RallyIQ

Game plan

Lukas Rosol v Arthur Fils

Every number combines what Lukas Rosol does well with what Arthur Fils allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Lukas Rosol wins, best of 3 48%90%: 22%–75% · best of 5: 48%
Serve points won 69.8% / 70.2% Lukas / Arthur · tour 65.7%
Strengths only, no similarity priors 48%serve 69.8% / 70.2%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Lukas Rosol's record against Arthur Fils'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

CareerLukasArthur
Direction choice−0.27 ±0.17
better than 7%
+0.18 ±0.06
better than 92%
Shot selection−0.18 ±0.18
better than 31%
−0.04 ±0.13
better than 48%
Execution−1.65 ±0.79
better than 7%
+0.20 ±0.45
better than 75%
Points left on the table2.97 ±0.26
lower than 21%
2.31 ±0.10
lower than 83%

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.

Lukas Rosol serving

Deuce court

1st serveNowLukas winsv ArthurMatchupOptimal
Wide49%66%72%65.0%±6.650%
Body18%63%67%66.2%±10.55% ▼
T32%78%73%75.6%±7.245% ▲

Optimal v Arthur Fils: +0.3±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +6.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLukas winsv ArthurMatchupOptimal
Wide42%75%71%73.1%±7.055% ▲
Body20%53%66%56.4%±11.96% ▼
T38%68%71%66.1%±7.839%

Optimal v Arthur Fils: +0.8±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +5.9 per 100 first serves in before the returner adjusts.

Arthur Fils serving

Deuce court

1st serveNowArthur winsv LukasMatchupOptimal
Wide56%73%80%80.5%±6.148% ▼
Body5%59%67%62.2%±10.80% ▼
T39%79%77%80.6%±5.552% ▲

Optimal v Lukas Rosol: +0.8±0.7 per 100 first serves (faults included) over the current mix. Serving T every time would read +1.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowArthur winsv LukasMatchupOptimal
Wide53%74%78%78.2%±6.145% ▼
Body5%57%66%60.5%±11.80% ▼
T42%73%71%72.9%±7.255% ▲

Optimal v Lukas Rosol: +0.5±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.1 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.

Lukas Rosol returning

1st serve to the forehand

ReturnNowTourOwnv ArthurValue
FH through the middle56%+4.3−2.4+3.0+4.8±2.5
FH crosscourt35%+5.5±0.0+3.8+9.3±3.9
FH down the line9%+1.7+0.4+0.9+3.0±3.3

Lean FH crosscourt: +3.1±2.9 per 100 returns v the current mix (94 returns charted)

1st serve to the backhand

ReturnNowTourOwnv ArthurValue
BH through the middle29%+6.4−1.1+3.4+8.8±2.4
BH crosscourt20%+8.8−0.7+2.7+10.8±2.9
BH slice down the line14%−8.4+2.4+1.4−4.6±3.2
BH slice through the middle12%−4.2−1.8+0.5−5.5±2.2
BH down the line9%+4.2−0.2−0.9+3.1±4.0

Lean BH crosscourt: +5.8±2.5 per 100 returns v the current mix (114 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv ArthurValue
BH crosscourt39%+1.0+1.1−2.1±0.0±2.5
BH through the middle35%−2.9−2.5−0.8−6.3±1.9
BH down the line17%−0.2+1.7+2.1+3.6±4.1
FH through the middle9%−2.9−1.3+0.9−3.2±1.6

Lean BH crosscourt: +1.9±1.8 per 100 returns v the current mix (54 returns charted)

Arthur Fils returning

1st serve to the forehand

ReturnNowTourOwnv LukasValue
FH through the middle39%+4.3+1.2−1.2+4.2±2.5
FH slice through the middle22%−4.2+0.6+0.1−3.5±2.1
FH crosscourt15%+5.5+6.2−2.0+9.7±4.0
FH down the line12%+1.7+0.4+0.1+2.2±4.0
FH slice crosscourt6%−4.3±0.0±0.0−4.4±2.0

Lean FH crosscourt: +7.5±3.7 per 100 returns v the current mix (963 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LukasValue
BH through the middle42%+6.4+1.3+0.6+8.2±2.4
BH crosscourt34%+8.8+2.4+0.1+11.3±3.0
BH down the line10%+4.2+2.6−3.0+3.8±4.2
BH slice through the middle9%−4.2−0.1−0.9−5.2±2.5
BH slice down the line3%−8.4−0.9−0.1−9.3±3.2

Lean BH crosscourt: +4.4±2.3 per 100 returns v the current mix (1115 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LukasValue
FH through the middle44%−3.5+1.7−0.6−2.3±2.8
FH crosscourt38%−0.2+0.2−0.3−0.4±4.0
FH down the line15%−1.8+1.5−2.4−2.7±4.4
FH slice through the middle3%−12.7+0.5±0.0−12.1±1.3

Lean FH crosscourt: +1.6±2.8 per 100 returns v the current mix (287 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv LukasValue
BH through the middle37%−2.9−2.7+1.0−4.6±2.2
BH crosscourt33%+1.0−0.7+1.3+1.6±2.8
FH through the middle12%−2.9+0.2−0.6−3.2±2.4
BH down the line7%−0.2+1.5−1.9−0.6±4.7
FH inside-in6%+0.6−2.9−0.3−2.7±4.1

Lean BH crosscourt: +3.6±2.1 per 100 returns v the current mix (914 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 on grass. Each player's grass record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Lukas Rosol

Favour

ShotEdgeOwnTheirs
FH to their forehand · return+4.3±5.3+1.0+3.3
FH to their forehand · rally+0.3±5.0+0.4−0.1
BH to their backhand · return−0.5±4.0+0.4−1.0
BH to their forehand · rally−1.5±6.1−2.4+0.9
BH to the middle · rally−1.6±3.2−2.2+0.6
FH to the middle · return−2.1±3.9−6.3+4.1

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−7.5±4.0−6.5−1.0
FH to their backhand · rally−7.4±4.8−1.0−6.5
FH to their backhand · return +1−6.3±6.3−3.2−3.1
FH to their backhand · serve +1−5.7±5.3+0.2−5.9
BH to their backhand · serve +1−4.7±3.9−4.5−0.3

Arthur Fils

Favour

ShotEdgeOwnTheirs
BH to their forehand · rally+6.3±6.0+4.0+2.2
FH to their forehand · serve +1+3.0±5.7±0.0+3.0
FH to their backhand · serve +1+2.1±5.3−2.2+4.3
BH to their backhand · rally+1.9±3.3+1.8+0.1
BH to their backhand · return+1.1±4.9+0.4+0.7
FH to the middle · serve +1+0.9±3.9−0.8+1.6

Avoid

ShotEdgeOwnTheirs
FH to their backhand · rally−3.9±4.8−4.9+1.1
BH to the middle · rally−3.6±2.6−1.6−2.0
BH slice to the middle · rally−3.3±3.2−2.5−0.8
FH to the middle · return−1.3±3.8+1.1−2.4
BH slice to their backhand · rally−0.6±3.6+0.1−0.7

Against Arthur Fils-like opponents

Lukas Rosol vMatchesServe pts wonReturn pts won
All charted opponents–60.1%30.0%

Similar by tactical fingerprint: Tallon Griekspoor, Tommy Paul, Felix Auger Aliassime, Alexander Shevchenko, Zizou Bergs, Marin Cilic, Roman Safiullin, Lloyd Harris, Thomaz Bellucci, Leonardo Mayer. When two players have rarely met, their records against these lookalikes fill the gap.