RallyIQ

Game plan

Juan Pablo Varillas v Aleksandar Vukic

Every number combines what Juan Pablo Varillas does well with what Aleksandar Vukic allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Juan Pablo Varillas wins, best of 3 78%90%: 49%–94% · best of 5: 83%
Serve points won 69.7% / 63.3% Juan / Aleksandar · tour 63.8%
Strengths only, no similarity priors 78%serve 69.7% / 63.3%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Juan Pablo Varillas's record against Aleksandar Vukic's tactical lookalikes and in their charted head-to-heads. 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

CareerJuanAleksandar
Direction choice−0.06 ±0.13
better than 43%
−0.13 ±0.20
better than 24%
Shot selection+0.37 ±0.13
better than 84%
+0.04 ±0.24
better than 58%
Execution−0.07 ±0.85
better than 65%
−0.89 ±0.39
better than 28%
Points left on the table2.44 ±0.20
lower than 69%
2.44 ±0.25
lower than 68%

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.

Juan Pablo Varillas serving

Deuce court

1st serveNowJuan winsv AleksandarMatchupOptimal
Wide41%72%75%73.9%±8.236% ▼
Body8%54%59%49.5%±13.60% ▼
T51%68%86%80.8%±7.064% ▲

Optimal v Aleksandar Vukic: +0.9±0.8 per 100 first serves (faults included) over the current mix. Serving T every time would read +5.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJuan winsv AleksandarMatchupOptimal
Wide50%66%73%65.8%±8.644% ▼
Body7%66%62%65.1%±15.00% ▼
T42%73%81%81.9%±7.256% ▲

Optimal v Aleksandar Vukic: +0.5±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +9.3 per 100 first serves in before the returner adjusts.

Aleksandar Vukic serving

Deuce court

1st serveNowAleksandar winsv JuanMatchupOptimal
Wide44%70%78%74.6%±7.840% ▼
Body9%56%67%60.5%±14.50% ▼
T47%78%76%78.6%±7.260% ▲

Optimal v Juan Pablo Varillas: +0.7±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAleksandar winsv JuanMatchupOptimal
Wide53%77%72%75.8%±7.746% ▼
Body5%62%64%63.5%±15.80% ▼
T41%72%75%75.3%±8.054% ▲

Optimal v Juan Pablo Varillas: +0.4±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +0.9 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.

Juan Pablo Varillas returning

1st serve to the forehand

ReturnNowTourOwnv AleksandarValue
FH through the middle57%+4.3±0.0±0.0+4.2±3.0
FH down the line23%+1.7−1.7−0.9−0.9±4.5
FH crosscourt16%+5.5−0.3±0.0+5.3±4.3
FH slice through the middle5%−4.2−0.7−0.6−5.6±2.0

Lean FH crosscourt: +2.5±4.1 per 100 returns v the current mix (166 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv AleksandarValue
BH through the middle51%+6.4−1.1−0.9+4.4±2.7
BH crosscourt29%+8.8+1.3−2.9+7.2±3.5
BH down the line16%+4.2+0.2+1.9+6.2±4.5
BH slice through the middle4%−4.2−0.5−1.7−6.4±2.1

Lean BH crosscourt: +2.1±3.0 per 100 returns v the current mix (171 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv AleksandarValue
BH through the middle41%−2.9+0.8+0.1−2.0±2.5
BH crosscourt35%+1.0+1.9−1.3+1.6±3.3
FH through the middle11%−2.9+0.7+0.2−2.0±2.3
BH down the line8%−0.2−0.5+2.9+2.2±4.6
FH inside-out5%+1.0+1.4−0.3+2.1±3.2

Lean BH crosscourt: +1.8±2.4 per 100 returns v the current mix (170 returns charted, inside the 90% margin)

Aleksandar Vukic returning

1st serve to the forehand

ReturnNowTourOwnv JuanValue
FH through the middle52%+4.3−0.5−2.0+1.8±3.0
FH crosscourt22%+5.5+2.7−0.1+8.1±4.3
FH down the line21%+1.7−2.5−1.1−1.9±4.4
FH slice through the middle5%−4.2−0.7±0.0−4.9±1.0

Lean FH crosscourt: +6.0±3.8 per 100 returns v the current mix (126 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JuanValue
BH through the middle46%+6.4+0.1+0.1+6.7±2.7
BH crosscourt26%+8.8−2.5+1.3+7.6±3.6
BH down the line13%+4.2−4.2+1.0+1.0±4.4
BH slice through the middle9%−4.2−1.5+0.3−5.4±2.2
BH slice down the line4%−8.4−1.8±0.0−10.2±1.9

Lean BH crosscourt: +3.4±3.0 per 100 returns v the current mix (224 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JuanValue
BH through the middle44%−2.9±0.0−0.6−3.5±2.6
BH crosscourt29%+1.0−1.5+0.6+0.2±3.2
BH down the line10%−0.2−1.1−0.4−1.7±4.1
FH through the middle7%−2.9−0.5+0.9−2.4±2.1
FH inside-out6%+1.0+0.5+0.4+1.8±3.1

Lean BH crosscourt: +2.0±2.6 per 100 returns v the current mix (104 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 on hard. Each player's hard record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Juan Pablo Varillas

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+7.7±5.7+2.0+5.7
FH to their forehand · return +1+5.7±6.3+1.3+4.4
FH to their backhand · rally+4.9±4.0+0.6+4.3
BH to their backhand · rally+3.8±3.7+2.5+1.3
BH to the middle · serve +1+3.3±4.0+3.6−0.3
FH to their forehand · rally+2.1±4.3+0.6+1.6

Avoid

ShotEdgeOwnTheirs
FH to their backhand · return +1−4.0±5.9−6.4+2.4
BH to their forehand · rally−3.6±6.3−4.2+0.7
BH to their backhand · return +1−2.7±5.1−5.8+3.1
BH to their backhand · return−2.4±4.7+1.4−3.8
BH to the middle · return−1.6±3.4−0.6−1.0

Aleksandar Vukic

Favour

ShotEdgeOwnTheirs
FH to their forehand · return +1+4.8±6.3+2.7+2.0
FH to their forehand · rally+4.2±4.2+0.9+3.3
BH to their forehand · rally+3.0±5.9−1.7+4.7
BH to the middle · rally+2.6±3.1+0.6+2.0
FH to their backhand · rally+1.8±4.2−0.8+2.5
FH to the middle · rally+1.4±3.4+0.3+1.1

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−5.4±3.9−2.0−3.4
FH to their backhand · return +1−5.2±6.1−1.5−3.7
BH to their backhand · rally−1.8±3.7−1.9±0.0
FH to their backhand · serve +1−1.7±5.0−4.2+2.6
BH to the middle · return−1.7±3.4−1.7±0.0

Against Aleksandar Vukic-like opponents

Juan Pablo Varillas vMatchesServe pts wonReturn pts won
All charted opponents–60.6%36.1%

Similar by tactical fingerprint: Stefanos Tsitsipas, Flavio Cobolli, Andrey Rublev, Thiago Seyboth Wild, Zizou Bergs, Marin Cilic, J J Wolf, Kyle Edmund, Philipp Kohlschreiber. When two players have rarely met, their records against these lookalikes fill the gap.