RallyIQ

Game plan

Laura Siegemund v Sabine Lisicki

Every number combines what Laura Siegemund does well with what Sabine Lisicki 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 38%90%: 15%–67% · best of 5: 35%
Serve points won 55.8% / 58.0% Laura / Sabine · tour 56.4%
Strengths only, no similarity priors 39%serve 56.0% / 58.1%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Sabine Lisicki's tactical lookalikes and in their charted head-to-heads (lookalikes: −8.1 on serve, +1.5 on return vs expectation (117 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

CareerLauraSabine
Direction choice−0.01 ±0.09
better than 52%
+0.02 ±0.12
better than 56%
Shot selection−0.15 ±0.31
better than 32%
+0.35 ±0.13
better than 83%
Execution−1.01 ±0.57
better than 17%
−1.31 ±0.65
better than 13%
Points left on the table2.66 ±0.08
lower than 41%
2.61 ±0.18
lower than 50%

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.

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 SabineMatchupOptimal
Wide38%61%69%63.8%±7.053% ▲
Body38%57%62%62.1%±7.423% ▼
T24%65%65%61.2%±8.624%

Optimal v Sabine Lisicki: +0.3±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLaura winsv SabineMatchupOptimal
Wide30%57%67%58.3%±8.230%
Body34%53%59%56.1%±7.919% ▼
T36%59%63%57.7%±7.951% ▲

Optimal v Sabine Lisicki: +0.3±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +0.9 per 100 first serves in before the returner adjusts.

Sabine Lisicki serving

Deuce court

1st serveNowSabine winsv LauraMatchupOptimal
Wide46%69%66%69.5%±6.261% ▲
Body18%60%61%63.9%±9.13% ▼
T36%75%71%77.9%±6.836%

Optimal v Laura Siegemund: +1.1±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +6.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSabine winsv LauraMatchupOptimal
Wide40%73%67%73.7%±6.755% ▲
Body18%50%53%46.7%±9.93% ▼
T42%65%64%64.2%±7.642%

Optimal v Laura Siegemund: +1.4±1.1 per 100 first serves (faults included) over the current mix. Serving wide every time would read +9.0 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 SabineValue
FH through the middle37%+4.2−2.3−0.1+1.7±2.7
FH crosscourt20%+5.3−4.3+0.4+1.4±4.3
FH down the line17%+1.5+1.4+1.2+4.1±4.6
FH slice through the middle13%−6.7−0.8+1.9−5.6±2.6
FH slice crosscourt9%−6.6+0.7+0.8−5.0±2.6

Lean FH down the line: +4.1±4.1 per 100 returns v the current mix (385 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv SabineValue
BH through the middle45%+6.0+1.0−2.6+4.4±2.6
BH crosscourt23%+7.7−2.1+0.3+6.0±3.5
BH slice through the middle12%−6.2−2.8+0.6−8.4±2.4
BH down the line9%+2.2−2.0−2.4−2.2±4.6
BH slice crosscourt5%−4.2−0.2−0.4−4.7±2.7

Lean BH crosscourt: +4.7±3.0 per 100 returns v the current mix (311 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SabineValue
FH through the middle34%−3.2−1.4+0.8−3.8±3.0
FH crosscourt26%+0.5−1.0−0.7−1.1±4.3
FH slice crosscourt15%−14.9+0.3±0.0−14.6±1.6
FH down the line14%−0.6−0.2−0.7−1.4±4.7
FH slice through the middle10%−15.2−0.9±0.0−16.0±1.9

Lean FH crosscourt: +4.5±3.4 per 100 returns v the current mix (87 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv SabineValue
BH through the middle40%−2.6−0.5+0.5−2.6±2.7
BH crosscourt36%+1.5−1.2+1.0+1.3±3.5
BH down the line20%−0.5+3.1+1.0+3.6±5.2
FH through the middle4%−2.7+0.4+0.8−1.5±2.1

Lean BH down the line: +3.5±4.4 per 100 returns v the current mix (138 returns charted, inside the 90% margin)

Sabine Lisicki returning

1st serve to the forehand

ReturnNowTourOwnv LauraValue
FH through the middle44%+4.2−0.6+1.0+4.5±2.5
FH crosscourt24%+5.3−0.6+0.6+5.2±3.9
FH down the line21%+1.5+4.0+1.1+6.6±4.5
FH slice through the middle6%−6.7+1.6+0.5−4.6±2.3
FH slice crosscourt3%−6.6−0.1+0.7−6.0±1.8

Lean FH down the line: +2.6±3.8 per 100 returns v the current mix (340 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv LauraValue
BH through the middle46%+6.0+0.9−0.1+6.9±2.4
BH crosscourt25%+7.7−0.8−1.0+6.0±3.4
BH down the line22%+2.2+2.4−3.5+1.1±4.6
BH slice through the middle4%−6.2−0.1−0.4−6.7±2.0
BH slice crosscourt3%−4.2−0.5−0.9−5.6±1.9

Lean BH through the middle: +2.5±1.9 per 100 returns v the current mix (296 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LauraValue
FH through the middle42%−3.2−0.9−1.7−5.7±3.0
FH down the line31%−0.6+2.0−3.1−1.6±5.0
FH crosscourt27%+0.5+2.3−1.7+1.1±4.2

Lean FH crosscourt: +3.7±3.7 per 100 returns v the current mix (64 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv LauraValue
BH through the middle44%−2.6−1.5−1.1−5.2±2.8
BH crosscourt30%+1.5−3.0−1.5−3.0±3.6
BH down the line21%−0.5−3.3+2.0−1.9±5.2
FH through the middle4%−2.7+0.8−1.7−3.6±2.1

Lean BH down the line: +1.9±4.4 per 100 returns v the current mix (135 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 hard. Each player's hard record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Laura Siegemund

Favour

ShotEdgeOwnTheirs
FH to their backhand · rally+5.2±4.6+1.7+3.5
BH to their forehand · rally+3.7±6.1+2.3+1.5
FH to the middle · serve +1+3.6±3.7+3.2+0.3
FH to their backhand · return+3.2±6.0+2.4+0.8
BH to their backhand · rally+2.5±3.9+1.5+1.0
BH to the middle · serve +1+1.8±3.4−0.9+2.7

Avoid

ShotEdgeOwnTheirs
FH to their forehand · return +1−6.7±5.5−5.6−1.1
FH to their forehand · return−6.1±6.0−7.2+1.1
FH to their forehand · rally−4.3±4.2−3.0−1.3
BH to their backhand · return−4.2±4.7−2.8−1.4
FH to their backhand · serve +1−4.1±5.4−2.0−2.1

Sabine Lisicki

Favour

ShotEdgeOwnTheirs
BH to their backhand · return +1+5.9±4.9−0.3+6.1
FH to their backhand · return+5.8±5.7+3.7+2.1
FH to their forehand · return +1+1.9±4.9−1.1+3.0
FH to the middle · rally+0.9±3.3+1.0−0.1
BH to the middle · return +1+0.9±3.5−1.8+2.6
FH to the middle · return+0.8±3.0−0.1+1.0

Avoid

ShotEdgeOwnTheirs
BH to their backhand · serve +1−9.6±5.1−4.6−4.9
FH to the middle · serve +1−5.5±3.8−5.8+0.3
BH to the middle · serve +1−5.3±3.6−1.7−3.6
FH to their backhand · return +1−4.9±5.9−1.8−3.1
FH to their backhand · serve +1−4.8±5.4+3.1−7.9

Against Sabine Lisicki-like opponents

Laura Siegemund vMatchesServe pts wonReturn pts won
All charted opponents–52.8%41.7%
Players most similar to Sabine Lisicki1 45.5%40.3%

Similar by tactical fingerprint: Madison Keys, Linda Noskova, Aryna Sabalenka, Clara Tauson, Viktoria Hruncakova, Anastasia Pavlyuchenkova, Aliaksandra Sasnovich, Veronika Kudermetova, Kristina Mladenovic, Daniela Hantuchova. When two players have rarely met, their records against these lookalikes fill the gap.