RallyIQ

Game plan

Lukas Rosol v Zizou Bergs

Every number combines what Lukas Rosol does well with what Zizou Bergs 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 67%90%: 34%–90% · best of 5: 70%
Serve points won 70.0% / 66.4% Lukas / Zizou · tour 65.7%
Strengths only, no similarity priors 67%serve 70.0% / 66.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerLukasZizou
Direction choice−0.27 ±0.17
better than 7%
−0.08 ±0.07
better than 36%
Shot selection−0.18 ±0.18
better than 31%
+0.25 ±0.19
better than 75%
Execution−1.65 ±0.79
better than 7%
−1.10 ±0.72
better than 22%
Points left on the table2.97 ±0.26
lower than 21%
2.64 ±0.13
lower than 46%

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 ZizouMatchupOptimal
Wide49%66%73%66.0%±7.750%
Body18%63%63%63.0%±13.25% ▼
T32%78%73%75.9%±8.045% ▲

Optimal v Zizou Bergs: +0.8±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLukas winsv ZizouMatchupOptimal
Wide42%75%74%75.8%±7.655% ▲
Body20%53%66%56.3%±13.86% ▼
T38%68%77%73.4%±8.039%

Optimal v Zizou Bergs: +1.0±1.0 per 100 first serves (faults included) over the current mix. Serving wide every time would read +4.7 per 100 first serves in before the returner adjusts.

Zizou Bergs serving

Deuce court

1st serveNowZizou winsv LukasMatchupOptimal
Wide45%75%80%82.2%±6.543% ▼
Body11%68%67%71.2%±10.40% ▼
T44%76%77%78.0%±7.057% ▲

Optimal v Lukas Rosol: +1.0±0.9 per 100 first serves (faults included) over the current mix. Serving wide every time would read +3.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowZizou winsv LukasMatchupOptimal
Wide48%72%78%76.7%±7.344% ▼
Body9%67%66%69.5%±12.00% ▼
T43%65%71%64.7%±9.356% ▲

Optimal v Lukas Rosol: +0.4±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +5.8 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 ZizouValue
FH through the middle56%+4.3−2.4−2.1−0.3±2.9
FH crosscourt35%+5.5±0.0+3.4+8.9±4.4
FH down the line9%+1.7+0.4±0.0+2.0±3.9

Lean FH crosscourt: +5.8±3.3 per 100 returns v the current mix (94 returns charted)

1st serve to the backhand

ReturnNowTourOwnv ZizouValue
BH through the middle29%+6.4−1.1−2.0+3.3±2.7
BH crosscourt20%+8.8−0.7+1.7+9.8±3.4
BH slice down the line14%−8.4+2.4−0.4−6.4±3.1
BH slice through the middle12%−4.2−1.8−1.3−7.3±2.3
BH down the line9%+4.2−0.2+0.9+4.9±4.1

Lean BH crosscourt: +7.3±2.9 per 100 returns v the current mix (114 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv ZizouValue
BH crosscourt39%+1.0+1.1+0.1+2.2±3.1
BH through the middle35%−2.9−2.5−1.4−6.8±2.3
BH down the line17%−0.2+1.7±0.0+1.5±4.3
FH through the middle9%−2.9−1.3−0.1−4.3±1.9

Lean BH crosscourt: +3.9±2.2 per 100 returns v the current mix (54 returns charted)

Zizou Bergs returning

1st serve to the forehand

ReturnNowTourOwnv LukasValue
FH through the middle51%+4.3+0.1−1.2+3.2±2.8
FH down the line26%+1.7−3.0+0.1−1.2±4.2
FH crosscourt13%+5.5+2.7−2.0+6.2±4.3
FH slice through the middle6%−4.2−0.1+0.1−4.2±2.2
FH slice crosscourt3%−4.3−0.5±0.0−4.8±1.5

Lean FH crosscourt: +4.5±4.2 per 100 returns v the current mix (344 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LukasValue
BH through the middle40%+6.4−0.9+0.6+6.1±2.8
BH crosscourt21%+8.8−1.6+0.1+7.2±3.5
BH slice through the middle18%−4.2−1.0−0.9−6.2±2.5
BH down the line8%+4.2+0.3−3.0+1.5±4.2
BH slice down the line7%−8.4+0.1−0.1−8.3±3.1

Lean BH crosscourt: +4.7±3.1 per 100 returns v the current mix (306 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LukasValue
FH through the middle57%−3.5−1.7−0.6−5.7±2.9
FH down the line29%−1.8−0.2−2.4−4.4±4.4
FH crosscourt14%−0.2+0.6−0.3±0.0±3.8

Lean FH crosscourt: +4.5±3.9 per 100 returns v the current mix (124 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv LukasValue
BH crosscourt45%+1.0−1.7+1.3+0.6±3.2
BH through the middle40%−2.9−3.3+1.0−5.2±2.6
BH down the line5%−0.2+1.0−1.9−1.0±4.1
BH slice through the middle4%−11.3−0.7−0.2−12.2±1.8
FH through the middle4%−2.9+0.3−0.6−3.2±2.1

Lean BH crosscourt: +3.1±2.1 per 100 returns v the current mix (193 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+4.0±5.8+1.0+3.1
FH to their forehand · rally+1.8±5.2+0.4+1.3
BH to their backhand · return+1.6±4.4+0.4+1.2
FH to their backhand · serve +1+0.9±5.5+0.2+0.7
FH to their backhand · return +1+0.9±6.5−3.2+4.1
FH to the middle · serve +1+0.4±3.9−2.2+2.6

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−7.5±4.1−6.3−1.2
BH to their backhand · rally−6.2±4.2−6.5+0.3
BH to the middle · return−6.2±3.8−4.9−1.3
FH to their backhand · rally−5.7±5.0−1.0−4.7
BH to their backhand · serve +1−5.6±4.2−4.5−1.1

Zizou Bergs

Favour

ShotEdgeOwnTheirs
BH to their forehand · rally+4.9±6.3+2.7+2.2
FH to their backhand · serve +1+3.5±5.5−0.8+4.3
FH to their forehand · serve +1+2.6±6.0−0.4+3.0
FH to the middle · rally+2.1±3.8+1.6+0.5
FH to the middle · serve +1+1.0±4.0−0.6+1.6
BH to their backhand · return+1.0±5.2+0.2+0.7

Avoid

ShotEdgeOwnTheirs
BH slice to their backhand · rally−3.4±3.8−2.7−0.7
BH to the middle · rally−2.8±2.6−0.9−2.0
FH to the middle · return−2.2±3.9+0.3−2.4
FH to their forehand · rally−1.2±5.3−2.2+0.9
BH to their backhand · rally−0.9±3.6−1.0+0.1

Against Zizou Bergs-like opponents

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

Similar by tactical fingerprint: Stefanos Tsitsipas, Ben Shelton, Tallon Griekspoor, Zhizhen Zhang, Felix Auger Aliassime, Alexei Popyrin, Roman Safiullin, Otto Virtanen, Lucas Pouille, Sam Querrey. When two players have rarely met, their records against these lookalikes fill the gap.