RallyIQ

Game plan

Andrei Cherkasov v Roberto Bautista Agut

Every number combines what Andrei Cherkasov 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

Andrei Cherkasov wins, best of 3 21%90%: 5%–50% · best of 5: 16%
Serve points won 61.8% / 68.3% Andrei / Roberto · tour 65.7%
Strengths only, no similarity priors 21%serve 61.8% / 68.3%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Andrei Cherkasov's record against Roberto Bautista Agut'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.

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.

Andrei Cherkasov serving

Deuce court

1st serveNowAndrei winsv RobertoMatchupOptimal
Wide54%63%74%64.6%±8.867% ▲
Body11%63%60%60.3%±13.90% ▼
T34%66%76%66.6%±11.233% ▼

Optimal v Roberto Bautista Agut: +0.8±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAndrei winsv RobertoMatchupOptimal
Wide30%69%77%73.8%±10.830%
Body20%57%53%47.3%±13.77% ▼
T50%66%72%66.3%±9.463% ▲

Optimal v Roberto Bautista Agut: +1.0±1.0 per 100 first serves (faults included) over the current mix. Serving wide every time would read +9.1 per 100 first serves in before the returner adjusts.

Roberto Bautista Agut serving

Deuce court

1st serveNowRoberto winsv AndreiMatchupOptimal
Wide45%70%69%66.0%±9.258% ▲
Body9%64%59%59.0%±13.70% ▼
T47%72%67%64.0%±12.142% ▼

Optimal v Andrei Cherkasov: +0.4±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.5 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRoberto winsv AndreiMatchupOptimal
Wide56%70%72%69.3%±9.551% ▼
Body9%61%65%63.0%±14.60% ▼
T36%72%72%72.0%±11.049% ▲

Optimal v Andrei Cherkasov: +0.6±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.3 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.

Andrei Cherkasov returning

1st serve to the forehand

ReturnNowTourOwnv RobertoValue
FH down the line62%+1.7+4.9+4.3+10.9±3.9
FH through the middle30%+4.3−0.4+2.6+6.5±2.2
FH crosscourt8%+5.5−1.0−1.2+3.3±2.8

Lean FH down the line: +2.0±1.7 per 100 returns v the current mix (60 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RobertoValue
BH down the line46%+4.2+0.6+1.3+6.2±4.2
BH through the middle40%+6.4+0.8+1.2+8.5±2.1
BH crosscourt14%+8.8+0.4+2.2+11.5±2.3

Lean BH through the middle: +0.6±2.3 per 100 returns v the current mix (50 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv RobertoValue
BH through the middle52%−2.9+2.2+2.3+1.7±2.1
BH down the line28%−0.2+1.1+2.5+3.5±4.4
BH crosscourt12%+1.0−0.7+0.2+0.5±2.1
FH through the middle8%−2.9+0.4−0.4−2.9±1.6

Lean BH down the line: +1.8±3.4 per 100 returns v the current mix (65 returns charted, inside the 90% margin)

Roberto Bautista Agut returning

1st serve to the forehand

ReturnNowTourOwnv AndreiValue
FH through the middle47%+4.3+2.4−0.3+6.4±2.5
FH down the line19%+1.7+2.4+0.9+5.0±4.0
FH crosscourt15%+5.5+1.8+2.3+9.5±3.5
FH slice through the middle13%−4.2+0.4±0.0−3.8±1.4
FH slice crosscourt3%−4.3+0.3±0.0−4.1±2.0

Lean FH crosscourt: +4.9±3.3 per 100 returns v the current mix (1224 returns charted)

1st serve to the backhand

ReturnNowTourOwnv AndreiValue
BH through the middle42%+6.4+2.7+0.8+9.9±2.3
BH crosscourt20%+8.8+2.4+0.3+11.5±3.1
BH slice through the middle17%−4.2−0.1+1.2−3.1±1.9
BH down the line11%+4.2+4.9+2.6+11.8±3.8
BH slice crosscourt6%+0.5−1.2±0.0−0.7±2.1

Lean BH down the line: +5.0±3.6 per 100 returns v the current mix (1218 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv AndreiValue
FH through the middle48%−3.5+0.4+1.7−1.4±2.5
FH crosscourt24%−0.2+0.7+1.5+2.0±3.8
FH down the line24%−1.8+0.9+0.4−0.5±4.5
FH slice through the middle4%−12.7±0.0±0.0−12.7±1.3

Lean FH crosscourt: +2.8±3.3 per 100 returns v the current mix (289 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv AndreiValue
BH through the middle48%−2.9+0.6+0.8−1.5±1.7
BH crosscourt33%+1.0+1.7+1.7+4.3±2.3
BH down the line12%−0.2+0.8−0.6±0.0±4.0
FH through the middle3%−2.9−0.4+1.7−1.5±2.2
FH inside-out2%+1.0±0.0+0.4+1.3±3.4

Lean BH crosscourt: +3.7±1.8 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 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.

Andrei Cherkasov

Favour

ShotEdgeOwnTheirs
BH to their forehand · rally+4.9±4.4+3.2+1.7
BH to the middle · return+3.6±2.7+1.7+1.9
FH to their backhand · rally+1.4±3.3−0.5+1.8
BH to the middle · rally+0.6±2.3+1.0−0.4
FH to their forehand · rally−0.1±3.6−2.5+2.4
BH to their backhand · rally−0.2±2.8−1.3+1.1

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−0.2±2.8−1.3+1.1
FH to their forehand · rally−0.1±3.6−2.5+2.4
BH to the middle · rally+0.6±2.3+1.0−0.4
FH to their backhand · rally+1.4±3.3−0.5+1.8
BH to the middle · return+3.6±2.7+1.7+1.9

Roberto Bautista Agut

Favour

ShotEdgeOwnTheirs
FH to their backhand · rally+5.3±3.3+2.6+2.7
FH to their forehand · rally+2.4±3.3+3.3−0.9
BH to their backhand · rally+0.2±2.7+0.2±0.0

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally+0.2±2.7+0.2±0.0
FH to their forehand · rally+2.4±3.3+3.3−0.9
FH to their backhand · rally+5.3±3.3+2.6+2.7

Against Roberto Bautista Agut-like opponents

Andrei Cherkasov vMatchesServe pts wonReturn pts won
All charted opponents–56.0%36.5%

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.