RallyIQ

Game plan

Elina Svitolina v Lucia Bronzetti

Every number combines what Elina Svitolina does well with what Lucia Bronzetti 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 89%90%: 69%–98% · best of 5: 94%
Serve points won 61.8% / 52.3% Elina / Lucia · tour 56.3%
Strengths only, no similarity priors 90%serve 62.0% / 52.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Lucia Bronzetti's tactical lookalikes and in their charted head-to-heads (lookalikes: −2.4 on serve, +0.4 on return vs expectation (374 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

CareerElinaLucia
Direction choice−0.09 ±0.04
better than 37%
−0.37 ±0.15
better than 3%
Shot selection−0.08 ±0.06
better than 36%
+0.27 ±0.15
better than 75%
Execution+0.90 ±0.18
better than 88%
+0.14 ±0.68
better than 67%
Points left on the table2.66 ±0.05
lower than 41%
2.96 ±0.22
lower than 13%

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 LuciaMatchupOptimal
Wide39%69%67%70.0%±5.954% ▲
Body17%56%60%58.0%±10.02% ▼
T44%70%73%74.4%±6.944%

Optimal v Lucia Bronzetti: +1.0±0.9 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.5 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowElina winsv LuciaMatchupOptimal
Wide43%69%66%69.3%±6.159% ▲
Body15%59%57%60.1%±10.10% ▼
T41%64%70%69.1%±7.541%

Optimal v Lucia Bronzetti: +0.6±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.5 per 100 first serves in before the returner adjusts.

Lucia Bronzetti serving

Deuce court

1st serveNowLucia winsv ElinaMatchupOptimal
Wide48%73%65%72.3%±6.263% ▲
Body20%56%57%55.9%±9.55% ▼
T32%70%68%70.8%±7.932%

Optimal v Elina Svitolina: +0.6±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.

Ad court

1st serveNowLucia winsv ElinaMatchupOptimal
Wide42%52%64%50.7%±7.427% ▼
Body17%63%58%64.9%±9.317%
T41%60%66%61.8%±7.756% ▲

Optimal v Elina Svitolina: +0.4±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +7.2 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 LuciaValue
FH through the middle48%+4.2+2.2+0.2+6.6±2.4
FH crosscourt18%+5.3+1.2+1.4+7.9±3.6
FH down the line14%+1.5−0.5−3.0−1.9±3.8
FH slice through the middle12%−6.7+1.1+1.7−3.9±2.0
FH slice crosscourt5%−6.6−1.1+1.3−6.4±2.1

Lean FH crosscourt: +4.6±3.2 per 100 returns v the current mix (2739 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LuciaValue
BH through the middle48%+6.0+1.7+2.1+9.9±2.1
BH crosscourt29%+7.7+1.4+0.4+9.6±2.9
BH down the line11%+2.2+1.5−3.1+0.5±4.2
BH slice through the middle5%−6.2−1.8+1.1−6.9±2.2
BH slice crosscourt3%−4.2−2.2−0.6−7.0±2.7

Lean BH through the middle: +3.1±1.5 per 100 returns v the current mix (2082 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LuciaValue
FH through the middle49%−3.2+0.7+1.0−1.5±2.7
FH crosscourt28%+0.5+1.8−1.7+0.7±4.1
FH down the line19%−0.6−1.8+0.4−1.9±4.9
FH slice through the middle3%−15.2+0.6±0.0−14.6±1.7

Lean FH crosscourt: +2.0±3.3 per 100 returns v the current mix (613 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv LuciaValue
BH through the middle42%−2.6+1.3+1.4+0.1±2.3
BH crosscourt42%+1.5+1.5+1.6+4.6±3.0
BH down the line12%−0.5−0.3+1.2+0.4±4.9
FH through the middle1%−2.7−0.5+1.0−2.1±2.5
FH inside-out1%+1.4−0.6+0.4+1.2±3.8

Lean BH crosscourt: +2.7±2.1 per 100 returns v the current mix (1205 returns charted)

Lucia Bronzetti returning

1st serve to the forehand

ReturnNowTourOwnv ElinaValue
FH through the middle56%+4.2+1.0−0.3+4.9±2.2
FH crosscourt25%+5.3−2.3−2.0+1.0±3.5
FH down the line19%+1.5−5.7+2.2−1.9±3.8

Lean FH through the middle: +2.3±1.5 per 100 returns v the current mix (204 returns charted)

1st serve to the backhand

ReturnNowTourOwnv ElinaValue
BH through the middle54%+6.0−0.4−0.2+5.4±2.2
BH crosscourt30%+7.7+0.6−0.3+8.1±3.0
BH down the line16%+2.2−2.3−0.5−0.6±3.8

Lean BH crosscourt: +2.8±2.5 per 100 returns v the current mix (171 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv ElinaValue
BH through the middle51%−2.6+1.3−0.5−1.8±2.2
BH crosscourt27%+1.5−1.1−0.2+0.2±2.7
FH through the middle15%−2.7±0.0−0.1−2.8±1.8
BH down the line6%−0.5+1.0+2.0+2.5±2.9

Lean BH crosscourt: +1.3±2.3 per 100 returns v the current mix (78 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.

Elina Svitolina

Favour

ShotEdgeOwnTheirs
FH to their forehand · return +1+4.1±3.0+0.9+3.2
FH to their backhand · rally+3.8±2.4+1.0+2.8
FH to their backhand · return +1+3.6±3.5+1.4+2.2
FH to their backhand · serve +1+3.4±3.1+0.9+2.5
BH to the middle · return+3.1±1.8+0.9+2.1
BH to the middle · return +1+3.0±2.0+1.1+1.8

Avoid

ShotEdgeOwnTheirs
BH to their forehand · return−0.5±3.5+1.0−1.4
FH to the middle · serve +1±0.0±2.1+0.5−0.5
BH to their backhand · rally+0.2±2.2+1.8−1.6
BH to their forehand · rally+0.6±3.4+0.3+0.3
FH to the middle · rally+0.8±1.7+1.0−0.2

Lucia Bronzetti

Favour

ShotEdgeOwnTheirs
BH to their backhand · serve +1+3.2±2.9+2.4+0.8
FH to the middle · serve +1+2.8±2.0+3.1−0.3
FH to their forehand · serve +1+2.5±3.1+2.1+0.4
FH to their backhand · serve +1+2.0±3.0+0.6+1.4
FH to their forehand · rally+1.6±2.1+1.7−0.1
FH to their forehand · return +1+1.6±3.1+1.7−0.2

Avoid

ShotEdgeOwnTheirs
FH to their forehand · return−3.3±3.4−2.0−1.3
FH to their backhand · return−2.2±3.5−4.2+2.0
BH to their forehand · rally−1.6±3.3−1.1−0.5
FH to their backhand · rally−1.0±2.4−1.4+0.4
BH to their backhand · return−0.4±2.8+0.2−0.6

Against Lucia Bronzetti-like opponents

Elina Svitolina vMatchesServe pts wonReturn pts won
All charted opponents–57.8%44.4%
Players most similar to Lucia Bronzetti2 57.4%48.4%

Similar by tactical fingerprint: Suzan Lamens, Eva Vedder, Emma Navarro, Ajla Tomljanovic, Yafan Wang, Nao Hibino, Jennifer Brady, Rebecca Peterson, Johanna Larsson. When two players have rarely met, their records against these lookalikes fill the gap.