RallyIQ

Game plan

Elmer Moller v Roberto Bautista Agut

Every number combines what Elmer Moller 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

Elmer Moller wins, best of 3 25%90%: 7%–57% · best of 5: 20%
Serve points won 56.9% / 62.0% Elmer / Roberto · tour 61.3%
Strengths only, no similarity priors 25%serve 56.9% / 62.0%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

Head to head, per 100 shots

CareerElmerRoberto
Direction choice−0.11 ±0.21
better than 27%
+0.03 ±0.06
better than 65%
Shot selection−0.26 ±0.30
better than 27%
+0.08 ±0.08
better than 62%
Execution−1.20 ±0.33
better than 19%
+1.23 ±0.28
better than 98%

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.

Elmer Moller serving

Deuce court

1st serveNowElmer winsv RobertoMatchupOptimal
Wide39%71%74%71.7%±8.352% ▲
Body19%64%60%61.0%±12.56% ▼
T42%63%76%64.2%±9.142%

Optimal v Roberto Bautista Agut: +0.8±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +5.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowElmer winsv RobertoMatchupOptimal
Wide39%59%77%64.5%±8.840%
Body21%65%53%56.0%±12.77% ▼
T40%68%72%68.4%±8.953% ▲

Optimal v Roberto Bautista Agut: +1.0±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.1 per 100 first serves in before the returner adjusts.

Roberto Bautista Agut serving

Deuce court

1st serveNowRoberto winsv ElmerMatchupOptimal
Wide45%70%73%70.2%±7.958% ▲
Body9%64%64%64.6%±12.00% ▼
T47%72%77%74.6%±9.042% ▼

Optimal v Elmer Moller: +0.5±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRoberto winsv ElmerMatchupOptimal
Wide56%70%64%60.4%±9.051% ▼
Body9%61%62%59.5%±13.40% ▼
T36%72%73%72.6%±8.249% ▲

Optimal v Elmer Moller: +0.9±0.8 per 100 first serves (faults included) over the current mix. Serving T every time would read +7.9 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.

Elmer Moller returning

1st serve to the forehand

ReturnNowTourOwnv RobertoValue
FH through the middle39%+4.3+0.2+2.6+7.1±2.4
FH crosscourt20%+5.5−2.4−1.2+1.9±3.5
FH down the line20%+1.7+2.6+4.3+8.6±3.7
FH slice through the middle15%−4.2+0.3+2.1−1.9±2.0
FH slice down the line5%−4.3+0.2−0.1−4.2±2.6

Lean FH down the line: +4.2±3.2 per 100 returns v the current mix (93 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RobertoValue
BH crosscourt35%+8.8+2.2+2.2+13.2±2.8
BH through the middle28%+6.4+0.7+1.2+8.3±2.0
BH down the line18%+4.2−1.2+1.3+4.4±3.8
BH slice through the middle18%−4.2−0.7+3.1−1.8±1.9

Lean BH crosscourt: +5.8±2.1 per 100 returns v the current mix (60 returns charted)

Roberto Bautista Agut returning

1st serve to the forehand

ReturnNowTourOwnv ElmerValue
FH through the middle47%+4.3+2.4−3.1+3.6±2.5
FH down the line19%+1.7+2.4−0.6+3.5±3.6
FH crosscourt15%+5.5+1.8−0.4+6.9±3.9
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: +4.2±3.6 per 100 returns v the current mix (1224 returns charted)

1st serve to the backhand

ReturnNowTourOwnv ElmerValue
BH through the middle42%+6.4+2.7+1.0+10.1±2.3
BH crosscourt20%+8.8+2.4+1.4+12.6±3.1
BH slice through the middle17%−4.2−0.1−0.3−4.7±1.7
BH down the line11%+4.2+4.9+1.3+10.5±3.7
BH slice crosscourt6%+0.5−1.2±0.0−0.7±2.1

Lean BH crosscourt: +5.9±2.8 per 100 returns v the current mix (1218 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv ElmerValue
FH through the middle48%−3.5+0.4+0.6−2.5±2.7
FH crosscourt24%−0.2+0.7+1.0+1.5±4.1
FH down the line24%−1.8+0.9+0.4−0.5±4.3
FH slice through the middle4%−12.7±0.0±0.0−12.7±1.3

Lean FH crosscourt: +3.0±3.5 per 100 returns v the current mix (289 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv ElmerValue
BH through the middle48%−2.9+0.6+0.2−2.0±2.0
BH crosscourt33%+1.0+1.7−0.1+2.6±2.6
BH down the line12%−0.2+0.8−2.5−1.9±4.4
FH through the middle3%−2.9−0.4+0.6−2.7±2.4
FH inside-out2%+1.0±0.0+0.4+1.3±3.2

Lean BH crosscourt: +3.1±2.1 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.

Elmer Moller

Favour

ShotEdgeOwnTheirs
FH to the middle · rally+7.1±3.0+4.6+2.5
BH to their forehand · rally+0.9±5.5−2.9+3.8
FH to their forehand · rally+0.5±3.9−0.9+1.4
FH to the middle · return±0.0±3.5−3.1+3.2
BH to their backhand · rally−0.4±3.1−1.5+1.2
BH to the middle · return−2.2±3.1−2.1±0.0

Avoid

ShotEdgeOwnTheirs
BH to the middle · rally−2.6±2.7−2.4−0.2
FH to their backhand · rally−2.3±4.1−2.5+0.2
BH to the middle · return−2.2±3.1−2.1±0.0
BH to their backhand · rally−0.4±3.1−1.5+1.2
FH to the middle · return±0.0±3.5−3.1+3.2

Roberto Bautista Agut

Favour

ShotEdgeOwnTheirs
BH to their backhand · rally+3.2±3.4+0.4+2.8
FH to the middle · rally+2.9±3.2+0.2+2.7
FH to their backhand · rally+2.5±3.9−1.4+3.9
FH to their forehand · serve +1+1.9±5.2+2.1−0.1
FH to their backhand · serve +1+1.7±4.5+0.7+1.0
FH to their forehand · rally+1.5±3.7+1.9−0.4

Avoid

ShotEdgeOwnTheirs
FH to the middle · return+0.5±3.4+2.5−2.0
BH to the middle · rally+0.6±2.8+0.1+0.5
BH to the middle · return+1.0±3.2−0.6+1.6
FH to their forehand · rally+1.5±3.7+1.9−0.4
FH to their backhand · serve +1+1.7±4.5+0.7+1.0

Against Roberto Bautista Agut-like opponents

Elmer Moller vMatchesServe pts wonReturn pts won
All charted opponents–56.7%38.1%

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.