RallyIQ

WTA · Right-handed · 11 charted matches · 2021–2025

Jule Niemeier

Archetype: Runs around the backhand · Forehand-dominant

Against an average opponent

Serve points won 55.6% ±3.5 raw 52.1% · tour 56.3% · 737 points
Return points won 43.5% ±3.5 raw 40.7% · tour 43.7% · 708 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 −0.06 ±0.09 better than 41% of WTA · raw −0.06
Shot selection +0.21 ±0.30 better than 68% of WTA · raw +0.21
Execution −2.75 ±0.94 better than 2% of WTA · raw −2.72
Tactical adaptability +0.06 first serves toward what's working, set to set · 11 matches
Adaptation speed −0.04 same, every two to three service games · per 100 first serves
Points left on the table 2.67 per 100 shots vs best direction · lower than 37% 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 3,559 shots.

Shot expected value

The share of points Jule Niemeier 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 · 192 shots

OptionUsedWin %Tour
FH down the line 30% 46.7%±9.3 52.2%
FH crosscourt 27% 54.9%±9.6 52.7%
FH through the middle 19% 35.4%±10.4 45.8%
BH through the middle 9% 45.4%±13.3 46.2%
BH crosscourt 8% 53.3%±13.7 50.9%

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

position worth 45% to the average player · 188 shots

OptionUsedWin %Tour
BH crosscourt 33% 32.3%±8.5 47.6%
BH through the middle 27% 36.7%±9.5 43.3%
BH slice through the middle 10% 33.0%±12.4 34.4%
FH inside-out 9% 44.6%±13.4 52.5%
BH down the line 9% 42.6%±13.6 46.8%
BH slice down the line 6% 29.2%±13.2 31.7%
BH slice crosscourt 6% 50.3%±14.5 40.4%

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

position worth 43% to the average player · 149 shots

OptionUsedWin %Tour
FH crosscourt 41% 44.9%±9.1 46.7%
FH through the middle 26% 33.2%±10.2 41.3%
FH down the line 24% 44.6%±10.9 44.9%

Return +1: drive to your backhand side

position worth 44% to the average player · 117 shots

OptionUsedWin %Tour
BH crosscourt 38% 48.6%±10.2 47.8%
BH through the middle 22% 40.4%±11.9 43.0%
BH slice crosscourt 13% 36.9%±13.4 39.6%
BH slice through the middle 9% 32.1%±14.0 33.2%

Serve under pressure

Pressure predictability index −1 How much less varied Jule Niemeier's first-serve direction gets on break points. Positive means easier to read. Based on 90 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 38% 26% ▼ 66% / 66%
Body 19% 26% 63% / 57%
T 43% 48% 65% / 68%

361 normal · 23 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 36% 24% ▼ 63% / 66%
Body 22% 33% ▲ 56% / 56%
T 42% 43% 62% / 64%

286 normal · 67 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% 55.3%±6.2 n=143 52% ▲
Body19% 58.3%±8.0 n=74 4% ▼
T43% 50.4%±5.9 n=167 44%

Consistent with an optimal mix (p = 0.24).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide33% 51.1%±6.8 n=118 49% ▲
Body24% 52.6%±7.7 n=85 9% ▼
T42% 47.8%±6.1 n=150 42%

Consistent with an optimal mix (p = 0.61).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.37 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: +2.0±7.8 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. (206 repeats, 509 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 66 38% −6.2±8.1
1stAd courtT 56 31% −4.5±8.2
1stAd courtWide 95 39% +4.2±7.2
1stDeuce courtBody 72 41% −1.6±8.0
1stDeuce courtT 70 31% −1.5±7.6
1stDeuce courtWide 89 28% −6.1±6.8
2ndAd courtBody 44 59% +3.8±9.4
2ndAd courtT 25 54% −1.4±11.1
2ndAd courtWide 54 47% −7.0±9.0
2ndDeuce courtBody 71 56% +1.3±8.1
2ndDeuce courtT 48 51% −5.0±9.3
2ndDeuce courtWide 18 59% +4.8±11.7

Signature patterns

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

Serve → +1

  1. Wide serve (deuce court) → FH down the line used 4.6% · won 54% · −6.2±11.7 vs own baseline
  2. Body serve (ad court) → FH down the line used 5.1% · won 52% · −8.3±11.5 vs own baseline
  3. Body serve (deuce court) → FH through the middle used 4.6% · won 48% · −12.2±11.7 vs own baseline
  4. T serve (deuce court) → FH down the line used 4.6% · won 42% · −18.2±11.6 vs own baseline

Return

  1. vs T serve (deuce court) → BH through the middle, deep used 9.7% · won 47% · +0.5±11.4 vs own baseline
  2. vs wide serve (deuce court) → FH through the middle, mid used 9.7% · won 43% · −3.3±11.3 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 8.4% · won 42% · +2.9±10.5 vs own baseline
  2. BH through the middle → FH crosscourt used 6.9% · won 40% · +1.2±11.0 vs own baseline
  3. BH through the middle → BH crosscourt used 6.9% · won 38% · −0.7±11.0 vs own baseline
  4. FH crosscourt → FH through the middle used 7.5% · won 37% · −2.0±10.7 vs own baseline
  5. FH crosscourt → FH crosscourt used 6.4% · won 34% · −5.0±10.9 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH crosscourt → FH through the middle used 1.2% · won 39% · −1.6±12.1 vs own baseline · −6.4 vs tour on the same sequence
  2. BH crosscourt → BH crosscourt → BH crosscourt used 1.1% · won 36% · −4.5±12.2 vs own baseline · −19.2 vs tour on the same sequence Disrupted by Daria Kasatkina (0/7)
  3. FH through the middle → FH crosscourt → FH crosscourt used 0.9% · won 35% · −5.2±12.5 vs own baseline · −20.0 vs tour on the same sequence Disrupted by Iga Swiatek (4/6)
  4. FH crosscourt → FH crosscourt → FH crosscourt used 1.0% · won 35% · −6.1±12.3 vs own baseline · −23.3 vs tour on the same sequence Disrupted by Arianne Hartono (1/6)

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

Wide 1st serve · deuce court−0.9143
T 1st serve · ad court−1.0150
FH to the middle · return−1.1150
FH to their forehand · rally−1.4219
T 1st serve · deuce court−1.5167

Most exposed to

FH to their forehand · rally−2.1190
BH to the middle · return−1.6159
Wide 1st serve · ad court−1.2137
Wide 1st serve · deuce court−0.9140
T 1st serve · deuce court+0.9126

Active players who are best at the shot in the top weakness: Linda Fruhvirtova, Maja Chwalinska, Sara Sorribes Tormo, Linda Klimovicova, Nadia Podoroska

Tactical fingerprint

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

Unforced errors / shot15.7%
Forehand share61%
Run-around forehands19%
Point-ending shots29.8%
Drop shots / shot2.5%
T serves · deuce43%
Backhand slice25%
T serves · ad42%
Serve & volley3%
Points at net8%
Through the middle30%
FH down the line30%
Deep returns33%
Chipped returns8%
Wide serves · deuce37%
Wide serves · ad33%
Avg rally length3.7
BH down the line14%
1st serve in57%

Plays most like

  1. Lulu Sun 2022–2025 plan v
  2. Xin Yu Wang 2019–2026 plan v
  3. Nadia Podoroska 2020–2026 plan v
  4. Caroline Garcia 2013–2025 plan v
  5. Maria Sakkari 2015–2026 plan v
  6. Liudmila Samsonova 2021–2026 plan v
  7. Sabine Lisicki 2009–2022 plan v
  8. Coco Vandeweghe 2014–2018 plan v

Closest from another era

  1. Jelena Dokic 2000–2009
  2. Justine Henin 1999–2010
  3. Lindsay Davenport 1995–2006

Charted matches