RallyIQ

Game plan

Juan Pablo Varillas v J J Wolf

Every number combines what Juan Pablo Varillas does well with what J J Wolf 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 72%90%: 38%–93% · best of 5: 77%
Serve points won 64.7% / 60.1% Juan / J · tour 63.4%
Strengths only, no similarity priors 72%serve 64.7% / 60.1%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 J J Wolf'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

CareerJuanJ
Direction choice−0.06 ±0.13
better than 43%
−0.12 ±0.22
better than 26%
Shot selection+0.37 ±0.13
better than 84%
+0.48 ±0.32
better than 91%
Execution−0.07 ±0.85
better than 65%
−1.36 ±1.07
better 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.

Juan Pablo Varillas serving

Deuce court

1st serveNowJuan winsv JMatchupOptimal
Wide41%72%76%74.8%±9.438% ▼
Body8%54%62%52.6%±15.60% ▼
T51%68%74%65.9%±9.862% ▲

Optimal v J J Wolf: +0.6±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +6.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJuan winsv JMatchupOptimal
Wide50%66%73%65.4%±10.044% ▼
Body7%66%65%68.4%±15.70% ▼
T42%73%69%70.3%±10.456% ▲

Optimal v J J Wolf: +0.5±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.6 per 100 first serves in before the returner adjusts.

J J Wolf serving

Deuce court

1st serveNowJ winsv JuanMatchupOptimal
Wide47%70%78%75.3%±8.660% ▲
Body8%64%67%67.5%±15.20% ▼
T45%75%76%75.5%±9.240% ▼

Optimal v Juan Pablo Varillas: +0.4±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +0.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJ winsv JuanMatchupOptimal
Wide48%72%72%71.5%±9.861% ▲
Body10%60%64%61.7%±16.90% ▼
T42%60%75%64.2%±10.739% ▼

Optimal v Juan Pablo Varillas: +0.3±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.1 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 JValue
FH through the middle57%+4.3±0.0±0.0+4.3±3.0
FH down the line23%+1.7−1.7−0.3−0.2±4.4
FH crosscourt16%+5.5−0.3+1.1+6.3±4.2
FH slice through the middle5%−4.2−0.7+0.3−4.6±2.0

Lean FH crosscourt: +3.2±4.1 per 100 returns v the current mix (166 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JValue
BH through the middle51%+6.4−1.1+1.0+6.4±2.8
BH crosscourt29%+8.8+1.3+0.9+11.0±3.6
BH down the line16%+4.2+0.2+2.1+6.4±4.1
BH slice through the middle4%−4.2−0.5−1.0−5.8±2.0

Lean BH crosscourt: +3.8±3.0 per 100 returns v the current mix (171 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JValue
BH through the middle41%−2.9+0.8+0.4−1.7±2.6
BH crosscourt35%+1.0+1.9+0.1+3.0±3.3
FH through the middle11%−2.9+0.7+0.4−1.8±2.3
BH down the line8%−0.2−0.5+0.8+0.1±4.2
FH inside-out5%+1.0+1.4+0.7+3.0±3.0

Lean BH crosscourt: +2.7±2.4 per 100 returns v the current mix (170 returns charted)

J J Wolf returning

1st serve to the forehand

ReturnNowTourOwnv JuanValue
FH through the middle46%+4.3−0.3−2.0+2.0±3.0
FH crosscourt40%+5.5−1.7−0.1+3.7±4.3
FH down the line14%+1.7−0.3−1.1+0.3±4.1

Lean FH crosscourt: +1.3±3.0 per 100 returns v the current mix (83 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JuanValue
BH through the middle45%+6.4+1.9+0.1+8.5±2.8
BH crosscourt29%+8.8−1.7+1.3+8.4±3.6
BH down the line17%+4.2+0.9+1.0+6.1±4.3
BH slice through the middle9%−4.2−0.3+0.3−4.2±2.0

Lean BH through the middle: +1.5±2.0 per 100 returns v the current mix (124 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JuanValue
BH crosscourt46%+1.0−2.0+0.6−0.3±3.2
BH through the middle43%−2.9−2.6−0.6−6.1±2.5
BH down the line12%−0.2−1.9−0.4−2.4±3.9

Lean BH crosscourt: +2.7±2.1 per 100 returns v the current mix (68 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.

Juan Pablo Varillas

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+3.9±3.4+0.8+3.1
FH to their backhand · serve +1+3.1±3.7+0.9+2.1
BH to their backhand · return+2.0±3.3+1.6+0.4
BH to their backhand · rally+1.9±2.5+1.2+0.7
FH to their backhand · rally+1.8±3.0+1.2+0.6
FH to the middle · return+0.9±2.7+0.9±0.0

Avoid

ShotEdgeOwnTheirs
FH to the middle · rally−0.7±2.4−0.9+0.2
BH to the middle · rally+0.6±2.2−0.2+0.8
BH to the middle · return+0.7±2.5±0.0+0.7
BH to their forehand · rally+0.8±4.4−2.6+3.4
FH to the middle · return+0.9±2.7+0.9±0.0

J J Wolf

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+2.4±3.2−0.2+2.6
BH to the middle · rally+0.9±2.3−1.2+2.1
FH to their backhand · rally+0.4±3.1−0.8+1.2
BH to the middle · return−0.7±2.5−0.5−0.2
FH to their backhand · serve +1−0.7±3.6−1.1+0.4
BH to their backhand · return−1.1±3.3−2.4+1.3

Avoid

ShotEdgeOwnTheirs
FH to their forehand · serve +1−2.3±4.1−4.1+1.7
FH to the middle · return−1.6±2.8−0.6−1.0
FH to the middle · rally−1.5±2.4−2.5+1.0
BH to their backhand · rally−1.2±2.6−0.4−0.8
BH to their backhand · return−1.1±3.3−2.4+1.3

Against J J Wolf-like opponents

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

Similar by tactical fingerprint: Stefanos Tsitsipas, Andrey Rublev, Felix Auger Aliassime, Guy Den Ouden, Marin Cilic, Aleksandar Vukic, Thanasi Kokkinakis, Lloyd Harris, Kyle Edmund, Juan Ignacio Londero. When two players have rarely met, their records against these lookalikes fill the gap.