RallyIQ

WTA · Right-handed · 18 charted matches · 2024–2026

Talia Gibson

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 59.9% ±3.6 raw 60.7% · tour 56.3% · 1,266 points
Return points won 42.9% ±3.7 raw 39.4% · tour 43.7% · 1,273 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 +0.26 ±0.05 better than 91% of WTA · raw +0.27
Shot selection +0.01 ±0.09 better than 45% of WTA · raw +0.03
Execution −0.47 ±0.93 better than 35% of WTA · raw −0.35
Tactical adaptability −0.16 first serves toward what's working, set to set · 18 matches
Adaptation speed −0.07 same, every two to three service games · per 100 first serves
Points left on the table 2.25 per 100 shots vs best direction · lower than 89% 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 5,449 shots.

Shot expected value

The share of points Talia Gibson 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 · 312 shots

OptionUsedWin %Tour
BH crosscourt 23% 52.9%±8.5 50.9%
FH down the line 22% 53.8%±8.6 52.2%
FH crosscourt 19% 44.4%±9.1 52.7%
FH through the middle 13% 44.3%±10.6 45.8%
BH through the middle 12% 36.1%±10.6 46.2%
BH down the line 11% 50.0%±11.2 50.0%

Return +1: drive to your middle

position worth 50% to the average player · 222 shots

OptionUsedWin %Tour
FH crosscourt 23% 50.0%±9.8 52.3%
BH crosscourt 21% 45.7%±10.1 50.8%
FH down the line 19% 52.6%±10.4 53.0%
BH through the middle 17% 38.3%±10.5 46.2%
FH through the middle 11% 40.7%±12.0 46.5%
BH down the line 9% 52.8%±13.0 50.6%

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

position worth 43% to the average player · 215 shots

OptionUsedWin %Tour
FH crosscourt 47% 43.3%±7.4 46.7%
FH through the middle 26% 41.7%±9.4 41.3%
FH down the line 21% 40.9%±10.0 44.9%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 204 shots

OptionUsedWin %Tour
BH crosscourt 23% 44.7%±10.1 52.5%
FH crosscourt 21% 54.5%±10.4 54.0%
BH through the middle 17% 46.8%±11.2 46.3%
FH down the line 14% 49.3%±11.9 53.3%
FH through the middle 14% 48.1%±11.9 45.5%
BH down the line 13% 48.2%±12.1 51.0%

Serve under pressure

Pressure predictability index +5 How much less varied Talia Gibson's first-serve direction gets on break points. Positive means easier to read. Based on 131 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 43% 52% ▲ 68% / 66%
Body 10% 10% 55% / 57%
T 47% 39% ▼ 74% / 68%

630 normal · 31 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 50% 54% 74% / 66%
Body 6% 4% 54% / 56%
T 43% 42% 69% / 64%

503 normal · 100 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
Wide43% 63.6%±4.4 n=287 59% ▲
Body10% 52.5%±8.3 n=67 0% ▼
T46% 61.7%±4.4 n=307 41% ▼

Consistent with an optimal mix (p = 0.06).
Optimal mix: +0.8 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide51% 60.0%±4.4 n=307 50%
Body6% 55.7%±10.1 n=36 0% ▼
T43% 61.9%±4.7 n=260 50% ▲

Consistent with an optimal mix (p = 0.49).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.58 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: −3.7±5.3 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. (460 repeats, 768 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 52 45% +1.4±9.0
1stAd courtT 179 33% −2.7±5.3
1stAd courtWide 133 31% −3.0±6.0
1stDeuce courtBody 99 44% +1.4±7.2
1stDeuce courtT 122 24% −8.0±5.7
1stDeuce courtWide 196 28% −6.0±4.9
2ndAd courtBody 80 49% −6.4±7.8
2ndAd courtT 49 51% −3.8±9.3
2ndAd courtWide 118 51% −2.8±6.8
2ndDeuce courtBody 122 55% +1.0±6.6
2ndDeuce courtT 55 55% −1.0±8.9
2ndDeuce courtWide 67 55% +1.0±8.3

Signature patterns

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

Serve → +1

  1. T serve (ad court) → FH crosscourt used 3.5% · won 68% · +3.4±9.3 vs own baseline
  2. Wide serve (deuce court) → FH down the line used 4.0% · won 64% · −0.8±9.1 vs own baseline
  3. Wide serve (ad court) → FH crosscourt used 3.2% · won 62% · −2.7±9.9 vs own baseline
  4. Wide serve (deuce court) → BH crosscourt used 3.5% · won 61% · −4.0±9.7 vs own baseline
  5. T serve (deuce court) → BH crosscourt used 2.3% · won 59% · −5.9±10.9 vs own baseline

Return

  1. vs T serve (ad court) → FH through the middle, deep used 5.4% · won 58% · +14.2±10.0 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, short used 3.0% · won 58% · +14.6±11.6 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, mid used 3.5% · won 53% · +9.5±11.3 vs own baseline
  4. vs wide serve (deuce court) → FH crosscourt, mid used 3.8% · won 51% · +7.5±11.1 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, deep used 3.8% · won 47% · +3.9±11.1 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → BH crosscourt used 5.5% · won 59% · +9.6±10.1 vs own baseline
  2. BH crosscourt → FH crosscourt used 5.7% · won 55% · +5.6±10.1 vs own baseline
  3. BH crosscourt → BH down the line used 4.4% · won 54% · +4.6±10.9 vs own baseline
  4. FH crosscourt → FH down the line used 4.4% · won 54% · +4.6±10.9 vs own baseline
  5. FH through the middle → FH down the line used 3.4% · won 53% · +3.1±11.6 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Talia Gibson 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 1.0% · won 58% · +8.7±11.6 vs own baseline · +18.0 vs tour on the same sequence
  2. BH crosscourt → BH crosscourt → BH down the line used 0.7% · won 58% · +8.8±12.6 vs own baseline · +22.5 vs tour on the same sequence
  3. BH crosscourt → BH through the middle → FH crosscourt used 0.6% · won 58% · +9.2±12.9 vs own baseline · +19.5 vs tour on the same sequence
  4. BH crosscourt → BH through the middle → BH crosscourt used 0.9% · won 55% · +5.9±12.1 vs own baseline · +10.5 vs tour on the same sequence
  5. FH through the middle → BH crosscourt → BH crosscourt used 0.6% · won 53% · +4.2±13.0 vs own baseline · +13.4 vs tour on the same sequence
  6. FH crosscourt → FH through the middle → BH crosscourt used 0.9% · won 52% · +2.7±12.3 vs own baseline · +2.6 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

FH to the middle · return+1.4242
Wide 1st serve · deuce court+0.9287
T 1st serve · deuce court+0.7307
FH to their forehand · serve +1+0.5163
T 1st serve · ad court+0.2260

Most exposed to

T 1st serve · deuce court−3.4218
BH to their backhand · rally−2.5138
T 1st serve · ad court−2.4274
Wide 1st serve · deuce court−2.1292
FH to their forehand · rally−1.6209

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +3.36, Caroline Wozniacki +3.17, Daria Kasatkina +2.59, Angelique Kerber +2.49, Sara Errani +2.47

Favourable matchups

Sara Errani +1.27, Angelique Kerber +0.77, Elina Avanesyan +0.63, Marie Bouzkova +0.61, Katie Volynets +0.36

Active players who are best at the shot in the top weakness: Serena Williams, Madison Keys, Ashlyn Krueger, Karolina Pliskova, Victoria Mboko

Tactical fingerprint

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

Point-ending shots38.3%
Unforced errors / shot15.7%
T serves · deuce46%
Wide serves · ad51%
Deep returns37%
BH down the line25%
FH down the line33%
T serves · ad43%
Wide serves · deuce43%
Serve & volley0%
Chipped returns8%
Drop shots / shot1.2%
Backhand slice6%
Forehand share51%
1st serve in59%
Points at net4%
Run-around forehands1%
Through the middle24%
Avg rally length3.2

Plays most like

  1. Amanda Anisimova 2017–2026 plan v
  2. Petra Kvitova 2010–2025 plan v
  3. Daniela Hantuchova 2002–2015 plan v
  4. Naomi Osaka 2016–2026 plan v
  5. Danielle Collins 2018–2025 plan v
  6. Veronika Kudermetova 2018–2025 plan v
  7. Jelena Ostapenko 2014–2026 plan v
  8. Viktoria Hruncakova 2018–2026 plan v

Closest from another era

  1. Daniela Hantuchova 2002–2015
  2. Jelena Dokic 2000–2009
  3. Lindsay Davenport 1995–2006

Charted matches