RallyIQ

Game plan

Laura Siegemund v Su Wei Hsieh

Every number combines what Laura Siegemund does well with what Su Wei Hsieh allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Laura Siegemund wins, best of 3 47%90%: 16%–80% · best of 5: 47%
Serve points won 58.2% / 58.7% Laura / Su · tour 58.1%
Strengths only, no similarity priors 53%serve 58.8% / 58.2%

Each player's serve and return strength is fitted against every opponent they were charted against, so a record built on weak opponents counts for less. At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers. The result is then nudged by Laura Siegemund's record against Su Wei Hsieh's tactical lookalikes and in their charted head-to-heads (lookalikes: −3.5 on serve, −2.9 on return vs expectation (622 points)). A game-by-game Markov chain turns point odds into match odds; the 90% range covers the uncertainty in the two strengths, not the nudges. Charted matches lean toward big events, so treat this as a scouting estimate, not a betting line.

Head to head, per 100 shots

CareerLauraSu
Direction choice−0.01 ±0.09
better than 52%
+0.33 ±0.09
better than 96%
Shot selection−0.15 ±0.31
better than 32%
−0.59 ±0.14
better than 9%
Execution−1.01 ±0.57
better than 17%
+0.24 ±0.61
better than 70%
Points left on the table2.66 ±0.08
lower than 41%
2.26 ±0.15
lower than 89%

Each player's career against an average tour player in the same position, adjusted for opponent strength, with a 90% margin (shots clustered by match). Points left on the table is the gap to the best-value direction for the same stroke, so lower is better. Percentiles are within each player's own tour. A side is highlighted only when the gap is larger than the margin on the difference.

Structural compatibility

Expected edge per 100 rally shots from style alone: Laura Siegemund −0.42, Su Wei Hsieh −0.03. Each player's shot mix weighted by their own skill with each shot and by how much the other gives up against it. This is why some rankings gaps don't hold in a given matchup.

Serve plan

The share of points the server wins when a first serve lands in that direction (hover a rate for its 90% interval; ± is the 90% margin). "Matchup" combines the server's rate with how this returner handles that serve. "Optimal" is the mix that wins most against this returner once they start reading a habit, at the response measured across the tour, and only within the range servers' habits actually vary. The gain over the current mix is how exploitable that mix is.

Laura Siegemund serving

Deuce court

1st serveNowLaura winsv SuMatchupOptimal
Wide38%61%66%60.9%±7.038%
Body38%57%49%48.7%±8.423% ▼
T24%65%72%69.2%±7.639% ▲

Optimal v Su Wei Hsieh: +1.2±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +11.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLaura winsv SuMatchupOptimal
Wide30%57%66%57.1%±7.941% ▲
Body34%53%59%56.2%±8.719% ▼
T36%59%68%62.8%±7.440% ▲

Optimal v Su Wei Hsieh: +0.5±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.0 per 100 first serves in before the returner adjusts.

Su Wei Hsieh serving

Deuce court

1st serveNowSu winsv LauraMatchupOptimal
Wide48%66%66%66.7%±6.163% ▲
Body20%54%61%58.1%±9.05% ▼
T32%60%71%63.6%±8.332%

Optimal v Laura Siegemund: +1.3±1.0 per 100 first serves (faults included) over the current mix. Serving wide every time would read +2.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSu winsv LauraMatchupOptimal
Wide45%66%67%67.6%±6.955% ▲
Body20%60%53%56.0%±9.35% ▼
T35%61%64%60.7%±7.940% ▲

Optimal v Laura Siegemund: +0.8±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.8 per 100 first serves in before the returner adjusts.

Return plan

Value of each return, in points per 100 returns against an average return of the same serve (direction, court, surface): the tour's result with that return, the returner's own edge with it, and what this server gives up when it comes back to that side. Returns with no charted direction are left out, so values compare with each other rather than with zero. Depth isn't a choice here: missed returns have no depth. Serve quality isn't charted, so a block through the middle partly reflects the serve that forced it.

Laura Siegemund returning

1st serve to the forehand

ReturnNowTourOwnv SuValue
FH through the middle37%+4.2−2.3+0.7+2.6±2.5
FH crosscourt20%+5.3−4.3+1.3+2.3±4.1
FH down the line17%+1.5+1.4+2.5+5.4±4.6
FH slice through the middle13%−6.7−0.8+0.5−7.0±2.3
FH slice crosscourt9%−6.6+0.7+0.6−5.2±2.6

Lean FH down the line: +4.8±4.0 per 100 returns v the current mix (385 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SuValue
BH through the middle45%+6.0+1.0+1.8+8.8±2.4
BH crosscourt23%+7.7−2.1±0.0+5.6±3.4
BH slice through the middle12%−6.2−2.8−2.5−11.6±2.5
BH down the line9%+2.2−2.0+3.9+4.0±4.6
BH slice crosscourt5%−4.2−0.2−0.8−5.2±2.7

Lean BH through the middle: +5.4±1.6 per 100 returns v the current mix (311 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SuValue
FH through the middle34%−3.2−1.4−1.1−5.6±3.0
FH crosscourt26%+0.5−1.0+1.9+1.5±4.3
FH slice crosscourt15%−14.9+0.3±0.0−14.6±1.6
FH down the line14%−0.6−0.2+1.6+0.9±4.6
FH slice through the middle10%−15.2−0.9±0.0−16.1±1.3

Lean FH crosscourt: +6.8±3.4 per 100 returns v the current mix (87 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv SuValue
BH through the middle40%−2.6−0.5+0.2−2.9±2.7
BH crosscourt36%+1.5−1.2+1.8+2.1±3.5
BH down the line20%−0.5+3.1+1.3+3.8±5.2
FH through the middle4%−2.7+0.4−1.1−3.4±2.1

Lean BH down the line: +3.6±4.4 per 100 returns v the current mix (138 returns charted, inside the 90% margin)

Su Wei Hsieh returning

1st serve to the forehand

ReturnNowTourOwnv LauraValue
FH slice through the middle27%−6.7+0.5+0.5−5.6±2.4
FH crosscourt23%+5.3+4.5+0.6+10.4±3.9
FH through the middle22%+4.2+0.1+1.0+5.3±2.7
FH slice crosscourt18%−6.6−1.1+0.7−7.1±2.3
FH down the line5%+1.5+2.1+1.1+4.7±4.3

Lean FH crosscourt: +10.0±3.2 per 100 returns v the current mix (386 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LauraValue
BH through the middle47%+6.0+2.9−0.1+8.9±2.3
BH crosscourt35%+7.7+0.9−1.0+7.6±3.3
BH down the line9%+2.2+2.4−3.5+1.1±4.6
BH slice down the line3%−12.5−1.5−0.7−14.7±2.5
BH slice through the middle3%−6.2−0.9−0.4−7.5±1.9

Lean BH through the middle: +2.9±1.7 per 100 returns v the current mix (338 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LauraValue
FH crosscourt52%+0.5+1.5−1.7+0.3±4.4
FH through the middle23%−3.2+0.6−1.7−4.3±2.9
FH down the line15%−0.6+4.9−3.1+1.3±4.8
FH slice through the middle10%−15.2±0.0±0.0−15.2±1.3

Lean FH crosscourt: +2.5±2.3 per 100 returns v the current mix (88 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv LauraValue
BH crosscourt47%+1.5+0.4−1.5+0.4±3.5
BH through the middle30%−2.6+0.7−1.1−3.0±2.8
BH down the line23%−0.5+0.8+2.0+2.3±5.2

Lean BH down the line: +2.5±4.5 per 100 returns v the current mix (207 returns charted, inside the 90% margin)

Rally plan

Edge, in points per 100 shots: the hitter's skill with the shot (own) plus how much the receiver usually gives up against it (theirs), both measured against the tour average on grass. Each player's grass record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Laura Siegemund

Favour

ShotEdgeOwnTheirs
BH to their forehand · serve +1+6.3±5.3−1.2+7.5
FH to the middle · serve +1+4.0±2.4+2.1+1.9
BH to the middle · return+3.5±2.9+1.1+2.5
BH to their forehand · rally+2.6±4.9+3.1−0.5
FH to the middle · return +1+2.4±3.3−0.5+2.9
FH to their backhand · return+2.1±5.0+1.2+0.9

Avoid

ShotEdgeOwnTheirs
BH to their forehand · return +1−4.8±4.8−0.8−4.0
FH to their forehand · rally−4.4±4.0−3.8−0.6
BH to their backhand · rally−4.3±3.7−0.4−3.8
FH to the middle · return−4.2±3.2−2.4−1.8
BH to the middle · rally−2.9±2.6−0.5−2.4

Su Wei Hsieh

Favour

ShotEdgeOwnTheirs
FH to their forehand · return+3.8±3.6+3.5+0.3
BH to the middle · return+3.7±2.9+2.9+0.8
FH to their backhand · rally+2.6±4.3+3.4−0.8
BH to their forehand · serve +1+2.5±5.6+5.8−3.3
FH to the middle · return+1.8±2.4+1.0+0.8
BH to their backhand · return +1+1.7±3.1−1.4+3.2

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−6.7±4.8−1.8−4.9
FH to their forehand · rally−3.5±3.9−1.4−2.1
FH to their backhand · return +1−3.0±5.0−1.2−1.8
BH to their forehand · return−3.0±5.0−1.6−1.4
BH to their backhand · serve +1−2.9±4.1±0.0−2.9

Against Su Wei Hsieh-like opponents

Laura Siegemund vMatchesServe pts wonReturn pts won
All charted opponents–52.8%41.7%
Players most similar to Su Wei Hsieh4 51.2%39.9%

Similar by tactical fingerprint: Anastasia Potapova, Anna Kalinskaya, Linda Klimovicova, Antonia Ruzic, Sorana Cirstea, Sofia Kenin, Anastasija Sevastova, Anhelina Kalinina, R, Elena Vesnina. When two players have rarely met, their records against these lookalikes fill the gap.