RallyIQ

Game plan

Sara Bejlek v Martina Trevisan

Every number combines what Sara Bejlek does well with what Martina Trevisan allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Sara Bejlek wins, best of 3 30%90%: 7%–67% · best of 5: 26%
Serve points won 47.9% / 51.7% Sara / Martina · tour 56.3%
Strengths only, no similarity priors 31%serve 48.1% / 51.8%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Sara Bejlek's record against Martina Trevisan's tactical lookalikes and in their charted head-to-heads (lookalikes: −5.2 on serve, +2.1 on return vs expectation (136 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

CareerSaraMartina
Direction choice−0.14 ±0.15
better than 27%
−0.17 ±0.15
better than 22%
Shot selection+0.24 ±0.28
better than 72%
+0.41 ±0.23
better than 91%
Execution−0.48 ±0.87
better than 34%
−0.41 ±0.87
better than 38%

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.

Sara Bejlek serving

Deuce court

1st serveNowSara winsv MartinaMatchupOptimal
Wide29%59%67%60.3%±11.544% ▲
Body36%51%57%50.2%±12.021% ▼
T35%56%63%50.4%±13.335%

Optimal v Martina Trevisan: +0.7±1.3 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +7.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSara winsv MartinaMatchupOptimal
Wide49%65%63%62.4%±11.264% ▲
Body32%57%54%54.8%±12.317% ▼
T19%53%61%49.4%±13.919%

Optimal v Martina Trevisan: +0.3±1.3 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.9 per 100 first serves in before the returner adjusts.

Martina Trevisan serving

Deuce court

1st serveNowMartina winsv SaraMatchupOptimal
Wide23%67%67%67.4%±11.838% ▲
Body32%54%53%49.4%±12.817% ▼
T45%52%74%58.7%±12.645%

Optimal v Sara Bejlek: +0.9±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +9.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMartina winsv SaraMatchupOptimal
Wide54%55%68%57.9%±11.254%
Body30%48%57%48.9%±13.515% ▼
T16%66%65%65.9%±12.931% ▲

Optimal v Sara Bejlek: +1.0±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +9.4 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.

Sara Bejlek returning

1st serve to the forehand

ReturnNowTourOwnv MartinaValue
FH through the middle35%+4.2−0.9+0.7+3.9±3.0
FH crosscourt29%+5.3+1.3−4.6+2.0±4.2
FH down the line28%+1.5+1.6+2.1+5.2±4.5
FH slice through the middle9%−6.7−0.1±0.0−6.8±1.1

Lean FH down the line: +2.4±3.6 per 100 returns v the current mix (69 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv MartinaValue
BH through the middle50%+6.0+0.1+2.6+8.7±2.8
BH crosscourt28%+7.7+0.6−6.2+2.2±3.7
BH down the line22%+2.2−0.3+3.3+5.1±4.6

Lean BH through the middle: +2.6±2.0 per 100 returns v the current mix (134 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv MartinaValue
BH through the middle35%−2.6−0.3+1.4−1.5±2.7
BH crosscourt31%+1.5−0.3−0.2+1.0±3.4
FH through the middle19%−2.7+0.5−1.2−3.3±2.4
BH down the line15%−0.5−0.5−0.9−1.9±4.6

Lean BH crosscourt: +2.1±2.7 per 100 returns v the current mix (62 returns charted, inside the 90% margin)

Martina Trevisan returning

1st serve to the forehand

ReturnNowTourOwnv SaraValue
FH crosscourt43%+5.3+2.1±0.0+7.4±4.2
FH through the middle38%+4.2−0.5+1.1+4.8±3.2
FH down the line19%+1.5+2.5+2.9+6.8±4.5

Lean FH crosscourt: +1.1±2.8 per 100 returns v the current mix (103 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv SaraValue
BH through the middle45%+6.0+0.8+1.8+8.6±2.8
BH down the line22%+2.2−1.3+3.8+4.7±4.7
BH crosscourt14%+7.7−4.4+2.1+5.4±3.6
BH slice through the middle14%−6.2−3.2±0.0−9.4±1.8
BH slice down the line3%−12.5−2.0±0.0−14.5±1.6

Lean BH through the middle: +4.7±1.9 per 100 returns v the current mix (218 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv SaraValue
BH through the middle38%−2.6−1.0−0.5−4.0±2.7
BH crosscourt25%+1.5+0.9−0.1+2.3±3.0
BH down the line10%−0.5+0.8+2.8+3.1±4.3
FH inside-out10%+1.4+2.6+1.5+5.5±3.5
FH inside-in9%+0.7+0.2+1.3+2.3±3.5

Lean BH crosscourt: +2.3±2.6 per 100 returns v the current mix (68 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.

Sara Bejlek

Favour

ShotEdgeOwnTheirs
BH to their forehand · return+4.2±4.5+2.7+1.5
BH to the middle · return+4.0±2.6+0.9+3.0
FH to the middle · rally+3.6±2.5+1.3+2.4
FH to their backhand · return +1+2.1±4.3+1.1+1.0
FH to their backhand · rally+2.0±3.3+1.7+0.2
BH to their forehand · rally+1.5±4.0+0.3+1.2

Avoid

ShotEdgeOwnTheirs
FH to their forehand · rally−1.4±3.7−1.0−0.5
FH to the middle · return−0.8±2.9−0.9+0.1
BH to their backhand · rally−0.3±3.3−0.1−0.2
BH to the middle · rally+0.5±2.3−0.1+0.6
FH to their backhand · serve +1+0.8±4.2−0.7+1.5

Martina Trevisan

Favour

ShotEdgeOwnTheirs
BH to their forehand · return+5.6±4.6+0.6+5.0
FH to their backhand · return+5.1±4.4+1.8+3.3
BH to their forehand · rally+3.2±4.2−0.6+3.8
BH to the middle · return+3.1±2.5+1.4+1.6
FH to their backhand · return +1+2.8±4.2+0.9+2.0
FH to their backhand · rally+2.1±3.1+1.3+0.9

Avoid

ShotEdgeOwnTheirs
FH to their forehand · serve +1−2.9±4.2+1.9−4.8
BH to their backhand · rally−1.2±3.3−2.0+0.8
FH to their backhand · serve +1−0.5±4.0+0.4−0.9
FH to the middle · serve +1−0.2±2.8−1.1+0.8
FH to their forehand · rally+0.3±3.4−1.4+1.7

Against Martina Trevisan-like opponents

Sara Bejlek vMatchesServe pts wonReturn pts won
All charted opponents–45.0%40.9%
Players most similar to Martina Trevisan1 44.4%45.3%

Similar by tactical fingerprint: Cristina Bucsa, Diana Shnaider, Arantxa Rus, Marta Kostyuk, Leylah Fernandez, Jil Teichmann, Olga Danilovic, Kaja Juvan, Victoria Jimenez Kasintseva. When two players have rarely met, their records against these lookalikes fill the gap.