 ±1.25 better than 16% of WTA · raw −0.97

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 2,733 shots.

Shot expected value

The share of points Robin Montgomery 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 · 206 shots

OptionUsedWin %Tour
FH down the line 23% 49.9%±10.0 52.2%
BH through the middle 22% 47.3%±10.1 46.2%
FH crosscourt 20% 49.3%±10.4 52.7%
FH through the middle 19% 44.3%±10.6 45.8%
BH crosscourt 11% 48.1%±12.7 50.9%
BH down the line 5% 46.7%±15.0 50.0%

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

position worth 43% to the average player · 122 shots

OptionUsedWin %Tour
FH crosscourt 44% 49.1%±9.6 46.7%
FH through the middle 36% 41.0%±10.1 41.3%
FH down the line 20% 49.9%±12.4 44.9%

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

position worth 45% to the average player · 118 shots

OptionUsedWin %Tour
BH crosscourt 42% 57.9%±9.7 47.6%
BH through the middle 34% 37.8%±10.3 43.3%
BH down the line 14% 38.8%±13.2 46.8%
BH slice through the middle 9% 31.9%±13.8 34.4%

Return +1: drive to your middle

position worth 50% to the average player · 99 shots

OptionUsedWin %Tour
BH through the middle 24% 52.8%±12.4 46.2%
FH crosscourt 24% 55.6%±12.3 52.3%
FH through the middle 20% 43.3%±12.9 46.5%
BH crosscourt 16% 50.4%±13.7 50.8%
FH down the line 10% 42.0%±14.8 53.0%

Serve under pressure

Pressure predictability index +7 How much less varied Robin Montgomery's first-serve direction gets on break points. Positive means easier to read. Based on 60 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 33% 18% ▼ 72% / 66%
Body 27% 35% 62% / 57%
T 39% 47% 69% / 68%

270 normal · 17 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 36% 53% ▲ 61% / 66%
Body 22% 16% 60% / 56%
T 42% 30% ▼ 73% / 64%

219 normal · 43 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
Wide32% 55.5%±7.4 n=93 32%
Body28% 57.5%±7.8 n=80 13% ▼
T40% 60.1%±6.7 n=114 55% ▲

Consistent with an optimal mix (p = 0.66).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide39% 55.9%±7.1 n=102 39%
Body21% 58.8%±8.7 n=56 6% ▼
T40% 60.6%±6.9 n=104 55% ▲

Consistent with an optimal mix (p = 0.67).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.56 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: +2.6±5.9 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. (160 repeats, 371 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 34 57% +12.6±10.2
1stAd courtT 55 37% +1.7±8.6
1stAd courtWide 67 35% +0.9±8.0
1stDeuce courtBody 56 39% −3.3±8.7
1stDeuce courtT 52 26% −5.7±8.0
1stDeuce courtWide 85 31% −3.4±7.1
2ndAd courtBody 56 54% −1.0±8.8
2ndAd courtT 26 46% −9.5±10.9
2ndAd courtWide 30 50% −3.4±10.6
2ndDeuce courtBody 43 57% +2.2±9.5
2ndDeuce courtT 11 56% −0.4±12.8
2ndDeuce courtWide 44 53% −0.9±9.5

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH down the line used 6.3% · won 58% · −5.5±11.3 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 6.3% · won 52% · −11.3±11.4 vs own baseline

Return

  1. vs wide serve (deuce court) → BH through the middle, deep used 13.8% · won 54% · +2.8±11.0 vs own baseline
  2. vs wide serve (deuce court) → BH through the middle, mid used 10.6% · won 53% · +1.4±11.8 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 6.4% · won 50% · +2.0±10.7 vs own baseline
  2. FH through the middle → FH crosscourt used 6.6% · won 47% · −0.4±10.6 vs own baseline
  3. FH through the middle → BH through the middle used 4.4% · won 47% · −1.0±11.7 vs own baseline
  4. FH crosscourt → FH crosscourt used 6.9% · won 46% · −1.2±10.5 vs own baseline
  5. BH through the middle → FH through the middle used 6.4% · won 46% · −1.3±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 Robin Montgomery 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 through the middle used 1.4% · won 52% · +4.8±12.7 vs own baseline · +12.8 vs tour on the same sequence
  2. FH crosscourt → BH through the middle → FH down the line used 1.3% · won 51% · +3.6±12.9 vs own baseline · +1.9 vs tour on the same sequence
  3. FH crosscourt → BH crosscourt → FH down the line used 1.4% · won 49% · +2.4±12.7 vs own baseline · +4.6 vs tour on the same sequence
  4. BH crosscourt → FH crosscourt → BH down the line used 1.3% · won 46% · −1.3±12.8 vs own baseline · −4.8 vs tour on the same sequence
  5. FH crosscourt → BH crosscourt → FH crosscourt used 2.1% · won 45% · −2.4±11.4 vs own baseline · −6.0 vs tour on the same sequence Disrupted by Marta Kostyuk (2/7), Elina Avanesyan (5/7)
  6. FH crosscourt → BH crosscourt → FH through the middle used 1.9% · won 43% · −3.8±11.8 vs own baseline · −3.3 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

FH to their backhand · rally+1.3203
BH to the middle · return+0.6121
FH to the middle · return−0.7148
BH to the middle · rally−1.8123
FH to their forehand · rally−2.0123

Most exposed to

BH to the middle · return−0.3145
FH to the middle · rally−0.3123
Wide 1st serve · deuce court−0.2133
FH to their backhand · rally±0.0152
Wide 1st serve · ad court+0.2122

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.

Forehand share60%
Through the middle35%
Deep returns39%
Unforced errors / shot13.2%
T serves · deuce40%
Point-ending shots25.6%
T serves · ad40%
Serve & volley0%
Drop shots / shot1.4%
BH down the line19%
FH down the line28%
1st serve in61%
Wide serves · ad39%
Backhand slice9%
Chipped returns6%
Run-around forehands3%
Avg rally length3.8
Points at net4%
Wide serves · deuce32%

Plays most like

  1. Maya Joint 2024–2026 plan v
  2. Irina Camelia Begu 2015–2024 plan v
  3. Xiyu Wang 2019–2025 plan v
  4. Dominika Cibulkova 2009–2019 plan v
  5. Nao Hibino 2016–2025 plan v
  6. Shuai Zhang 2009–2026 plan v
  7. Bernarda Pera 2017–2025 plan v
  8. Lulu Sun 2022–2025 plan v

Closest from another era

  1. Dinara Safina 2007–2011
  2. Daniela Hantuchova 2002–2015
  3. Jelena Dokic 2000–2009

Charted matches