RallyIQ

Game plan

Elina Svitolina v Johanna Larsson

Every number combines what Elina Svitolina does well with what Johanna Larsson allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Elina Svitolina wins, best of 3 96%90%: 82%–99% · best of 5: 98%
Serve points won 63.0% / 49.7% Elina / Johanna · tour 56.3%
Strengths only, no similarity priors 96%serve 62.8% / 49.7%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Elina Svitolina's record against Johanna Larsson's tactical lookalikes and in their charted head-to-heads (lookalikes: +1.5 on serve, −0.6 on return vs expectation (447 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

CareerElinaJohanna
Direction choice−0.09 ±0.04
better than 37%
−0.20 ±0.22
better than 16%
Shot selection−0.08 ±0.06
better than 36%
−0.07 ±0.27
better than 38%
Execution+0.90 ±0.18
better than 88%
−0.86 ±0.93
better than 22%

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.

Elina Svitolina serving

Deuce court

1st serveNowElina winsv JohannaMatchupOptimal
Wide39%69%72%74.1%±7.454% ▲
Body17%56%68%66.2%±11.32% ▼
T44%70%69%71.0%±8.044%

Optimal v Johanna Larsson: +0.9±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowElina winsv JohannaMatchupOptimal
Wide43%69%65%68.5%±8.145% ▲
Body15%59%58%61.2%±10.80% ▼
T41%64%70%68.9%±8.555% ▲

Optimal v Johanna Larsson: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.4 per 100 first serves in before the returner adjusts.

Johanna Larsson serving

Deuce court

1st serveNowJohanna winsv ElinaMatchupOptimal
Wide44%59%65%57.9%±8.559% ▲
Body17%54%57%53.4%±11.22% ▼
T39%60%68%60.6%±9.239%

Optimal v Elina Svitolina: +0.4±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJohanna winsv ElinaMatchupOptimal
Wide51%54%64%53.1%±8.352%
Body17%53%58%54.9%±11.51% ▼
T32%60%66%61.5%±10.047% ▲

Optimal v Elina Svitolina: +0.7±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.4 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.

Elina Svitolina returning

1st serve to the forehand

ReturnNowTourOwnv JohannaValue
FH through the middle48%+4.2+2.2+0.7+7.1±2.4
FH crosscourt18%+5.3+1.2−1.6+4.8±3.4
FH down the line14%+1.5−0.5+0.1+1.1±3.6
FH slice through the middle12%−6.7+1.1+0.9−4.8±1.8
FH slice crosscourt5%−6.6−1.1+1.2−6.5±2.1

Lean FH through the middle: +3.8±1.5 per 100 returns v the current mix (2739 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JohannaValue
BH through the middle48%+6.0+1.7+0.1+7.9±2.3
BH crosscourt29%+7.7+1.4+2.3+11.4±2.9
BH down the line11%+2.2+1.5±0.0+3.7±4.0
BH slice through the middle5%−6.2−1.8+0.5−7.6±2.0
BH slice crosscourt3%−4.2−2.2±0.0−6.3±2.1

Lean BH crosscourt: +4.8±2.4 per 100 returns v the current mix (2082 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JohannaValue
FH through the middle49%−3.2+0.7+0.4−2.1±2.5
FH crosscourt28%+0.5+1.8−0.9+1.5±3.8
FH down the line19%−0.6−1.8±0.0−2.3±3.4
FH slice through the middle3%−15.2+0.6±0.0−14.6±1.7

Lean FH crosscourt: +3.0±3.0 per 100 returns v the current mix (613 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JohannaValue
BH through the middle42%−2.6+1.3+0.5−0.8±2.3
BH crosscourt42%+1.5+1.5−1.1+1.9±3.0
BH down the line12%−0.5−0.3+0.5−0.3±4.1
FH through the middle1%−2.7−0.5+0.4−2.8±2.3
FH inside-out1%+1.4−0.6±0.0+0.8±2.5

Lean BH crosscourt: +1.5±2.1 per 100 returns v the current mix (1205 returns charted, inside the 90% margin)

Johanna Larsson returning

1st serve to the forehand

ReturnNowTourOwnv ElinaValue
FH through the middle41%+4.2−1.0−0.3+2.9±2.4
FH crosscourt29%+5.3+1.4−2.0+4.7±3.4
FH slice through the middle18%−6.7−0.6−0.4−7.8±2.0
FH down the line7%+1.5+1.8+2.2+5.6±2.9
FH slice crosscourt6%−6.6−1.0−1.4−9.1±2.3

Lean FH crosscourt: +3.7±2.6 per 100 returns v the current mix (101 returns charted)

1st serve to the backhand

ReturnNowTourOwnv ElinaValue
BH through the middle55%+6.0+0.1−0.2+6.0±2.2
BH crosscourt27%+7.7−0.8−0.3+6.7±2.8
BH down the line11%+2.2−0.5−0.5+1.2±3.2
BH slice through the middle8%−6.2+0.4−0.2−6.0±1.8

Lean BH crosscourt: +1.9±2.4 per 100 returns v the current mix (93 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv ElinaValue
BH through the middle29%−2.6+1.0−0.5−2.1±1.8
FH through the middle29%−2.7+0.5−0.1−2.2±1.8
BH crosscourt26%+1.5+0.5−0.2+1.8±2.4
FH inside-out17%+1.4+1.6+1.8+4.8±2.8

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.

Elina Svitolina

Favour

ShotEdgeOwnTheirs
BH to their forehand · rally+4.4±3.5+0.3+4.0
FH to their forehand · rally+3.4±2.4+0.5+2.9
BH to the middle · rally+3.0±1.8+1.4+1.7
FH to the middle · return+3.0±2.3+2.0+1.0
FH to their forehand · serve +1+2.9±3.3+1.0+1.9
FH to their backhand · serve +1+1.6±3.4+0.9+0.7

Avoid

ShotEdgeOwnTheirs
FH to the middle · rally+0.4±1.8+1.0−0.6
FH to their backhand · rally+0.9±2.8+1.0−0.1
BH to their backhand · rally+1.0±2.2+1.8−0.8
BH to the middle · return+1.2±2.0+0.9+0.3
BH to their backhand · return+1.3±2.6+0.6+0.7

Johanna Larsson

Favour

ShotEdgeOwnTheirs
BH to the middle · return+0.9±2.1+1.4−0.6
FH to their backhand · rally−0.2±3.1−0.7+0.4
FH to their forehand · return−0.2±3.5+1.1−1.3
FH to the middle · serve +1−0.4±2.2−0.1−0.3
BH to the middle · rally−0.4±1.7−0.3±0.0
BH to their backhand · rally−0.9±2.4−1.4+0.4

Avoid

ShotEdgeOwnTheirs
FH to the middle · rally−2.8±1.8−1.8−1.0
FH to the middle · return−1.5±2.2−1.4±0.0
FH to their forehand · rally−1.0±2.4−0.9−0.1
BH to their backhand · rally−0.9±2.4−1.4+0.4
BH to the middle · rally−0.4±1.7−0.3±0.0

Against Johanna Larsson-like opponents

Elina Svitolina vMatchesServe pts wonReturn pts won
All charted opponents–57.8%44.4%
Players most similar to Johanna Larsson3 59.1%45.4%

Similar by tactical fingerprint: Arantxa Rus, Suzan Lamens, Jil Teichmann, Emma Raducanu, Lucia Bronzetti, Ana Bogdan, Anna Lena Friedsam, Andrea Petkovic, Kiki Bertens. When two players have rarely met, their records against these lookalikes fill the gap.