RallyIQ

WTA · Right-handed · 42 charted matches · 2018–2025

Danielle Collins

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 60.2% ±2.7 raw 59.3% · tour 56.3% · 2,851 points
Return points won 46.3% ±2.8 raw 44.2% · tour 43.7% · 2,871 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 +0.30 ±0.07 better than 95% of WTA · raw +0.29
Shot selection +0.11 ±0.08 better than 57% of WTA · raw +0.09
Execution −0.53 ±0.52 better than 32% of WTA · raw −0.63
Tactical adaptability −0.04 first serves toward what's working, set to set · 41 matches
Adaptation speed +0.06 same, every two to three service games · per 100 first serves
Points left on the table 2.16 per 100 shots vs best direction · lower than 96% 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 12,883 shots.

Shot expected value

The share of points Danielle Collins 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 · 574 shots

OptionUsedWin %Tour
FH crosscourt 28% 61.6%±5.9 52.7%
BH crosscourt 18% 51.3%±7.4 50.9%
FH down the line 18% 51.6%±7.5 52.2%
FH through the middle 14% 50.2%±8.3 45.8%
BH through the middle 13% 44.5%±8.4 46.2%
BH down the line 9% 56.8%±9.5 50.0%

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

position worth 43% to the average player · 569 shots

OptionUsedWin %Tour
FH crosscourt 46% 48.4%±4.9 46.7%
FH down the line 25% 46.2%±6.5 44.9%
FH through the middle 19% 37.9%±7.0 41.3%
FH slice through the middle 4% 31.3%±11.9 29.2%
FH slice down the line 2% 24.6%±12.5 24.3%
FH slice crosscourt 2% 24.6%±12.9 31.9%

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

position worth 45% to the average player · 557 shots

OptionUsedWin %Tour
BH crosscourt 49% 51.0%±4.8 47.6%
BH down the line 19% 52.2%±7.3 46.8%
BH through the middle 18% 39.5%±7.4 43.3%
BH slice through the middle 4% 23.0%±10.6 34.4%
BH slice crosscourt 2% 31.5%±13.5 40.4%
BH lob through the middle 2% 27.2%±13.1 27.1%
BH lob crosscourt 2% 35.2%±14.3 32.8%

Return +1: drive to your middle

position worth 50% to the average player · 408 shots

OptionUsedWin %Tour
FH crosscourt 24% 46.6%±7.5 52.3%
BH crosscourt 22% 62.0%±7.6 50.8%
FH down the line 15% 47.1%±9.1 53.0%
FH through the middle 14% 52.3%±9.2 46.5%
BH down the line 12% 51.6%±9.8 50.6%
BH through the middle 12% 50.4%±10.0 46.2%

Serve under pressure

Pressure predictability index +2 How much less varied Danielle Collins's first-serve direction gets on break points. Positive means easier to read. Based on 300 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 49% 48% 66% / 66%
Body 12% 7% 62% / 57%
T 38% 45% 71% / 68%

1,412 normal · 75 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 46% 72% / 66%
Body 17% 16% 57% / 56%
T 34% 39% 66% / 64%

1,136 normal · 225 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
Wide49% 59.2%±2.9 n=732 49%
Body12% 61.2%±5.5 n=180 0% ▼
T39% 59.4%±3.3 n=575 51% ▲

Consistent with an optimal mix (p = 0.84).
Optimal mix: +0.2 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide49% 60.6%±3.0 n=665 64% ▲
Body17% 55.1%±5.1 n=225 1% ▼
T35% 59.2%±3.6 n=471 35%

Consistent with an optimal mix (p = 0.24).
Optimal mix: +0.9 per 100 first serves.

Exploitability 0.53 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: −1.8±3.7 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. (1,081 repeats, 1,683 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 243 41% −3.2±4.9
1stAd courtT 313 38% +2.0±4.3
1stAd courtWide 298 37% +2.8±4.4
1stDeuce courtBody 310 44% +1.4±4.4
1stDeuce courtT 281 34% +1.5±4.4
1stDeuce courtWide 360 34% +0.4±4.0
2ndAd courtBody 258 56% +1.0±4.8
2ndAd courtT 88 61% +5.6±7.4
2ndAd courtWide 177 52% −1.8±5.7
2ndDeuce courtBody 257 54% −0.7±4.8
2ndDeuce courtT 152 55% −0.6±6.1
2ndDeuce courtWide 119 54% +0.7±6.7

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 3.2% · won 63% · −0.9±7.4 vs own baseline
  2. Wide serve (deuce court) → BH through the middle used 2.2% · won 63% · −1.6±8.6 vs own baseline
  3. T serve (deuce court) → FH crosscourt used 2.4% · won 61% · −3.5±8.4 vs own baseline
  4. Body serve (ad court) → FH crosscourt used 2.0% · won 60% · −3.9±9.0 vs own baseline
  5. Wide serve (ad court) → BH through the middle used 2.0% · won 60% · −3.9±9.0 vs own baseline

Return

  1. vs wide serve (deuce court) → FH crosscourt, mid used 2.4% · won 61% · +17.5±8.7 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, deep used 2.3% · won 57% · +14.1±8.9 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, short used 2.2% · won 54% · +11.2±9.2 vs own baseline
  4. vs body serve (ad court) → BH crosscourt, mid used 2.2% · won 54% · +10.6±9.2 vs own baseline
  5. vs body serve (deuce court) → BH through the middle, deep used 2.2% · won 53% · +9.9±9.2 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH crosscourt used 7.4% · won 59% · +8.5±6.6 vs own baseline
  2. FH crosscourt → BH crosscourt used 6.1% · won 56% · +4.6±7.3 vs own baseline
  3. BH down the line → BH crosscourt used 1.5% · won 58% · +7.3±11.3 vs own baseline
  4. FH crosscourt → FH crosscourt used 6.3% · won 54% · +3.3±7.2 vs own baseline
  5. BH through the middle → FH down the line used 1.5% · won 55% · +4.3±11.3 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Danielle Collins 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 crosscourt used 0.5% · won 64% · +13.5±10.7 vs own baseline · +20.6 vs tour on the same sequence
  2. Wide serve → BH through the middle return, mid → FH crosscourt used 0.6% · won 63% · +11.9±10.5 vs own baseline · +14.2 vs tour on the same sequence
  3. BH crosscourt → BH crosscourt → BH crosscourt used 1.3% · won 57% · +6.6±8.5 vs own baseline · +11.1 vs tour on the same sequence Disrupted by Monica Puig (5/8), Karolina Muchova (4/6)
  4. BH crosscourt → BH down the line → FH crosscourt used 0.9% · won 58% · +7.4±9.7 vs own baseline · +14.4 vs tour on the same sequence Disrupted by Karolina Muchova (5/7)
  5. BH crosscourt → BH slice through the middle → FH crosscourt used 0.4% · won 61% · +10.8±11.9 vs own baseline · +15.0 vs tour on the same sequence Disrupted by Caroline Dolehide (5/7)
  6. Wide serve → FH through the middle return, mid → BH crosscourt used 0.6% · won 59% · +8.1±10.5 vs own baseline · +8.4 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 · serve +1+2.8215
BH to their backhand · return +1+2.5261
Body 2nd serve · ad court+1.7218
T 2nd serve · deuce court+1.4148
BH to their forehand · rally+1.2336

Most exposed to

BH to their forehand · serve +1−2.4171
FH to their forehand · serve +1−2.1280
FH to their backhand · rally−1.3418
FH to their backhand · return +1−1.2176
BH to the middle · serve +1−1.1313

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.18, Caroline Wozniacki +1.83, Angelique Kerber +1.36, Daria Kasatkina +1.34, Tatjana Maria +1.32

Favourable matchups

Sara Errani +1.66, Angelique Kerber +0.99, Elina Avanesyan +0.92, Marie Bouzkova +0.83, Katie Volynets +0.71

Active players who are best at the shot in the top weakness: Iga Swiatek, Belinda Bencic, Leylah Fernandez, Coco Gauff, Linda Noskova

Tactical fingerprint

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

Point-ending shots33.3%
Deep returns41%
Wide serves · deuce49%
Wide serves · ad49%
Unforced errors / shot12.4%
BH down the line22%
T serves · deuce39%
Drop shots / shot1.6%
Serve & volley0%
FH down the line28%
T serves · ad35%
Run-around forehands5%
Chipped returns6%
Points at net5%
Backhand slice6%
Forehand share50%
Through the middle23%
1st serve in56%
Avg rally length3.3

Plays most like

  1. Ekaterina Alexandrova 2017–2026 plan v
  2. Daniela Hantuchova 2002–2015 plan v
  3. Talia Gibson 2024–2026 plan v
  4. Anett Kontaveit 2015–2023 plan v
  5. Veronika Kudermetova 2018–2025 plan v
  6. Naomi Osaka 2016–2026 plan v
  7. Sorana Cirstea 2014–2026 plan v
  8. Aryna Sabalenka 2016–2026 plan v

Closest from another era

  1. Jelena Dokic 2000–2009
  2. Lindsay Davenport 1995–2006
  3. Elena Dementieva 1999–2010

Charted matches