RallyIQ

Game plan

Andrea Petkovic v Shelby Rogers

Every number combines what Andrea Petkovic does well with what Shelby Rogers allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Andrea Petkovic wins, best of 3 25%90%: 9%–48% · best of 5: 20%
Serve points won 57.2% / 62.4% Andrea / Shelby · tour 56.4%
Strengths only, no similarity priors 25%serve 56.8% / 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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Andrea Petkovic's record against Shelby Rogers's tactical lookalikes and in their charted head-to-heads (lookalikes: +6.9 on serve, −8.2 on return vs expectation (166 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

CareerAndreaShelby
Direction choice−0.18 ±0.14
better than 21%
−0.15 ±0.09
better than 26%
Shot selection+0.39 ±0.15
better than 89%
−0.18 ±0.13
better than 29%
Execution−0.77 ±0.60
better than 24%
−0.20 ±0.44
better than 49%
Points left on the table2.70 ±0.22
lower than 35%
2.78 ±0.16
lower than 25%

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.

Andrea Petkovic serving

Deuce court

1st serveNowAndrea winsv ShelbyMatchupOptimal
Wide39%66%73%73.6%±6.954% ▲
Body28%58%57%58.5%±9.312% ▼
T33%62%69%63.4%±8.634%

Optimal v Shelby Rogers: +1.0±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +7.5 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAndrea winsv ShelbyMatchupOptimal
Wide36%67%70%71.8%±8.036%
Body25%50%55%48.4%±10.210% ▼
T39%60%69%64.3%±8.454% ▲

Optimal v Shelby Rogers: +1.4±1.1 per 100 first serves (faults included) over the current mix. Serving wide every time would read +8.8 per 100 first serves in before the returner adjusts.

Shelby Rogers serving

Deuce court

1st serveNowShelby winsv AndreaMatchupOptimal
Wide50%72%64%69.9%±7.165% ▲
Body18%59%61%63.1%±9.72% ▼
T32%65%73%70.5%±8.733%

Optimal v Andrea Petkovic: +0.4±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowShelby winsv AndreaMatchupOptimal
Wide44%66%69%69.6%±8.053% ▲
Body13%62%55%60.5%±11.20% ▼
T43%65%62%62.6%±8.147% ▲

Optimal v Andrea Petkovic: +0.6±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.2 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.

Andrea Petkovic returning

1st serve to the forehand

ReturnNowTourOwnv ShelbyValue
FH through the middle58%+4.2+1.7+0.9+6.7±2.6
FH crosscourt30%+5.3−0.1+2.6+7.8±4.3
FH down the line10%+1.5−2.5−2.7−3.6±4.6
FH slice through the middle2%−6.7+1.0+0.9−4.8±2.1

Lean FH crosscourt: +2.0±3.4 per 100 returns v the current mix (307 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv ShelbyValue
BH through the middle48%+6.0+2.1+1.3+9.4±2.7
BH crosscourt34%+7.7−0.1+0.9+8.5±3.7
BH down the line15%+2.2+6.4−2.6+6.0±4.6
BH slice through the middle3%−6.2+0.5+1.5−4.3±2.0

Lean BH through the middle: +1.2±2.0 per 100 returns v the current mix (182 returns charted, inside the 90% margin)

2nd serve to the forehand

ReturnNowTourOwnv ShelbyValue
FH crosscourt54%+0.5+0.9+0.3+1.8±4.4
FH through the middle46%−3.2+0.8−0.5−2.9±3.0

Lean FH crosscourt: +2.2±2.5 per 100 returns v the current mix (63 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv ShelbyValue
BH through the middle51%−2.6+2.1−1.1−1.7±2.7
BH crosscourt32%+1.5−0.1−2.4−1.0±3.6
BH down the line13%−0.5+2.5+1.8+3.8±4.7
FH inside-in5%+0.7−3.3+0.3−2.2±3.9

Lean BH crosscourt: −0.2±2.9 per 100 returns v the current mix (104 returns charted, inside the 90% margin)

Shelby Rogers returning

1st serve to the forehand

ReturnNowTourOwnv AndreaValue
FH through the middle42%+4.2±0.0+1.1+5.2±2.8
FH crosscourt21%+5.3−0.1+2.0+7.3±4.3
FH down the line15%+1.5−0.2−0.1+1.2±4.7
FH slice through the middle12%−6.7±0.0+0.1−6.6±2.5
FH slice crosscourt6%−6.6−1.0+0.5−7.1±2.4

Lean FH crosscourt: +4.8±3.7 per 100 returns v the current mix (264 returns charted)

1st serve to the backhand

ReturnNowTourOwnv AndreaValue
BH through the middle46%+6.0−2.3+1.3+5.1±2.6
BH crosscourt19%+7.7+1.8+2.1+11.6±3.6
BH down the line13%+2.2−0.3+2.7+4.6±4.6
BH slice through the middle10%−6.2−0.7+1.9−5.0±2.3
BH slice crosscourt7%−4.2−2.9−0.8−7.9±2.4

Lean BH crosscourt: +8.1±3.2 per 100 returns v the current mix (237 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv AndreaValue
FH through the middle71%−3.2+1.0−1.4−3.6±3.0
FH crosscourt29%+0.5−1.4+0.9±0.0±4.0

Lean FH through the middle: −1.1±1.5 per 100 returns v the current mix (41 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv AndreaValue
BH through the middle52%−2.6−0.5+0.9−2.2±2.8
BH crosscourt26%+1.5−1.0+2.5+3.1±3.7
BH down the line19%−0.5+0.8+1.4+1.7±4.8
BH slice down the line3%−10.6−1.0±0.0−11.6±1.8

Lean BH crosscourt: +3.5±3.2 per 100 returns v the current mix (153 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 hard. Each player's hard record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Andrea Petkovic

Favour

ShotEdgeOwnTheirs
BH to their forehand · return+9.1±6.7+8.6+0.6
FH to their backhand · serve +1+3.9±5.5−2.0+5.9
FH to their backhand · return +1+3.1±6.3+4.2−1.1
FH to the middle · return+3.1±2.9+2.3+0.7
BH to their forehand · serve +1+2.1±7.1+1.1+1.0
FH to their forehand · return+2.0±5.5−1.4+3.4

Avoid

ShotEdgeOwnTheirs
FH to their forehand · serve +1−4.6±4.9−4.0−0.6
FH to their forehand · return +1−4.1±4.8−1.7−2.4
BH to the middle · return +1−3.3±3.6−1.8−1.5
BH to the middle · serve +1−2.9±3.4−1.5−1.5
FH to the middle · serve +1−2.6±3.4+0.5−3.1

Shelby Rogers

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+8.2±4.9+5.8+2.5
FH to their forehand · return +1+4.2±5.2+3.2+1.0
FH to their backhand · serve +1+3.3±5.0+0.1+3.2
FH to their forehand · return+3.2±5.8±0.0+3.1
FH to the middle · serve +1+2.9±3.4+2.1+0.8
BH to the middle · serve +1+2.4±3.4+2.5−0.1

Avoid

ShotEdgeOwnTheirs
BH to their backhand · serve +1−5.9±5.2−4.5−1.4
BH to their forehand · rally−3.7±5.6−2.2−1.5
BH to their backhand · rally−3.1±3.8−3.1±0.0
FH to their backhand · return−2.7±6.0−1.5−1.2
BH to their backhand · return +1−2.1±4.9−0.3−1.8

Against Shelby Rogers-like opponents

Andrea Petkovic vMatchesServe pts wonReturn pts won
All charted opponents–55.1%43.4%
Players most similar to Shelby Rogers1 60.9%30.0%

Similar by tactical fingerprint: Coco Gauff, Iva Jovic, Anastasia Potapova, Karolina Pliskova, Belinda Bencic, Sorana Cirstea, Victoria Mboko, Nao Hibino, Irina Camelia Begu, Kaia Kanepi. When two players have rarely met, their records against these lookalikes fill the gap.