RallyIQ

Game plan

Magnus Larsson v Reilly Opelka

Every number combines what Magnus Larsson does well with what Reilly Opelka allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Magnus Larsson wins, best of 3 54%90%: 29%–78% · best of 5: 55%
Serve points won 70.1% / 69.2% Magnus / Reilly · tour 63.4%
Strengths only, no similarity priors 54%serve 70.1% / 69.2%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerMagnusReilly
Direction choice+0.15 ±0.23
better than 88%
−0.19 ±0.11
better than 16%
Shot selection−0.83 ±0.32
better than 4%
+0.14 ±0.11
better than 69%
Execution+0.03 ±1.45
better than 70%
−1.23 ±0.68
better than 18%

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.

Magnus Larsson serving

Deuce court

1st serveNowMagnus winsv ReillyMatchupOptimal
Wide39%71%80%79.1%±6.337% ▼
Body10%70%70%75.5%±9.90% ▼
T50%79%83%86.3%±4.863% ▲

Optimal v Reilly Opelka: +0.8±0.7 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMagnus winsv ReillyMatchupOptimal
Wide49%80%81%86.9%±4.762% ▲
Body8%61%72%70.7%±11.60% ▼
T42%73%80%81.5%±6.238% ▼

Optimal v Reilly Opelka: +0.7±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.7 per 100 first serves in before the returner adjusts.

Reilly Opelka serving

Deuce court

1st serveNowReilly winsv MagnusMatchupOptimal
Wide50%77%79%82.2%±5.963% ▲
Body9%62%66%64.7%±12.50% ▼
T41%80%83%86.7%±5.137% ▼

Optimal v Magnus Larsson: +0.9±0.7 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowReilly winsv MagnusMatchupOptimal
Wide49%82%77%84.8%±5.243% ▼
Body7%61%63%61.1%±14.10% ▼
T44%77%79%83.0%±5.857% ▲

Optimal v Magnus Larsson: +1.0±0.7 per 100 first serves (faults included) over the current mix. Serving wide every time would read +2.5 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.

Magnus Larsson returning

1st serve to the forehand

ReturnNowTourOwnv ReillyValue
FH through the middle42%+4.3−2.3+1.2+3.2±2.7
FH crosscourt23%+5.5−3.5+1.7+3.7±4.2
FH down the line19%+1.7−0.9+4.4+5.2±4.3
FH slice crosscourt6%−4.3+0.1+2.1−2.1±2.4
FH slice through the middle6%−4.2−0.5−0.3−5.0±1.7

Lean FH down the line: +2.7±3.8 per 100 returns v the current mix (123 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv ReillyValue
BH crosscourt28%+8.8±0.0+0.3+9.1±3.5
BH slice crosscourt21%+0.5−0.7−1.8−2.0±3.0
BH through the middle19%+6.4−0.8+0.8+6.4±2.4
BH slice through the middle18%−4.2−1.7−1.5−7.5±2.2
BH down the line10%+4.2−1.3−2.0+1.0±4.1

Lean BH crosscourt: +7.4±2.7 per 100 returns v the current mix (122 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv ReillyValue
BH through the middle27%−2.9−0.9−1.1−4.9±2.0
BH crosscourt25%+1.0+0.3−2.1−0.7±2.8
BH down the line21%−0.2+2.4−0.1+2.2±4.5
BH slice through the middle14%−11.3−0.2−2.8−14.3±2.1
BH slice crosscourt13%−4.0−0.7−3.2−7.9±2.2

Lean BH crosscourt: +3.4±2.4 per 100 returns v the current mix (63 returns charted)

Reilly Opelka returning

1st serve to the forehand

ReturnNowTourOwnv MagnusValue
FH through the middle41%+4.3−3.8−2.0−1.5±2.7
FH down the line21%+1.7−0.8+1.0+1.9±3.9
FH slice through the middle16%−4.2−2.6+0.3−6.6±2.0
FH crosscourt13%+5.5−1.9−1.2+2.4±4.2
FH slice down the line4%−4.3+1.2±0.0−3.0±2.2

Lean FH crosscourt: +3.6±3.9 per 100 returns v the current mix (809 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv MagnusValue
BH through the middle57%+6.4−2.2−3.1+1.1±2.2
BH crosscourt24%+8.8−2.2+2.0+8.6±3.1
BH slice through the middle7%−4.2−1.9−1.2−7.3±2.5
BH down the line7%+4.2+2.8−3.3+3.7±4.0
BH slice crosscourt3%+0.5−1.7−2.5−3.8±2.9

Lean BH crosscourt: +6.5±2.7 per 100 returns v the current mix (713 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MagnusValue
FH through the middle43%−3.5−4.5+0.2−7.7±2.7
FH down the line31%−1.8−4.5+0.3−6.0±4.4
FH crosscourt15%−0.2−5.8−2.1−8.2±4.2
FH slice through the middle6%−12.7+0.1±0.0−12.6±1.4
BH through the middle3%+0.1−0.5±0.0−0.4±1.6

Lean FH down the line: +1.4±3.3 per 100 returns v the current mix (219 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MagnusValue
BH through the middle53%−2.9−2.9±0.0−5.8±2.1
BH crosscourt34%+1.0−3.5+0.9−1.5±2.9
BH down the line9%−0.2−1.5±0.0−1.7±3.5
FH through the middle2%−2.9+0.3+0.2−2.4±2.0
FH inside-out2%+1.0+0.7+0.3+1.9±2.9

Lean BH crosscourt: +2.3±2.2 per 100 returns v the current mix (482 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.

Magnus Larsson

Favour

ShotEdgeOwnTheirs
FH to their backhand · serve +1−0.4±3.3+0.8−1.3
FH to their backhand · rally−0.8±3.1+0.5−1.3
FH to their forehand · rally−1.0±3.3−1.9+0.9
BH to their backhand · rally−1.5±2.6−1.9+0.4
FH to the middle · return−1.7±2.4−1.9+0.1
BH to their backhand · return−1.7±3.0+0.1−1.9

Avoid

ShotEdgeOwnTheirs
BH to the middle · return−2.2±2.2−1.2−1.0
BH to their backhand · return−1.7±3.0+0.1−1.9
FH to the middle · return−1.7±2.4−1.9+0.1
BH to their backhand · rally−1.5±2.6−1.9+0.4
FH to their forehand · rally−1.0±3.3−1.9+0.9

Reilly Opelka

Favour

ShotEdgeOwnTheirs
FH to the middle · return−5.9±2.4−4.7−1.2
BH to their backhand · rally−6.0±2.6−5.5−0.5
FH to their forehand · rally−7.5±3.3−4.6−2.9
FH to their backhand · rally−8.0±3.0−4.5−3.5

Avoid

ShotEdgeOwnTheirs
FH to their backhand · rally−8.0±3.0−4.5−3.5
FH to their forehand · rally−7.5±3.3−4.6−2.9
BH to their backhand · rally−6.0±2.6−5.5−0.5
FH to the middle · return−5.9±2.4−4.7−1.2

Against Reilly Opelka-like opponents

Magnus Larsson vMatchesServe pts wonReturn pts won
All charted opponents–65.1%31.0%

Similar by tactical fingerprint: Arthur Rinderknech, Zhizhen Zhang, Zizou Bergs, Giovanni Mpetshi Perricard, Gabriel Diallo, Nicolas Jarry, Milos Raonic, John Isner, Sam Querrey, Lukas Rosol. When two players have rarely met, their records against these lookalikes fill the gap.