RallyIQ

Game plan

Linda Klimovicova v Solana Sierra

Every number combines what Linda Klimovicova does well with what Solana Sierra allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Linda Klimovicova wins, best of 3 81%90%: 46%–97% · best of 5: 86%
Serve points won 62.2% / 55.4% Linda / Solana · tour 56.4%
Strengths only, no similarity priors 80%serve 62.1% / 55.6%

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. Both were charted enough in the last three seasons, so those carry the most weight. The result is then nudged by Linda Klimovicova's record against Solana Sierra's tactical lookalikes and in their charted head-to-heads (lookalikes: +1.0 on serve, +1.7 on return vs expectation (213 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

CareerLindaSolana
Direction choice+0.27 ±0.09
better than 92%
−0.29 ±0.07
better than 7%
Shot selection+0.47 ±0.14
better than 93%
−0.05 ±0.13
better than 41%
Execution+1.01 ±0.86
better than 92%
−3.33 ±0.95
better than 1%
Points left on the table2.13 ±0.17
lower than 97%
2.85 ±0.17
lower than 20%

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.

Linda Klimovicova serving

Deuce court

1st serveNowLinda winsv SolanaMatchupOptimal
Wide45%63%67%64.8%±8.645%
Body17%59%68%69.7%±10.31% ▼
T39%78%72%80.7%±7.954% ▲

Optimal v Solana Sierra: +0.5±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +8.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLinda winsv SolanaMatchupOptimal
Wide53%72%65%71.4%±8.668% ▲
Body16%48%56%47.6%±11.91% ▼
T31%68%63%66.9%±9.731%

Optimal v Solana Sierra: +1.2±1.2 per 100 first serves (faults included) over the current mix. Serving wide every time would read +5.1 per 100 first serves in before the returner adjusts.

Solana Sierra serving

Deuce court

1st serveNowSolana winsv LindaMatchupOptimal
Wide50%65%68%66.3%±8.261% ▲
Body21%60%54%56.3%±10.16% ▼
T29%67%68%67.1%±10.933% ▲

Optimal v Linda Klimovicova: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSolana winsv LindaMatchupOptimal
Wide37%61%61%56.4%±9.736%
Body22%58%55%57.7%±11.07% ▼
T41%56%64%55.8%±10.257% ▲

Optimal v Linda Klimovicova: +0.1±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +1.3 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.

Linda Klimovicova returning

1st serve to the forehand

ReturnNowTourOwnv SolanaValue
FH through the middle43%+4.2+1.1+0.4+5.7±2.8
FH crosscourt25%+5.3+1.6−0.1+6.7±4.4
FH down the line17%+1.5+1.0−0.6+2.0±4.7
FH slice through the middle10%−6.7+0.8−0.2−6.2±2.4
FH slice crosscourt6%−6.6+0.5+1.7−4.4±2.1

Lean FH crosscourt: +3.1±3.6 per 100 returns v the current mix (215 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv SolanaValue
BH through the middle43%+6.0+1.8−0.3+7.5±2.8
BH crosscourt38%+7.7+2.8−3.6+6.9±3.6
BH down the line7%+2.2+0.9−3.2−0.1±4.2
BH slice crosscourt7%−4.2−0.4+0.2−4.4±2.6
BH slice through the middle4%−6.2±0.0+1.0−5.2±2.0

Lean BH through the middle: +2.1±2.2 per 100 returns v the current mix (195 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv SolanaValue
BH crosscourt53%+1.5+1.9+0.3+3.6±3.7
BH through the middle35%−2.6−0.5+0.1−3.0±2.7
FH inside-in6%+0.7+1.5−1.4+0.9±3.9
BH down the line5%−0.5−0.3−2.1−2.9±4.2

Lean BH crosscourt: +2.8±2.0 per 100 returns v the current mix (94 returns charted)

Solana Sierra returning

1st serve to the forehand

ReturnNowTourOwnv LindaValue
FH through the middle42%+4.2−0.4+1.8+5.6±3.0
FH down the line28%+1.5−3.2−3.6−5.2±4.7
FH crosscourt16%+5.3−1.0−1.2+3.0±4.2
FH slice through the middle7%−6.7−2.1−0.4−9.3±2.3
FH slice crosscourt4%−6.6−0.9−0.5−8.0±2.2

Lean FH through the middle: +5.6±2.3 per 100 returns v the current mix (240 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LindaValue
BH through the middle36%+6.0−2.5+0.7+4.3±3.0
BH crosscourt28%+7.7−0.9+3.2+10.0±3.7
BH down the line18%+2.2−0.1−4.4−2.3±4.5
BH slice through the middle9%−6.2−0.5−0.9−7.5±2.2
BH slice crosscourt5%−4.2+0.4−1.2−5.0±2.5

Lean BH crosscourt: +7.6±3.0 per 100 returns v the current mix (148 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LindaValue
FH crosscourt44%+0.5+3.5+2.5+6.5±4.3
FH through the middle36%−3.2−1.3−2.3−6.7±2.9
FH down the line20%−0.6+0.1−0.4−0.8±4.7

Lean FH crosscourt: +6.2±2.8 per 100 returns v the current mix (50 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv LindaValue
BH through the middle50%−2.6+0.4−2.0−4.2±2.7
BH crosscourt37%+1.5+0.5−0.4+1.6±3.6
BH down the line13%−0.5−1.6−2.9−5.1±4.6

Lean BH crosscourt: +3.8±2.7 per 100 returns v the current mix (78 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.

Linda Klimovicova

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+5.0±3.0+3.2+1.8
FH to their forehand · return+3.4±4.3+4.2−0.7
BH to their backhand · serve +1+2.6±3.8+3.3−0.7
FH to the middle · return+1.9±2.6+1.3+0.6
BH to the middle · serve +1+1.1±2.6+2.3−1.2
FH to their forehand · return +1+0.7±3.9+1.9−1.3

Avoid

ShotEdgeOwnTheirs
FH to their backhand · return +1−6.5±4.3−0.7−5.8
BH to their forehand · return−2.7±4.6+1.2−3.9
FH to their backhand · serve +1−2.5±4.2+0.2−2.7
BH to the middle · return +1−2.4±2.6+0.8−3.3
BH to their backhand · rally−1.6±2.9+0.5−2.1

Solana Sierra

Favour

ShotEdgeOwnTheirs
FH to their backhand · rally+3.6±3.6−2.4+6.0
FH to their forehand · return+3.5±4.5+2.8+0.7
BH to their backhand · rally+1.8±3.0−1.7+3.5
FH to their forehand · return +1+1.2±4.0−1.9+3.2
FH to their forehand · rally+0.8±2.9−1.3+2.1
BH to their backhand · serve +1+0.2±3.6−0.3+0.5

Avoid

ShotEdgeOwnTheirs
BH to their forehand · return−10.2±4.6−4.8−5.4
FH to their backhand · return−7.2±4.2−4.4−2.8
BH to the middle · return−5.9±2.4−3.8−2.2
BH to their forehand · serve +1−5.7±4.9−7.9+2.2
BH to the middle · serve +1−4.5±2.5−3.5−1.0

Against Solana Sierra-like opponents

Linda Klimovicova vMatchesServe pts wonReturn pts won
All charted opponents–60.2%42.6%
Players most similar to Solana Sierra1 57.7%42.2%

Similar by tactical fingerprint: Iva Jovic, Anastasia Potapova, Karolina Pliskova, Tereza Valentova, Shuai Zhang, Elena Gabriela Ruse, Jessica Bouzas Maneiro, Veronika Kudermetova, Irina Camelia Begu, Anett Kontaveit. When two players have rarely met, their records against these lookalikes fill the gap.