RallyIQ

Game plan

Nicolas Lapentti v Arthur Cazaux

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

Forecast

Nicolas Lapentti wins, best of 3 41%90%: 14%–74% · best of 5: 39%
Serve points won 62.5% / 64.3% Nicolas / Arthur · tour 63.4%
Strengths only, no similarity priors 41%serve 62.5% / 64.3%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerNicolasArthur
Direction choice−0.23 ±0.09
better than 10%
−0.18 ±0.16
better than 17%
Shot selection−0.67 ±0.44
better than 6%
−0.06 ±0.30
better than 47%
Execution−0.88 ±1.05
better than 29%
+0.04 ±0.45
better than 72%

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.

Nicolas Lapentti serving

Deuce court

1st serveNowNicolas winsv ArthurMatchupOptimal
Wide30%71%73%71.0%±10.743% ▲
Body8%52%66%55.2%±17.30% ▼
T62%73%79%76.5%±9.157% ▼

Optimal v Arthur Cazaux: +0.3±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowNicolas winsv ArthurMatchupOptimal
Wide43%68%75%71.1%±10.143%
Body13%64%65%65.8%±15.80% ▼
T44%59%80%68.5%±10.457% ▲

Optimal v Arthur Cazaux: +0.5±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.8 per 100 first serves in before the returner adjusts.

Arthur Cazaux serving

Deuce court

1st serveNowArthur winsv NicolasMatchupOptimal
Wide46%72%79%78.7%±8.340% ▼
Body5%60%64%60.3%±18.20% ▼
T49%78%76%79.3%±8.960% ▲

Optimal v Nicolas Lapentti: +0.4±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowArthur winsv NicolasMatchupOptimal
Wide54%72%68%67.4%±10.967% ▲
Body3%69%64%69.9%±17.33%
T43%71%69%68.5%±11.230% ▼

Optimal v Nicolas Lapentti: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +2.0 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.

Nicolas Lapentti returning

1st serve to the forehand

ReturnNowTourOwnv ArthurValue
FH down the line27%+1.7−0.1−1.8−0.2±4.3
FH slice through the middle26%−4.2+0.6+0.7−2.9±2.2
FH through the middle24%+4.3−3.0−2.8−1.6±2.9
FH crosscourt13%+5.5+0.1+1.5+7.1±3.9
FH slice down the line10%−4.3+1.3−1.0−3.9±2.3

Lean FH down the line: +0.4±3.3 per 100 returns v the current mix (84 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv ArthurValue
BH through the middle25%+6.4−1.0−2.0+3.5±2.6
BH slice through the middle25%−4.2−1.0+0.1−5.0±2.2
BH down the line15%+4.2+0.6−1.2+3.7±4.0
BH crosscourt14%+8.8−0.4+1.6+10.0±3.1
BH slice crosscourt14%+0.5−0.4−2.8−2.7±2.4

Lean BH through the middle: +2.9±2.2 per 100 returns v the current mix (73 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv ArthurValue
BH through the middle35%−2.9+0.5−0.2−2.6±2.4
BH crosscourt28%+1.0+1.2+0.3+2.6±3.0
FH through the middle17%−2.9±0.0−0.1−3.0±2.2
FH inside-out12%+1.0+0.4+1.0+2.4±3.1
BH down the line8%−0.2−2.2+0.2−2.3±3.9

Lean BH crosscourt: +3.2±2.4 per 100 returns v the current mix (60 returns charted)

Arthur Cazaux returning

1st serve to the forehand

ReturnNowTourOwnv NicolasValue
FH through the middle43%+4.3±0.0−0.1+4.1±3.0
FH down the line28%+1.7−3.8+1.4−0.7±4.3
FH slice through the middle14%−4.2−0.9±0.0−5.1±1.6
FH crosscourt9%+5.5−3.4−2.0+0.1±4.2
FH slice down the line5%−4.3+0.5±0.0−3.7±1.8

Lean FH through the middle: +3.5±2.1 per 100 returns v the current mix (243 returns charted)

1st serve to the backhand

ReturnNowTourOwnv NicolasValue
BH through the middle41%+6.4+1.0−0.2+7.2±2.8
BH crosscourt24%+8.8−0.7+0.9+8.9±3.4
BH down the line14%+4.2−2.9+1.8+3.1±4.3
BH slice through the middle12%−4.2−1.6+0.5−5.3±2.4
BH slice crosscourt6%+0.5−2.1+0.6−1.0±2.3

Lean BH crosscourt: +4.5±2.9 per 100 returns v the current mix (204 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv NicolasValue
FH through the middle53%−3.5+1.3+0.1−2.1±2.8
FH down the line37%−1.8+0.1−1.1−2.8±4.3
FH crosscourt10%−0.2−2.8+1.3−1.7±3.5

Lean FH through the middle: +0.2±2.1 per 100 returns v the current mix (60 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv NicolasValue
BH through the middle53%−2.9+1.2+0.7−1.0±2.4
BH crosscourt34%+1.0−1.3+1.2+0.9±3.3
BH down the line8%−0.2−1.5+0.5−1.2±4.1
FH through the middle5%−2.9+0.6+0.1−2.1±2.1

Lean BH crosscourt: +1.3±2.5 per 100 returns v the current mix (172 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.

Nicolas Lapentti

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+4.3±4.1+1.6+2.7
FH to their forehand · rally+2.1±3.3+1.7+0.4
FH to their backhand · rally+1.3±3.1−1.5+2.8
FH to the middle · rally+1.3±2.4+0.2+1.1
FH to their backhand · serve +1+1.2±3.8−0.6+1.7
BH to their backhand · rally+0.3±2.8±0.0+0.4

Avoid

ShotEdgeOwnTheirs
BH to the middle · rally−1.9±2.2−1.2−0.7
BH to their backhand · rally+0.3±2.8±0.0+0.4
FH to their backhand · serve +1+1.2±3.8−0.6+1.7
FH to the middle · rally+1.3±2.4+0.2+1.1
FH to their backhand · rally+1.3±3.1−1.5+2.8

Arthur Cazaux

Favour

ShotEdgeOwnTheirs
BH to their backhand · rally+2.4±2.4+2.4±0.0
FH to their forehand · rally+1.4±3.3+1.4±0.0
FH to the middle · return+0.5±2.8+0.7−0.2
FH to their backhand · rally−0.6±3.2−1.4+0.7

Avoid

ShotEdgeOwnTheirs
FH to their backhand · rally−0.6±3.2−1.4+0.7
FH to the middle · return+0.5±2.8+0.7−0.2
FH to their forehand · rally+1.4±3.3+1.4±0.0
BH to their backhand · rally+2.4±2.4+2.4±0.0

Against Arthur Cazaux-like opponents

Nicolas Lapentti vMatchesServe pts wonReturn pts won
All charted opponents–53.5%31.2%

Similar by tactical fingerprint: Gael Monfils, Jakub Mensik, Jack Draper, Marcos Giron, Taylor Fritz, Nuno Borges, Rinky Hijikata, Miomir Kecmanovic, Gregoire Barrere, Filip Krajinovic. When two players have rarely met, their records against these lookalikes fill the gap.