RallyIQ

Game plan

Matteo Arnaldi v Andrey Rublev

Every number combines what Matteo Arnaldi does well with what Andrey Rublev allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Matteo Arnaldi wins, best of 3 50%90%: 22%–78% · best of 5: 50%
Serve points won 62.9% / 62.8% Matteo / Andrey · tour 63.5%
Strengths only, no similarity priors 45%serve 62.6% / 63.6%

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. Both were charted enough in the last three seasons, so those carry the most weight. The result is then nudged by Matteo Arnaldi's record against Andrey Rublev's tactical lookalikes and in their charted head-to-heads (head-to-head: +2.5 on serve, +6.1 on return vs expectation (446 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

CareerMatteoAndrey
Direction choice±0.00 ±0.05
better than 57%
+0.03 ±0.04
better than 64%
Shot selection−0.18 ±0.32
better than 32%
−0.01 ±0.06
better than 52%
Execution−0.22 ±0.92
better than 56%
+0.89 ±0.28
better than 94%
Points left on the table2.65 ±0.11
lower than 45%
2.39 ±0.07
lower than 74%

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: Matteo Arnaldi +0.38, Andrey Rublev +0.60. 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.

Matteo Arnaldi serving

Deuce court

1st serveNowMatteo winsv AndreyMatchupOptimal
Wide47%70%74%71.1%±4.660% ▲
Body10%61%60%58.0%±9.50% ▼
T43%72%72%68.9%±5.540% ▼

Optimal v Andrey Rublev: +0.6±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMatteo winsv AndreyMatchupOptimal
Wide47%66%72%65.6%±5.434% ▼
Body3%66%60%62.7%±13.03%
T50%68%74%69.5%±5.163% ▲

Optimal v Andrey Rublev: +0.5±0.6 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.1 per 100 first serves in before the returner adjusts.

Andrey Rublev serving

Deuce court

1st serveNowAndrey winsv MatteoMatchupOptimal
Wide44%74%72%73.4%±4.557% ▲
Body5%68%65%70.2%±9.40% ▼
T51%80%76%80.8%±4.043% ▼

Optimal v Matteo Arnaldi: +0.3±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAndrey winsv MatteoMatchupOptimal
Wide52%77%71%74.7%±4.662% ▲
Body4%68%59%63.8%±11.20% ▼
T44%73%71%72.4%±4.938% ▼

Optimal v Matteo Arnaldi: +0.2±0.4 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.4 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.

Matteo Arnaldi returning

1st serve to the forehand

ReturnNowTourOwnv AndreyValue
FH through the middle39%+4.3+0.1+2.7+7.1±2.1
FH slice through the middle18%−4.2+0.8+0.8−2.6±2.0
FH down the line16%+1.7+1.9+0.8+4.4±3.8
FH crosscourt14%+5.5+2.5+5.0+13.1±3.7
FH slice down the line10%−4.3+4.3+2.2+2.2±3.1

Lean FH crosscourt: +8.0±3.3 per 100 returns v the current mix (340 returns charted)

1st serve to the backhand

ReturnNowTourOwnv AndreyValue
BH through the middle42%+6.4+2.7+3.1+12.2±2.0
BH crosscourt23%+8.8+2.2+3.6+14.6±2.9
BH slice through the middle16%−4.2+0.2−0.5−4.5±2.0
BH down the line11%+4.2+4.0+2.4+10.6±3.9
BH slice crosscourt5%+0.5+1.0+0.3+1.8±2.5

Lean BH crosscourt: +5.7±2.4 per 100 returns v the current mix (324 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv AndreyValue
FH through the middle45%−3.5−0.5+1.1−2.9±2.3
FH crosscourt29%−0.2−3.1+2.4−0.9±3.7
FH down the line26%−1.8−2.9+1.0−3.7±3.9

Lean FH crosscourt: +1.6±3.1 per 100 returns v the current mix (126 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv AndreyValue
BH through the middle42%−2.9+2.4+0.3−0.2±1.8
BH crosscourt38%+1.0+0.6+0.9+2.5±2.4
BH down the line8%−0.2+5.9+7.5+13.2±4.0
FH through the middle5%−2.9+0.4+1.1−1.4±1.7
FH inside-in4%+0.6−0.5+2.4+2.5±3.2

Lean BH down the line: +11.2±3.9 per 100 returns v the current mix (284 returns charted)

Andrey Rublev returning

1st serve to the forehand

ReturnNowTourOwnv MatteoValue
FH through the middle46%+4.3+1.4+2.8+8.4±2.0
FH crosscourt24%+5.5+3.9+5.4+14.8±3.4
FH down the line13%+1.7+2.5+1.2+5.4±3.9
FH slice through the middle10%−4.2−2.9+1.0−6.1±2.1
FH slice crosscourt4%−4.3−0.6±0.0−4.9±1.9

Lean FH crosscourt: +7.5±2.8 per 100 returns v the current mix (2295 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MatteoValue
BH through the middle47%+6.4+3.2+2.1+11.8±2.0
BH crosscourt32%+8.8+3.9+3.2+15.9±2.6
BH down the line9%+4.2+4.2+2.1+10.5±4.1
BH slice through the middle6%−4.2−0.6+0.9−3.9±2.3
BH slice crosscourt3%+0.5−2.2−0.3−2.0±2.9

Lean BH crosscourt: +4.7±2.0 per 100 returns v the current mix (2738 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MatteoValue
FH through the middle44%−3.5+1.0−0.5−3.0±2.5
FH crosscourt29%−0.2+0.6−0.1+0.3±4.0
FH down the line21%−1.8−0.4+1.1−1.1±4.4
BH through the middle2%+0.1−0.7−1.5−2.1±1.8
FH slice through the middle2%−12.7−0.3±0.0−13.0±1.4

Lean FH crosscourt: +2.0±3.2 per 100 returns v the current mix (677 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MatteoValue
BH crosscourt43%+1.0+0.8−0.1+1.8±2.1
BH through the middle39%−2.9+0.8−1.5−3.6±1.7
BH down the line9%−0.2+2.3+0.2+2.3±4.5
FH through the middle4%−2.9−1.1−0.5−4.5±2.3
FH inside-in2%+0.6+1.0−0.1+1.4±4.4
FH inside-out1%+1.0+1.0+1.1+3.1±3.7

Lean FH inside-out: +3.7±3.8 per 100 returns v the current mix (2289 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.

Matteo Arnaldi

Favour

ShotEdgeOwnTheirs
BH to their forehand · return+13.5±3.7+8.2+5.3
FH to their forehand · return+3.9±3.4−0.1+4.1
BH to the middle · return+3.4±1.5+2.3+1.1
FH slice to the middle · return+2.5±2.0+1.5+1.0
FH to the middle · return+2.1±1.8−0.2+2.3
BH to their backhand · return+1.8±2.1+0.7+1.1

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−6.2±3.1−4.5−1.7
FH to their backhand · return +1−5.2±3.2−3.9−1.4
BH slice to the middle · rally−4.1±1.9−1.6−2.5
BH to their backhand · return +1−3.9±2.3−3.1−0.9
FH slice to the middle · rally−2.9±2.3−0.1−2.8

Andrey Rublev

Favour

ShotEdgeOwnTheirs
FH to their forehand · return+8.0±3.2+3.9+4.1
FH to their backhand · return+3.7±3.1+2.3+1.4
FH to the middle · return+3.1±1.7+1.2+2.0
FH to their forehand · return +1+2.8±3.0+1.1+1.7
BH to their backhand · return+2.7±1.8+2.2+0.5
BH to their forehand · return+2.6±3.6+1.8+0.8

Avoid

ShotEdgeOwnTheirs
FH slice to the middle · rally−5.3±2.4−3.6−1.7
BH slice to the middle · rally−4.7±2.0−2.7−2.0
FH to their backhand · rally−4.1±1.9−0.5−3.6
BH to the middle · serve +1−2.3±2.1−0.5−1.8
BH to their backhand · return +1−1.4±2.4−0.5−0.9

Against Andrey Rublev-like opponents

Matteo Arnaldi vMatchesServe pts wonReturn pts won
All charted opponents–59.7%35.9%
Andrey Rublev (charted head-to-head)3 63.8%41.1%

Similar by tactical fingerprint: Karen Khachanov, Laslo Djere, Rinky Hijikata, Aleksandar Vukic, Borna Coric, David Goffin, Juan Pablo Varillas, Thanasi Kokkinakis, Kyle Edmund, Robin Soderling. When two players have rarely met, their records against these lookalikes fill the gap.

Charted head-to-head