RallyIQ

Game plan

Lorenzo Musetti v Roberto Bautista Agut

Every number combines what Lorenzo Musetti does well with what Roberto Bautista Agut allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Lorenzo Musetti wins, best of 3 72%90%: 54%–85% · best of 5: 76%
Serve points won 62.7% / 58.2% Lorenzo / Roberto · tour 61.3%
Strengths only, no similarity priors 76%serve 64.2% / 58.6%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Lorenzo Musetti's record against Roberto Bautista Agut's tactical lookalikes and in their charted head-to-heads (lookalikes: −3.2 on serve, +1.0 on return vs expectation (2792 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

CareerLorenzoRoberto
Direction choice−0.02 ±0.04
better than 50%
+0.03 ±0.06
better than 65%
Shot selection−0.57 ±0.10
better than 9%
+0.08 ±0.08
better than 62%
Execution+0.48 ±0.22
better than 83%
+1.23 ±0.28
better than 98%
Points left on the table2.74 ±0.06
lower than 35%
2.30 ±0.09
lower than 85%

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.

Structural compatibility

Expected edge per 100 rally shots from style alone: Lorenzo Musetti +1.83, Roberto Bautista Agut +0.38. Each player's shot mix weighted by their own skill with each shot and by how much the other gives up against it. This is why some rankings gaps don't hold in a given matchup.

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.

Lorenzo Musetti serving

Deuce court

1st serveNowLorenzo winsv RobertoMatchupOptimal
Wide41%70%74%70.9%±3.138% ▼
Body9%64%60%60.7%±6.80% ▼
T49%72%76%73.2%±3.162% ▲

Optimal v Roberto Bautista Agut: +0.7±0.5 per 100 first serves (faults included) over the current mix. Serving T every time would read +2.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLorenzo winsv RobertoMatchupOptimal
Wide55%69%77%73.5%±2.968% ▲
Body8%61%53%51.4%±8.00% ▼
T37%69%72%68.8%±3.632% ▼

Optimal v Roberto Bautista Agut: +0.8±0.5 per 100 first serves (faults included) over the current mix. Serving wide every time would read +3.5 per 100 first serves in before the returner adjusts.

Roberto Bautista Agut serving

Deuce court

1st serveNowRoberto winsv LorenzoMatchupOptimal
Wide45%70%72%69.1%±3.055% ▲
Body9%64%61%61.7%±6.70% ▼
T47%72%71%68.5%±3.345% ▼

Optimal v Lorenzo Musetti: +0.3±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +0.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRoberto winsv LorenzoMatchupOptimal
Wide56%70%68%64.3%±3.351% ▼
Body9%61%63%60.0%±7.40% ▼
T36%72%71%71.3%±3.449% ▲

Optimal v Lorenzo Musetti: +0.8±0.5 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.8 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.

Lorenzo Musetti returning

1st serve to the forehand

ReturnNowTourOwnv RobertoValue
FH through the middle40%+4.3−0.5+2.6+6.4±1.5
FH down the line24%+1.7−1.4+4.3+4.6±2.9
FH slice through the middle15%−4.2−0.4+2.1−2.5±1.8
FH crosscourt10%+5.5+2.3−1.2+6.7±3.2
FH slice down the line8%−4.3+0.2−0.1−4.2±2.9

Lean FH crosscourt: +3.1±3.0 per 100 returns v the current mix (2257 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RobertoValue
BH slice through the middle27%−4.2+1.4+3.1+0.3±1.6
BH through the middle25%+6.4+1.1+1.2+8.8±1.4
BH crosscourt20%+8.8+1.4+2.2+12.4±2.1
BH slice crosscourt11%+0.5−0.6+1.1+0.9±2.5
BH down the line9%+4.2±0.0+1.3+5.6±3.8

Lean BH crosscourt: +7.6±1.8 per 100 returns v the current mix (2587 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv RobertoValue
FH through the middle47%−3.5+1.1−0.4−2.8±2.1
FH down the line25%−1.8−1.0+1.5−1.3±4.1
FH crosscourt23%−0.2−1.2−1.4−2.8±4.0
FH slice through the middle3%−12.7−0.7±0.0−13.4±1.5
FH slice down the line2%−9.4+1.2−0.1−8.4±2.1

Lean FH down the line: +1.6±3.4 per 100 returns v the current mix (600 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv RobertoValue
BH through the middle33%−2.9+1.0+2.3+0.4±1.4
BH crosscourt27%+1.0+1.4+0.2+2.6±1.9
BH down the line14%−0.2−1.8+2.5+0.6±4.0
FH through the middle10%−2.9+1.2−0.4−2.0±1.9
FH inside-out6%+1.0−1.1+1.5+1.3±3.4

Lean BH crosscourt: +2.7±1.6 per 100 returns v the current mix (1827 returns charted)

Roberto Bautista Agut returning

1st serve to the forehand

ReturnNowTourOwnv LorenzoValue
FH through the middle47%+4.3+2.4+0.8+7.5±1.5
FH down the line19%+1.7+2.4−2.1+2.0±3.0
FH crosscourt15%+5.5+1.8+0.4+7.7±3.3
FH slice through the middle13%−4.2+0.4+0.4−3.4±2.0
FH slice crosscourt3%−4.3+0.3−0.2−4.3±2.8

Lean FH crosscourt: +3.3±3.0 per 100 returns v the current mix (1224 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LorenzoValue
BH through the middle42%+6.4+2.7+0.5+9.6±1.4
BH crosscourt20%+8.8+2.4−0.9+10.3±2.2
BH slice through the middle17%−4.2−0.1−0.8−5.1±2.0
BH down the line11%+4.2+4.9−0.7+8.5±3.7
BH slice crosscourt6%+0.5−1.2−1.0−1.6±2.8

Lean BH crosscourt: +4.6±1.9 per 100 returns v the current mix (1218 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LorenzoValue
FH through the middle48%−3.5+0.4−0.8−3.9±2.1
FH crosscourt24%−0.2+0.7+1.1+1.6±3.8
FH down the line24%−1.8+0.9−0.5−1.4±3.9
FH slice through the middle4%−12.7±0.0−1.7−14.3±2.0

Lean FH crosscourt: +3.9±3.2 per 100 returns v the current mix (289 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv LorenzoValue
BH through the middle48%−2.9+0.6+0.2−2.1±1.4
BH crosscourt33%+1.0+1.7−0.7+2.0±1.9
BH down the line12%−0.2+0.8−0.8−0.2±4.3
FH through the middle3%−2.9−0.4−0.8−4.0±1.9
FH inside-out2%+1.0±0.0−0.5+0.5±2.9

Lean BH crosscourt: +2.5±1.5 per 100 returns v the current mix (961 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 clay. Each player's clay record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Lorenzo Musetti

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+5.8±3.2+2.1+3.7
BH drop shot to their forehand · rally+5.7±7.3−1.9+7.7
FH volley to their backhand · rally+5.4±7.3−1.6+7.0
FH to their forehand · return+4.2±4.2+1.5+2.7
FH to the middle · rally+4.0±1.7+1.4+2.5
Smash to their forehand · rally+3.8±6.2+1.1+2.8

Avoid

ShotEdgeOwnTheirs
BH to their forehand · return +1−5.3±5.0−3.5−1.8
FH slice to their forehand · rally−5.1±5.5−3.0−2.0
BH volley to their backhand · rally−4.8±7.5−6.1+1.3
BH to their forehand · return−3.1±4.6−1.8−1.3
BH volley to their forehand · rally−2.9±7.2−1.6−1.3

Roberto Bautista Agut

Favour

ShotEdgeOwnTheirs
FH drop shot to their backhand · rally+6.0±6.9+4.2+1.9
FH volley to their forehand · rally+5.5±7.2+3.0+2.5
FH slice to their forehand · rally+4.3±5.3+5.6−1.3
BH to their backhand · return+4.0±2.2+3.4+0.6
FH to the middle · return+3.7±2.1+2.5+1.2
FH to the middle · serve +1+2.5±2.5+2.9−0.4

Avoid

ShotEdgeOwnTheirs
FH volley to their backhand · rally−6.7±7.1−0.5−6.1
BH slice to their forehand · return +1−4.6±4.8+1.0−5.6
FH slice to the middle · rally−4.0±3.5−2.2−1.8
BH to their forehand · return +1−3.8±5.4−0.2−3.6
BH slice to their forehand · rally−3.8±4.4−1.1−2.6

Against Roberto Bautista Agut-like opponents

Lorenzo Musetti vMatchesServe pts wonReturn pts won
All charted opponents–63.0%37.7%
Players most similar to Roberto Bautista Agut16 57.3%38.0%

Similar by tactical fingerprint: Casper Ruud, Brandon Nakashima, Gael Monfils, Mariano Navone, Novak Djokovic, Karen Khachanov, Pablo Carreno Busta, Francisco Cerundolo, Roberto Carballes Baena, Bernabe Zapata Miralles. When two players have rarely met, their records against these lookalikes fill the gap.