RallyIQ

WTA · Right-handed · 8 charted matches · 2014–2018

Nicole Gibbs

Against an average opponent

Serve points won 53.0% ±3.8 raw 51.4% · tour 56.3% · 512 points
Return points won 41.3% ±3.8 raw 38.4% · tour 43.7% · 430 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 −0.12 ±0.17 better than 33% of WTA · raw −0.09
Shot selection −0.43 ±0.33 better than 14% of WTA · raw −0.37
Execution −1.58 ±0.92 better than 9% of WTA · raw −1.15

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 2,690 shots.

Shot expected value

The share of points Nicole Gibbs 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 · 172 shots

OptionUsedWin %Tour
BH crosscourt 38% 47.7%±8.9 47.6%
BH through the middle 30% 48.1%±9.7 43.3%
BH down the line 12% 47.2%±12.8 46.8%
BH slice through the middle 10% 36.5%±12.8 34.4%
BH slice crosscourt 9% 47.5%±13.7 40.4%

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

position worth 43% to the average player · 152 shots

OptionUsedWin %Tour
FH crosscourt 55% 39.8%±7.9 46.7%
FH through the middle 26% 38.8%±10.3 41.3%
FH down the line 15% 41.8%±12.4 44.9%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 150 shots

OptionUsedWin %Tour
FH down the line 25% 47.3%±10.8 52.2%
FH through the middle 23% 37.3%±10.8 45.8%
FH crosscourt 22% 44.4%±11.2 52.7%
BH through the middle 16% 48.3%±12.4 46.2%
BH crosscourt 9% 50.5%±14.1 50.9%

Long rally, 9+: drive to your backhand side

position worth 44% to the average player · 119 shots

OptionUsedWin %Tour
BH crosscourt 48% 50.1%±9.4 47.9%
BH through the middle 17% 46.4%±13.0 42.7%
BH slice crosscourt 11% 41.6%±14.1 38.7%
BH slice through the middle 11% 38.5%±13.9 33.4%
BH down the line 8% 47.8%±15.0 46.7%

Serve under pressure

Pressure predictability index +2 How much less varied Nicole Gibbs's first-serve direction gets on break points. Positive means easier to read. Based on 80 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 40% 48% 68% / 66%
Body 24% 19% 63% / 57%
T 36% 33% 63% / 68%

245 normal · 21 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 30% 31% 63% / 66%
Body 34% 29% 46% / 56%
T 35% 41% 64% / 64%

186 normal · 59 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
Wide41% 58.6%±6.9 n=108 56% ▲
Body24% 56.2%±8.5 n=63 15% ▼
T36% 48.8%±7.4 n=95 29% ▼

Consistent with an optimal mix (p = 0.16).
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide30% 52.2%±8.1 n=74 35% ▲
Body33% 39.3%±7.6 n=81 18% ▼
T37% 51.8%±7.5 n=90 47% ▲

Off equilibrium (p = 0.025): serve wide more. Gap 4.4 points per 100 first serves.
Optimal mix: +1.1 per 100 first serves.

Exploitability 0.83 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: +6.8±10.0 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. (135 repeats, 362 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 10 40% −3.5±12.8
1stAd courtT 54 33% −2.6±8.4
1stAd courtWide 51 35% +0.5±8.7
1stDeuce courtBody 20 38% −5.0±11.3
1stDeuce courtT 55 21% −11.4±7.2
1stDeuce courtWide 52 37% +2.8±8.8
2ndAd courtBody 46 55% −0.4±9.4
2ndAd courtT 10 46% −8.8±13.0
2ndAd courtWide 32 48% −5.1±10.4
2ndDeuce courtBody 45 56% +2.0±9.4
2ndDeuce courtT 42 53% −3.5±9.7
2ndDeuce courtWide 11 49% −4.7±12.8

Signature patterns

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

Serve → +1

  1. Not enough data

Return

  1. Not enough data

Rally, consecutive own shots

  1. BH crosscourt → BH crosscourt used 6.2% · won 53% · +10.4±11.0 vs own baseline
  2. BH down the line → FH crosscourt used 5.3% · won 48% · +4.9±11.5 vs own baseline
  3. FH down the line → BH crosscourt used 4.8% · won 46% · +2.8±11.7 vs own baseline
  4. FH crosscourt → FH through the middle used 6.0% · won 42% · −1.3±11.0 vs own baseline
  5. FH through the middle → FH crosscourt used 5.8% · won 39% · −4.3±11.0 vs own baseline

Discovered sequences

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

  1. BH crosscourt → BH crosscourt → BH crosscourt used 2.4% · won 46% · +2.6±10.9 vs own baseline · −0.2 vs tour on the same sequence Disrupted by Carina Witthoeft (2/10), Heather Watson (9/14)
  2. BH crosscourt → BH crosscourt → BH through the middle used 1.4% · won 46% · +2.6±12.5 vs own baseline · +6.1 vs tour on the same sequence
  3. BH down the line → FH crosscourt → FH crosscourt used 1.8% · won 46% · +2.0±11.8 vs own baseline · −0.1 vs tour on the same sequence Disrupted by Heather Watson (5/12)
  4. BH through the middle → BH crosscourt → BH through the middle used 1.1% · won 45% · +1.1±13.0 vs own baseline · +4.5 vs tour on the same sequence Disrupted by Carina Witthoeft (2/7)
  5. FH down the line → BH crosscourt → BH crosscourt used 1.4% · won 44% · +0.3±12.5 vs own baseline · −3.9 vs tour on the same sequence
  6. FH crosscourt → FH crosscourt → FH through the middle used 1.4% · won 44% · +0.3±12.5 vs own baseline · +1.2 vs tour on the same sequence Disrupted by Heather Watson (5/8)

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 backhand · rally+2.5159
FH to their forehand · rally+1.3227
FH to their backhand · rally−4.6128

Most exposed to

BH to their backhand · rally−2.0179
FH to their backhand · rally+0.9139
FH to their forehand · rally+2.2232

Active players who are best at the shot in the top weakness: Maja Chwalinska, Sara Sorribes Tormo, Yulia Putintseva, Elsa Jacquemot, Caroline Wozniacki

Charted matches