RallyIQ

Game plan

Rafael Jodar v Sebastian Ofner

Every number combines what Rafael Jodar does well with what Sebastian Ofner allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Rafael Jodar wins, best of 3 58%90%: 25%–86% · best of 5: 60%
Serve points won 63.1% / 61.5% Rafael / Sebastian · tour 63.4%
Strengths only, no similarity priors 59%serve 63.1% / 61.3%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Rafael Jodar's record against Sebastian Ofner's tactical lookalikes and in their charted head-to-heads (lookalikes: −0.5 on serve, −3.9 on return vs expectation (164 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

CareerRafaelSebastian
Direction choice+0.18 ±0.12
better than 93%
+0.19 ±0.11
better than 94%
Shot selection+0.07 ±0.08
better than 61%
+0.10 ±0.16
better than 65%
Execution+0.37 ±1.34
better than 81%
−1.43 ±0.81
better than 12%
Points left on the table2.06 ±0.11
lower than 99%
2.44 ±0.27
lower than 69%

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.

Rafael Jodar serving

Deuce court

1st serveNowRafael winsv SebastianMatchupOptimal
Wide45%74%77%77.8%±8.058% ▲
Body3%53%63%52.8%±19.10% ▼
T52%71%74%69.4%±9.742% ▼

Optimal v Sebastian Ofner: +0.6±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +5.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRafael winsv SebastianMatchupOptimal
Wide54%73%74%74.4%±9.267% ▲
Body10%61%57%54.9%±17.00% ▼
T36%64%67%57.9%±11.533% ▼

Optimal v Sebastian Ofner: +0.7±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +7.9 per 100 first serves in before the returner adjusts.

Sebastian Ofner serving

Deuce court

1st serveNowSebastian winsv RafaelMatchupOptimal
Wide46%70%68%64.5%±10.159% ▲
Body7%58%59%54.3%±18.28%
T46%71%64%58.7%±11.033% ▼

Optimal v Rafael Jodar: +0.2±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSebastian winsv RafaelMatchupOptimal
Wide54%68%69%64.6%±10.345% ▼
Body4%70%67%73.6%±15.70% ▼
T42%68%66%61.4%±12.155% ▲

Optimal v Rafael Jodar: +0.1±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +10.0 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.

Rafael Jodar returning

1st serve to the forehand

ReturnNowTourOwnv SebastianValue
FH through the middle40%+4.3+1.0−0.6+4.7±3.1
FH crosscourt22%+5.5+3.4+0.8+9.7±4.2
FH slice through the middle15%−4.2−0.1−1.9−6.2±1.9
FH down the line10%+1.7+4.4−1.2+4.9±3.9
FH slice down the line7%−4.3−0.2−0.4−4.9±2.0

Lean FH crosscourt: +6.9±3.6 per 100 returns v the current mix (110 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SebastianValue
BH through the middle40%+6.4±0.0+1.3+7.8±2.8
BH crosscourt35%+8.8+0.5−2.9+6.4±3.6
BH down the line18%+4.2+3.5−3.9+3.8±4.4
BH slice through the middle4%−4.2−0.4−1.6−6.2±2.0
BH slice crosscourt3%+0.5−0.5−1.0−1.0±1.8

Lean BH through the middle: +2.0±2.3 per 100 returns v the current mix (164 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv SebastianValue
BH crosscourt44%+1.0−2.1+0.9−0.2±3.3
BH through the middle38%−2.9+1.0+0.6−1.3±2.6
BH down the line18%−0.2+2.3+0.1+2.2±4.3

Lean BH down the line: +2.4±4.0 per 100 returns v the current mix (107 returns charted, inside the 90% margin)

Sebastian Ofner returning

1st serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle44%+4.3−6.4+3.8+1.7±3.1
FH down the line36%+1.7−5.0+3.1−0.3±4.5
FH crosscourt16%+5.5−3.1+2.4+4.8±4.2
FH slice through the middle4%−4.2+0.4−1.5−5.2±1.8

Lean FH crosscourt: +3.6±4.1 per 100 returns v the current mix (154 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle43%+6.4−4.2+1.0+3.3±2.9
BH crosscourt36%+8.8−0.6+0.7+8.9±3.6
BH down the line12%+4.2−4.0+3.6+3.8±4.3
BH slice through the middle5%−4.2−0.7−1.2−6.2±1.9
BH slice crosscourt4%+0.5−1.0±0.0−0.5±1.3

Lean BH crosscourt: +4.1±2.7 per 100 returns v the current mix (139 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle44%−3.5−1.1−1.6−6.2±2.8
FH crosscourt29%−0.2+0.2−0.6−0.6±4.0
FH down the line27%−1.8−0.1+0.1−1.8±4.3

Lean FH through the middle: −2.8±2.2 per 100 returns v the current mix (45 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle52%−2.9−2.6−0.8−6.3±2.5
BH crosscourt38%+1.0±0.0−0.3+0.7±3.2
BH down the line10%−0.2+2.6+3.5+5.9±4.3

Lean BH crosscourt: +3.1±2.4 per 100 returns v the current mix (97 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.

Rafael Jodar

Favour

ShotEdgeOwnTheirs
BH to the middle · return+3.1±2.6+1.3+1.8
FH to their forehand · rally+2.1±3.3−0.6+2.7
BH to the middle · rally+1.8±2.3+0.7+1.0
BH to their backhand · return+1.0±3.4+2.4−1.3
FH to their backhand · serve +1+0.5±3.8−1.4+1.8
FH to the middle · return−0.2±2.8+0.1−0.3

Avoid

ShotEdgeOwnTheirs
FH to their backhand · rally−5.1±3.3−2.2−2.9
FH to their forehand · serve +1−3.9±4.1−1.9−2.0
BH to their backhand · rally−3.2±2.8−1.9−1.3
FH to the middle · rally−2.1±2.6−1.8−0.3
FH to the middle · return−0.2±2.8+0.1−0.3

Sebastian Ofner

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1−0.4±4.1+0.2−0.6
FH to their forehand · rally−0.6±3.2+0.8−1.4
FH to their backhand · rally−0.9±3.1−2.4+1.6
BH to their forehand · rally−1.3±4.5−2.1+0.7
BH to the middle · rally−1.7±2.4−1.8+0.1
BH to their backhand · rally−2.0±2.6−0.7−1.4

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−8.5±3.8−4.2−4.3
FH to the middle · rally−4.9±2.7−3.4−1.5
FH to the middle · return−4.5±2.8−5.1+0.7
FH to their backhand · return−3.0±4.1−4.8+1.8
BH to the middle · return−2.6±2.6−3.8+1.3

Against Sebastian Ofner-like opponents

Rafael Jodar vMatchesServe pts wonReturn pts won
All charted opponents–60.8%39.3%
Players most similar to Sebastian Ofner1 62.2%31.7%

Similar by tactical fingerprint: Arthur Fils, Tommy Paul, Sebastian Korda, Marin Cilic, Roman Safiullin, Borna Coric, David Goffin, Lloyd Harris, Kyle Edmund. When two players have rarely met, their records against these lookalikes fill the gap.