RallyIQ

Game plan

Lukas Rosol v John Isner

Every number combines what Lukas Rosol does well with what John Isner 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 47%90%: 26%–68% · best of 5: 46%
Serve points won 74.2% / 75.0% Lukas / John · tour 65.7%
Strengths only, no similarity priors 47%serve 74.2% / 75.0%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerLukasJohn
Direction choice−0.27 ±0.17
better than 7%
−0.13 ±0.05
better than 25%
Shot selection−0.18 ±0.18
better than 31%
+0.62 ±0.09
better than 96%
Execution−1.65 ±0.79
better than 7%
−0.90 ±0.33
better than 28%
Points left on the table2.97 ±0.26
lower than 21%
2.98 ±0.11
lower than 20%

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 JohnMatchupOptimal
Wide49%66%79%72.4%±5.850%
Body18%63%76%75.3%±7.85% ▼
T32%78%84%86.3%±4.645% ▲

Optimal v John Isner: +1.0±0.8 per 100 first serves (faults included) over the current mix. Serving T every time would read +8.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLukas winsv JohnMatchupOptimal
Wide42%75%83%84.9%±4.655% ▲
Body20%53%70%60.9%±10.06% ▼
T38%68%80%77.0%±6.139%

Optimal v John Isner: +1.4±0.8 per 100 first serves (faults included) over the current mix. Serving wide every time would read +7.7 per 100 first serves in before the returner adjusts.

John Isner serving

Deuce court

1st serveNowJohn winsv LukasMatchupOptimal
Wide52%78%80%84.8%±5.047% ▼
Body9%61%67%64.5%±9.20% ▼
T39%78%77%79.8%±5.553% ▲

Optimal v Lukas Rosol: +1.0±0.7 per 100 first serves (faults included) over the current mix. Serving wide every time would read +3.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJohn winsv LukasMatchupOptimal
Wide47%80%78%83.8%±4.860% ▲
Body6%66%66%69.0%±9.80% ▼
T47%79%71%78.4%±6.040% ▼

Optimal v Lukas Rosol: +0.9±0.6 per 100 first serves (faults included) over the current mix. Serving wide every time would read +3.4 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 JohnValue
FH through the middle56%+4.3−2.4−1.7+0.1±2.4
FH crosscourt35%+5.5±0.0−1.7+3.8±3.8
FH down the line9%+1.7+0.4−0.6+1.5±3.2

Lean FH crosscourt: +2.3±2.8 per 100 returns v the current mix (94 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JohnValue
BH through the middle29%+6.4−1.1−2.2+3.2±2.3
BH crosscourt20%+8.8−0.7−0.1+8.0±3.0
BH slice down the line14%−8.4+2.4−0.5−6.5±3.2
BH slice through the middle12%−4.2−1.8−2.2−8.2±1.9
BH down the line9%+4.2−0.2+1.7+5.7±3.8

Lean BH crosscourt: +6.2±2.6 per 100 returns v the current mix (114 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JohnValue
BH crosscourt39%+1.0+1.1−1.3+0.8±2.6
BH through the middle35%−2.9−2.5−3.1−8.5±1.9
BH down the line17%−0.2+1.7−3.8−2.3±4.0
FH through the middle9%−2.9−1.3−1.7−5.9±1.5

Lean BH crosscourt: +4.4±1.9 per 100 returns v the current mix (54 returns charted)

John Isner returning

1st serve to the forehand

ReturnNowTourOwnv LukasValue
FH through the middle47%+4.3−1.2−1.2+1.9±2.4
FH down the line31%+1.7−1.9+0.1−0.1±3.4
FH crosscourt11%+5.5+0.9−2.0+4.4±4.0
FH slice through the middle5%−4.2+2.2+0.1−1.9±2.3
FH slice down the line4%−4.3+0.6±0.0−3.6±2.3

Lean FH crosscourt: +3.3±3.9 per 100 returns v the current mix (1500 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv LukasValue
BH through the middle47%+6.4−3.2+0.6+3.8±2.3
BH crosscourt19%+8.8−2.4+0.1+6.4±3.0
BH down the line14%+4.2−1.8−3.0−0.6±3.8
BH slice through the middle9%−4.2−1.4−0.9−6.6±2.4
BH slice crosscourt7%+0.5−4.8−0.6−4.8±2.7

Lean BH crosscourt: +4.7±2.7 per 100 returns v the current mix (1608 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LukasValue
FH through the middle46%−3.5−2.6−0.6−6.6±2.7
FH down the line42%−1.8−4.5−2.4−8.7±4.1
FH crosscourt10%−0.2−5.4−0.3−6.0±4.1
FH slice through the middle2%−12.7−0.4±0.0−13.0±1.2

Lean FH crosscourt: +1.6±4.3 per 100 returns v the current mix (367 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv LukasValue
BH through the middle46%−2.9−2.8+1.0−4.8±2.1
BH crosscourt26%+1.0−3.3+1.3−1.0±2.9
BH down the line14%−0.2±0.0−1.9−2.1±4.4
FH inside-out7%+1.0+1.9−2.4+0.5±3.5
FH through the middle6%−2.9−2.5−0.6−5.9±2.5

Lean FH inside-out: +3.7±3.5 per 100 returns v the current mix (996 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 · serve +1+8.9±5.3+0.6+8.2
FH to their backhand · serve +1+5.6±5.0+0.2+5.4
FH to their forehand · rally+4.3±4.9+0.4+3.9
BH to their forehand · rally+3.5±6.2−2.4+6.0
FH to their backhand · rally+3.4±4.7−1.0+4.4
FH to their forehand · return−1.5±5.2+1.0−2.5

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−8.2±3.6−6.3−1.9
BH to the middle · return−7.9±3.4−4.9−3.0
FH to the middle · serve +1−4.9±3.7−2.2−2.7
FH to the middle · rally−4.9±3.6−4.1−0.8
FH to their backhand · return +1−4.8±6.3−3.2−1.6

John Isner

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+5.1±5.5+2.1+3.0
FH to their backhand · serve +1+3.3±4.9−1.0+4.3
BH to their forehand · rally−0.7±6.1−2.9+2.2
BH to the middle · rally−2.3±2.6−0.3−2.0
FH to the middle · serve +1−2.8±3.9−4.5+1.6
BH to the middle · return−3.0±3.3−3.4+0.4

Avoid

ShotEdgeOwnTheirs
BH slice to their backhand · rally−6.7±3.5−6.0−0.7
FH to their forehand · rally−5.0±5.1−5.9+0.9
BH slice to the middle · return−4.5±3.5−3.4−1.1
BH to their backhand · return−4.5±4.7−5.3+0.7
FH to the middle · rally−4.4±3.6−4.9+0.5

Against John Isner-like opponents

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

Similar by tactical fingerprint: Arthur Rinderknech, Felix Auger Aliassime, Alexei Popyrin, Giovanni Mpetshi Perricard, Reilly Opelka, Nicolas Jarry, Milos Raonic, Jeremy Chardy, Sam Querrey. When two players have rarely met, their records against these lookalikes fill the gap.