RallyIQ

Game plan

Felix Auger Aliassime v J J Wolf

Every number combines what Felix Auger Aliassime 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

Felix Auger Aliassime wins, best of 3 87%90%: 66%–97% · best of 5: 92%
Serve points won 68.3% / 59.1% Felix / J · tour 63.4%
Strengths only, no similarity priors 85%serve 67.5% / 59.2%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Felix Auger Aliassime's record against J J Wolf's tactical lookalikes and in their charted head-to-heads (lookalikes: +2.4 on serve, +0.3 on return vs expectation (1565 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

CareerFelixJ
Direction choice+0.01 ±0.05
better than 60%
−0.12 ±0.22
better than 26%
Shot selection+0.50 ±0.08
better than 93%
+0.48 ±0.32
better than 91%
Execution−0.79 ±0.31
better than 33%
−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.

Felix Auger Aliassime serving

Deuce court

1st serveNowFelix winsv JMatchupOptimal
Wide50%78%76%80.3%±6.445% ▼
Body8%66%62%64.6%±11.40% ▼
T42%78%74%76.3%±6.555% ▲

Optimal v J J Wolf: +0.7±0.7 per 100 first serves (faults included) over the current mix. Serving wide every time would read +3.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowFelix winsv JMatchupOptimal
Wide46%75%73%75.0%±6.740% ▼
Body6%63%65%65.4%±12.70% ▼
T47%76%69%74.1%±7.760% ▲

Optimal v J J Wolf: +0.6±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.1 per 100 first serves in before the returner adjusts.

J J Wolf serving

Deuce court

1st serveNowJ winsv FelixMatchupOptimal
Wide47%70%75%72.7%±7.060% ▲
Body8%64%64%64.2%±12.70% ▼
T45%75%74%73.6%±7.740% ▼

Optimal v Felix Auger Aliassime: +0.7±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJ winsv FelixMatchupOptimal
Wide48%72%72%71.1%±7.961% ▲
Body10%60%65%62.7%±13.20% ▼
T42%60%74%62.2%±8.439% ▼

Optimal v Felix Auger Aliassime: +0.3±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.6 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.

Felix Auger Aliassime returning

1st serve to the forehand

ReturnNowTourOwnv JValue
FH through the middle50%+4.3−0.6±0.0+3.7±2.4
FH down the line21%+1.7−0.9−0.3+0.5±3.7
FH crosscourt20%+5.5−1.5+1.1+5.0±3.6
FH slice through the middle6%−4.2−1.3+0.3−5.1±2.2
FH slice down the line2%−4.3+0.1±0.0−4.2±2.2

Lean FH crosscourt: +2.6±3.2 per 100 returns v the current mix (1741 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JValue
BH through the middle39%+6.4+1.5+1.0+9.0±2.2
BH crosscourt34%+8.8+0.1+0.9+9.8±2.8
BH slice through the middle11%−4.2−0.9−1.0−6.1±2.2
BH down the line7%+4.2+1.4+2.1+7.7±3.9
BH slice crosscourt6%+0.5−1.8−1.3−2.6±2.4

Lean BH crosscourt: +3.3±2.1 per 100 returns v the current mix (2015 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JValue
FH through the middle47%−3.5−0.1+0.4−3.2±2.7
FH crosscourt30%−0.2−0.5−4.7−5.5±3.9
FH down the line19%−1.8−2.0+0.7−3.1±4.5
FH slice through the middle2%−12.7+0.3±0.0−12.4±1.2
FH slice down the line1%−9.4+0.1±0.0−9.4±1.4

Lean FH down the line: +1.1±4.0 per 100 returns v the current mix (403 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JValue
BH crosscourt36%+1.0−3.2+0.1−2.1±2.7
BH through the middle34%−2.9−1.3+0.4−3.8±2.1
FH through the middle9%−2.9−0.2+0.4−2.7±2.4
BH down the line8%−0.2+2.0+0.8+2.6±4.5
FH inside-in6%+0.6+1.4−4.7−2.8±4.0

Lean BH down the line: +4.8±4.3 per 100 returns v the current mix (1299 returns charted)

J J Wolf returning

1st serve to the forehand

ReturnNowTourOwnv FelixValue
FH through the middle46%+4.3−0.3−0.2+3.8±2.4
FH crosscourt40%+5.5−1.7−0.6+3.2±3.9
FH down the line14%+1.7−0.3−3.3−1.9±3.2

Lean FH through the middle: +1.1±2.1 per 100 returns v the current mix (83 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv FelixValue
BH through the middle45%+6.4+1.9+0.6+8.9±2.3
BH crosscourt29%+8.8−1.7−0.6+6.5±3.0
BH down the line17%+4.2+0.9−1.4+3.7±4.1
BH slice through the middle9%−4.2−0.3−2.0−6.5±1.9

Lean BH through the middle: +2.9±1.7 per 100 returns v the current mix (124 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv FelixValue
BH crosscourt46%+1.0−2.0−1.5−2.5±2.6
BH through the middle43%−2.9−2.6+0.1−5.4±2.0
BH down the line12%−0.2−1.9+0.3−1.8±3.9

Lean BH crosscourt: +1.2±1.7 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.

Felix Auger Aliassime

Favour

ShotEdgeOwnTheirs
BH to their forehand · rally+2.6±3.6−0.8+3.4
FH to their forehand · rally+2.3±2.9−0.8+3.1
FH to their backhand · serve +1+1.9±3.0−0.2+2.1
BH to the middle · return+1.2±2.1+0.6+0.7
BH to the middle · rally+0.7±1.8−0.1+0.8
FH to the middle · return−0.3±2.1−0.4±0.0

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−1.3±2.1−2.0+0.7
FH to the middle · rally−1.0±2.0−1.1+0.2
BH to their backhand · return−0.7±2.6−1.1+0.4
FH to their backhand · rally−0.4±2.5−1.0+0.6
FH to the middle · return−0.3±2.1−0.4±0.0

J J Wolf

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+0.5±2.6−0.2+0.7
BH to their backhand · rally+0.4±2.1−0.4+0.8
BH to the middle · return−0.4±1.9−0.5+0.1
BH to the middle · rally−0.4±1.8−1.2+0.8
FH to the middle · return−1.1±2.3−0.6−0.5
FH to their backhand · rally−1.2±2.4−0.8−0.4

Avoid

ShotEdgeOwnTheirs
BH to their backhand · return−3.7±2.6−2.4−1.2
FH to their forehand · serve +1−3.4±3.3−4.1+0.7
FH to the middle · rally−2.2±2.0−2.5+0.4
FH to their backhand · serve +1−1.9±2.9−1.1−0.8
FH to their backhand · rally−1.2±2.4−0.8−0.4

Against J J Wolf-like opponents

Felix Auger Aliassime vMatchesServe pts wonReturn pts won
All charted opponents–65.8%34.5%
Players most similar to J J Wolf9 68.0%34.6%

Similar by tactical fingerprint: Stefanos Tsitsipas, Andrey Rublev, 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.