RallyIQ

Game plan

Sabine Lisicki v Julia Goerges

Every number combines what Sabine Lisicki does well with what Julia Goerges allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Sabine Lisicki wins, best of 3 27%90%: 9%–54% · best of 5: 22%
Serve points won 57.5% / 62.2% Sabine / Julia · tour 56.3%
Strengths only, no similarity priors 28%serve 57.6% / 62.0%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Sabine Lisicki's record against Julia Goerges's tactical lookalikes and in their charted head-to-heads (lookalikes: −1.6 on serve, −2.8 on return vs expectation (210 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

CareerSabineJulia
Direction choice+0.02 ±0.12
better than 56%
+0.23 ±0.09
better than 89%
Shot selection+0.35 ±0.13
better than 83%
+0.79 ±0.14
better than 99%
Execution−1.31 ±0.65
better than 13%
−0.84 ±0.54
better than 22%
Points left on the table2.61 ±0.18
lower than 50%
2.33 ±0.13
lower than 84%

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.

Sabine Lisicki serving

Deuce court

1st serveNowSabine winsv JuliaMatchupOptimal
Wide46%69%66%69.2%±6.846%
Body18%60%59%61.8%±9.03% ▼
T36%75%71%78.0%±6.351% ▲

Optimal v Julia Goerges: +1.4±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +7.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSabine winsv JuliaMatchupOptimal
Wide40%73%70%76.1%±6.355% ▲
Body18%50%53%47.6%±9.73% ▼
T42%65%57%57.4%±8.242%

Optimal v Julia Goerges: +1.2±1.1 per 100 first serves (faults included) over the current mix. Serving wide every time would read +13.1 per 100 first serves in before the returner adjusts.

Julia Goerges serving

Deuce court

1st serveNowJulia winsv SabineMatchupOptimal
Wide47%70%69%72.2%±6.262% ▲
Body16%56%62%61.3%±9.21% ▼
T37%72%65%69.4%±7.637%

Optimal v Sabine Lisicki: +0.9±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJulia winsv SabineMatchupOptimal
Wide38%72%67%72.8%±7.142% ▲
Body14%54%59%56.6%±10.00% ▼
T48%71%63%69.8%±7.058% ▲

Optimal v Sabine Lisicki: +0.9±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.7 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.

Sabine Lisicki returning

1st serve to the forehand

ReturnNowTourOwnv JuliaValue
FH through the middle44%+4.2−0.6−0.8+2.7±2.7
FH crosscourt24%+5.3−0.6+1.9+6.5±4.3
FH down the line21%+1.5+4.0+2.5+8.0±4.7
FH slice through the middle6%−6.7+1.6−0.6−5.7±2.5
FH slice crosscourt3%−6.6−0.1+0.8−5.9±2.2

Lean FH down the line: +4.3±4.0 per 100 returns v the current mix (340 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JuliaValue
BH through the middle46%+6.0+0.9−1.9+5.1±2.6
BH crosscourt25%+7.7−0.8+1.5+8.4±3.6
BH down the line22%+2.2+2.4−0.4+4.1±4.7
BH slice through the middle4%−6.2−0.1−1.4−7.8±2.3
BH slice crosscourt3%−4.2−0.5−0.3−4.9±2.4

Lean BH crosscourt: +3.5±3.1 per 100 returns v the current mix (296 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JuliaValue
FH through the middle42%−3.2−0.9+0.5−3.5±3.0
FH down the line31%−0.6+2.0+0.6+2.1±5.0
FH crosscourt27%+0.5+2.3+1.9+4.8±4.2

Lean FH crosscourt: +4.3±3.7 per 100 returns v the current mix (64 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JuliaValue
BH through the middle44%−2.6−1.5−3.4−7.5±2.7
BH crosscourt30%+1.5−3.0−1.0−2.5±3.4
BH down the line21%−0.5−3.3−1.9−5.8±5.1
FH through the middle4%−2.7+0.8+0.5−1.4±2.2

Lean BH crosscourt: +2.9±2.9 per 100 returns v the current mix (135 returns charted)

Julia Goerges returning

1st serve to the forehand

ReturnNowTourOwnv SabineValue
FH through the middle33%+4.2−2.0−0.1+2.0±2.9
FH down the line28%+1.5+0.3+1.2+3.0±4.6
FH crosscourt18%+5.3+2.3+0.4+8.0±4.3
FH slice through the middle15%−6.7−0.9+1.9−5.7±2.6
FH slice crosscourt3%−6.6+0.7+0.8−5.1±2.2

Lean FH crosscourt: +6.2±3.9 per 100 returns v the current mix (265 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SabineValue
BH through the middle43%+6.0−1.7−2.6+1.8±2.6
BH crosscourt19%+7.7−3.5+0.3+4.5±3.5
BH down the line18%+2.2−1.8−2.4−2.0±4.7
BH slice through the middle11%−6.2−1.9+0.6−7.5±2.4
BH slice crosscourt7%−4.2−4.0−0.4−8.5±2.8

Lean BH crosscourt: +5.1±3.2 per 100 returns v the current mix (371 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SabineValue
FH crosscourt40%+0.5−1.6−0.7−1.7±4.3
FH through the middle32%−3.2−1.3+0.8−3.7±2.9
FH down the line28%−0.6−1.1−0.7−2.4±4.9

Lean FH crosscourt: +0.8±3.1 per 100 returns v the current mix (57 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv SabineValue
BH through the middle33%−2.6−3.0+0.5−5.0±2.7
BH crosscourt25%+1.5+0.8+1.0+3.3±3.5
BH down the line22%−0.5−3.7+1.0−3.2±5.3
FH inside-out8%+1.4−2.8−0.7−2.2±4.0
FH inside-in6%+0.7+1.2−0.7+1.3±4.2

Lean BH crosscourt: +5.1±3.1 per 100 returns v the current mix (183 returns charted)

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.

Sabine Lisicki

Favour

ShotEdgeOwnTheirs
FH to their backhand · return+5.5±3.9+3.5+2.0
FH to their forehand · return+2.8±4.0+0.3+2.4
BH to their backhand · return +1+2.2±3.4+1.6+0.6
FH to their backhand · rally+1.3±3.4+2.5−1.3
BH to their backhand · rally+1.2±2.7+0.9+0.3
FH to the middle · rally+0.9±2.4+0.5+0.4

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−9.1±4.3−5.3−3.8
BH to their forehand · serve +1−6.4±4.8−1.5−5.0
FH to the middle · serve +1−5.1±2.7−3.7−1.4
BH to their backhand · serve +1−4.2±3.3−3.6−0.6
BH to the middle · return−4.0±2.0−0.7−3.3

Julia Goerges

Favour

ShotEdgeOwnTheirs
BH to their backhand · return +1+2.8±3.5+2.5+0.3
BH to the middle · serve +1+2.1±2.4+0.7+1.4
BH to their backhand · serve +1+1.0±3.3+1.1−0.2
BH to their backhand · return+1.0±3.0+0.3+0.7
FH to their forehand · serve +1+0.7±3.5+1.2−0.5
FH to their backhand · rally+0.6±3.1+0.4+0.2

Avoid

ShotEdgeOwnTheirs
BH to their forehand · return−4.6±4.2−3.6−1.0
BH to the middle · return−4.4±2.1−2.4−2.0
BH to their forehand · return +1−3.7±4.7−1.6−2.1
FH to the middle · return−3.3±2.4−3.3+0.1
FH to their backhand · return +1−3.0±4.1−1.8−1.2

Against Julia Goerges-like opponents

Sabine Lisicki vMatchesServe pts wonReturn pts won
All charted opponents–57.7%42.5%
Players most similar to Julia Goerges1 58.1%41.9%

Similar by tactical fingerprint: Madison Keys, Amanda Anisimova, Talia Gibson, Dayana Yastremska, Viktoria Hruncakova, Anastasia Pavlyuchenkova, Alycia Parks, Ana Ivanovic, Daniela Hantuchova. When two players have rarely met, their records against these lookalikes fill the gap.