RallyIQ

Game plan

J J Wolf v Giovanni Mpetshi Perricard

Every number combines what J J Wolf does well with what Giovanni Mpetshi Perricard allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

J J Wolf wins, best of 3 38%90%: 16%–65% · best of 5: 35%
Serve points won 67.3% / 69.9% J / Giovanni · tour 63.4%
Strengths only, no similarity priors 38%serve 67.3% / 69.9%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerJGiovanni
Direction choice−0.12 ±0.22
better than 26%
−0.26 ±0.07
better than 9%
Shot selection+0.48 ±0.32
better than 91%
−0.11 ±0.24
better than 38%
Execution−1.36 ±1.07
better than 13%
+0.77 ±0.79
better than 90%

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.

J J Wolf serving

Deuce court

1st serveNowJ winsv GiovanniMatchupOptimal
Wide47%70%83%80.7%±6.260% ▲
Body8%64%69%68.8%±13.70% ▼
T45%75%81%81.1%±6.640% ▼

Optimal v Giovanni Mpetshi Perricard: +1.0±0.7 per 100 first serves (faults included) over the current mix. Serving T every time would read +1.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJ winsv GiovanniMatchupOptimal
Wide48%72%79%78.5%±7.161% ▲
Body10%60%67%64.4%±15.20% ▼
T42%60%78%67.4%±8.839% ▼

Optimal v Giovanni Mpetshi Perricard: +0.9±0.9 per 100 first serves (faults included) over the current mix. Serving wide every time would read +6.0 per 100 first serves in before the returner adjusts.

Giovanni Mpetshi Perricard serving

Deuce court

1st serveNowGiovanni winsv JMatchupOptimal
Wide45%79%76%81.9%±6.458% ▲
Body8%62%62%60.6%±13.10% ▼
T47%79%74%78.1%±6.742% ▼

Optimal v J J Wolf: +0.9±0.7 per 100 first serves (faults included) over the current mix. Serving wide every time would read +3.5 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowGiovanni winsv JMatchupOptimal
Wide54%82%73%81.5%±6.067% ▲
Body5%61%65%62.9%±14.70% ▼
T41%77%69%75.1%±8.233% ▼

Optimal v J J Wolf: +0.7±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.6 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.

J J Wolf returning

1st serve to the forehand

ReturnNowTourOwnv GiovanniValue
FH through the middle46%+4.3−0.3+0.7+4.7±2.8
FH crosscourt40%+5.5−1.7+0.6+4.3±4.4
FH down the line14%+1.7−0.3−2.2−0.8±3.8

Lean FH through the middle: +0.9±2.4 per 100 returns v the current mix (83 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv GiovanniValue
BH through the middle45%+6.4+1.9+0.5+8.9±2.6
BH crosscourt29%+8.8−1.7−2.2+4.9±3.4
BH down the line17%+4.2+0.9−0.6+4.6±4.4
BH slice through the middle9%−4.2−0.3+1.1−3.4±2.2

Lean BH through the middle: +3.0±1.9 per 100 returns v the current mix (124 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv GiovanniValue
BH crosscourt46%+1.0−2.0−0.4−1.4±3.2
BH through the middle43%−2.9−2.6+1.6−3.9±2.5
BH down the line12%−0.2−1.9+0.3−1.8±4.2

Lean BH crosscourt: +1.1±2.1 per 100 returns v the current mix (68 returns charted, inside the 90% margin)

Giovanni Mpetshi Perricard returning

1st serve to the forehand

ReturnNowTourOwnv JValue
FH through the middle36%+4.3+1.8±0.0+6.0±2.9
FH slice through the middle21%−4.2+1.4+0.3−2.5±2.2
FH down the line20%+1.7−0.5−0.3+0.9±4.3
FH crosscourt9%+5.5−2.0+1.1+4.5±4.3
FH slice down the line8%−4.3+2.2±0.0−2.0±2.3

Lean FH through the middle: +4.1±2.1 per 100 returns v the current mix (466 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JValue
BH through the middle29%+6.4+0.9+1.0+8.3±2.7
BH slice through the middle25%−4.2+2.9−1.0−2.3±2.3
BH slice crosscourt17%+0.5+1.4−1.3+0.6±2.5
BH crosscourt11%+8.8+1.6+0.9+11.3±3.5
BH down the line10%+4.2−3.5+2.1+2.8±4.2

Lean BH crosscourt: +8.1±3.3 per 100 returns v the current mix (551 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JValue
FH through the middle45%−3.5−1.8+0.4−4.9±2.9
FH down the line34%−1.8−5.4+0.7−6.5±4.5
FH crosscourt12%−0.2−0.8−4.7−5.7±3.8
FH slice through the middle5%−12.7−0.2±0.0−12.9±1.1
FH slice down the line4%−9.4−0.8±0.0−10.3±1.4

Lean FH through the middle: +1.3±2.2 per 100 returns v the current mix (139 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JValue
BH through the middle34%−2.9−1.8+0.4−4.2±2.5
BH down the line20%−0.2−0.1+0.8+0.5±4.6
BH crosscourt15%+1.0−4.5+0.1−3.4±3.3
BH slice through the middle8%−11.3−0.5±0.0−11.8±1.7
BH slice crosscourt8%−4.0−1.4±0.0−5.4±1.8

Lean BH down the line: +4.4±3.8 per 100 returns v the current mix (384 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.

J J Wolf

Favour

ShotEdgeOwnTheirs
BH to the middle · return+1.5±2.3−0.5+2.0
BH to their backhand · rally+1.4±2.5−0.4+1.8
FH to their forehand · rally+0.3±3.0−0.2+0.5
FH to their backhand · rally−0.1±2.8−0.8+0.6
FH to their backhand · serve +1−0.4±3.2−1.1+0.8
FH to the middle · return−0.6±2.5−0.6+0.1

Avoid

ShotEdgeOwnTheirs
FH to their forehand · serve +1−3.8±3.6−4.1+0.3
BH to their backhand · return−3.0±3.1−2.4−0.6
FH to the middle · rally−2.2±2.4−2.5+0.3
BH to the middle · rally−1.5±2.2−1.2−0.4
FH to the middle · return−0.6±2.5−0.6+0.1

Giovanni Mpetshi Perricard

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+2.2±3.4−0.9+3.1
FH to their backhand · serve +1+1.2±3.5−0.9+2.1
FH to the middle · return−0.3±2.5−0.3±0.0
BH to their backhand · return−0.6±3.3−1.0+0.4
BH to the middle · rally−0.7±2.2−1.4+0.8
FH to the middle · rally−0.8±2.3−0.9+0.2

Avoid

ShotEdgeOwnTheirs
FH to their backhand · rally−2.3±3.0−2.9+0.6
BH to their backhand · rally−1.4±2.7−2.1+0.7
BH to the middle · return−0.8±2.3−1.5+0.7
BH to their forehand · rally−0.8±4.4−4.2+3.4
FH to the middle · rally−0.8±2.3−0.9+0.2

Against Giovanni Mpetshi Perricard-like opponents

J J Wolf vMatchesServe pts wonReturn pts won
All charted opponents–57.6%33.2%

Similar by tactical fingerprint: Jiri Lehecka, Ben Shelton, Denis Shapovalov, Alexei Popyrin, Reilly Opelka, Gabriel Diallo, Christopher Eubanks, Tim Van Rijthoven, Vasek Pospisil, Jo Wilfried Tsonga. When two players have rarely met, their records against these lookalikes fill the gap.