RallyIQ

Game plan

Jennifer Brady v Eva Vedder

Every number combines what Jennifer Brady does well with what Eva Vedder allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Jennifer Brady wins, best of 3 91%90%: 67%–98% · best of 5: 95%
Serve points won 64.5% / 54.4% Jennifer / Eva · tour 56.3%
Strengths only, no similarity priors 90%serve 64.7% / 54.6%

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. At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Jennifer Brady's record against Eva Vedder's tactical lookalikes and in their charted head-to-heads (lookalikes: −2.9 on serve, +4.1 on return vs expectation (200 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

CareerJenniferEva
Direction choice−0.09 ±0.08
better than 38%
−0.22 ±0.20
better than 15%
Shot selection+0.17 ±0.13
better than 62%
+0.01 ±0.33
better than 46%
Execution+0.48 ±0.65
better than 78%
−1.19 ±0.71
better than 15%
Points left on the table2.74 ±0.15
lower than 28%
2.90 ±0.34
lower than 16%

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.

Jennifer Brady serving

Deuce court

1st serveNowJennifer winsv EvaMatchupOptimal
Wide48%70%65%68.8%±9.054% ▲
Body12%54%66%63.1%±11.60% ▼
T40%78%69%79.5%±8.046% ▲

Optimal v Eva Vedder: +0.4±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJennifer winsv EvaMatchupOptimal
Wide39%67%72%73.8%±8.236% ▼
Body9%64%65%72.2%±12.40% ▼
T52%70%64%70.0%±9.564% ▲

Optimal v Eva Vedder: +0.4±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.1 per 100 first serves in before the returner adjusts.

Eva Vedder serving

Deuce court

1st serveNowEva winsv JenniferMatchupOptimal
Wide39%61%68%63.3%±10.054% ▲
Body23%49%57%48.7%±12.08% ▼
T38%64%68%63.8%±10.738%

Optimal v Jennifer Brady: +0.8±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowEva winsv JenniferMatchupOptimal
Wide49%61%67%63.1%±9.264% ▲
Body7%57%60%61.2%±14.20% ▼
T43%66%66%67.5%±10.036% ▼

Optimal v Jennifer Brady: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.6 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.

Jennifer Brady returning

1st serve to the forehand

ReturnNowTourOwnv EvaValue
FH through the middle56%+4.2−0.9+1.1+4.4±3.0
FH crosscourt18%+5.3−3.0+0.8+3.1±4.2
FH down the line15%+1.5−1.9−0.1−0.6±4.5
FH slice through the middle8%−6.7−1.6−0.4−8.8±2.4
FH slice crosscourt2%−6.6+1.0±0.0−5.6±1.1

Lean FH through the middle: +2.5±1.7 per 100 returns v the current mix (266 returns charted)

1st serve to the backhand

ReturnNowTourOwnv EvaValue
BH through the middle45%+6.0−0.7−0.8+4.5±2.8
BH crosscourt22%+7.7±0.0+2.0+9.7±3.7
BH down the line21%+2.2−1.5−0.5+0.1±4.6
BH slice through the middle9%−6.2+0.4+0.7−5.2±2.2
BH slice down the line3%−12.5−1.2±0.0−13.7±1.9

Lean BH crosscourt: +6.4±3.3 per 100 returns v the current mix (292 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv EvaValue
FH through the middle51%−3.2+1.0+0.6−1.6±3.1
FH crosscourt31%+0.5−3.4−0.5−3.3±4.2
FH down the line18%−0.6−0.2−2.5−3.3±4.6

Lean FH through the middle: +0.8±2.2 per 100 returns v the current mix (67 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv EvaValue
BH through the middle34%−2.6−0.8−1.1−4.5±2.8
BH crosscourt30%+1.5−3.0−0.6−2.1±3.7
FH through the middle13%−2.7−1.4+0.6−3.5±2.6
BH down the line11%−0.5−1.7+1.2−1.0±4.9
FH inside-in7%+0.7−2.4−0.5−2.1±4.2

Lean BH down the line: +1.8±4.6 per 100 returns v the current mix (206 returns charted, inside the 90% margin)

Eva Vedder returning

1st serve to the forehand

ReturnNowTourOwnv JenniferValue
FH through the middle52%+4.2+0.8−3.4+1.6±3.0
FH slice through the middle25%−6.7−0.1−1.7−8.5±2.4
FH crosscourt14%+5.3−0.9−0.7+3.8±4.0
FH down the line10%+1.5+0.5−2.7−0.7±4.1

Lean FH through the middle: +2.4±1.7 per 100 returns v the current mix (102 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JenniferValue
BH through the middle50%+6.0−4.0−2.4−0.3±2.8
BH crosscourt24%+7.7−0.6+1.0+8.2±3.6
BH down the line14%+2.2−2.4−1.1−1.4±4.5
BH slice through the middle8%−6.2+0.8−0.9−6.3±2.2
BH slice crosscourt3%−4.2−1.4−2.3−7.9±2.1

Lean BH crosscourt: +7.3±3.2 per 100 returns v the current mix (143 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JenniferValue
BH through the middle33%−2.6+2.7+0.4+0.6±2.4
BH crosscourt23%+1.5+0.9+0.5+2.9±3.0
FH through the middle19%−2.7−0.1−0.8−3.6±2.3
BH down the line13%−0.5−2.2−2.4−5.1±4.5
FH inside-out12%+1.4+0.8−1.6+0.6±3.6

Lean BH through the middle: +1.0±2.0 per 100 returns v the current mix (52 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.

Jennifer Brady

Favour

ShotEdgeOwnTheirs
FH to their backhand · rally+3.4±3.3+2.3+1.1
BH to their backhand · rally+2.9±2.8+2.4+0.5
FH to their forehand · serve +1+2.6±4.0+1.8+0.9
FH to their backhand · serve +1+2.5±4.0+3.1−0.6
FH to their forehand · rally+1.1±3.0+1.5−0.4
BH to the middle · rally+0.5±2.2+0.9−0.3

Avoid

ShotEdgeOwnTheirs
BH to the middle · return−1.9±2.4−0.2−1.7
BH to their backhand · return +1−1.4±3.6−0.2−1.2
FH to their forehand · return +1−0.4±3.9−0.9+0.4
FH to the middle · return−0.2±2.7−0.6+0.3
FH to the middle · rally−0.1±2.4−1.0+0.9

Eva Vedder

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+2.6±3.8+1.8+0.8
BH to their backhand · rally+1.9±2.7+1.2+0.8
BH to the middle · rally+1.0±2.2+0.7+0.4
FH to their backhand · rally+0.5±3.3−1.0+1.5
BH to their backhand · return±0.0±3.4±0.0−0.1
FH to the middle · rally−0.3±2.4−0.9+0.6

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−3.8±4.1−1.2−2.6
FH to the middle · return−3.2±2.7−0.1−3.1
BH to the middle · return−3.0±2.4−0.8−2.2
FH to the middle · serve +1−2.5±2.7−3.4+0.9
FH to their forehand · rally−2.0±3.1−1.8−0.2

Against Eva Vedder-like opponents

Jennifer Brady vMatchesServe pts wonReturn pts won
All charted opponents–60.6%40.5%
Players most similar to Eva Vedder1 55.8%47.4%

Similar by tactical fingerprint: Xin Yu Wang, Tamara Zidansek, Suzan Lamens, Nadia Podoroska, Maria Sakkari, Lucia Bronzetti, Polona Hercog, Kiki Bertens, Johanna Larsson. When two players have rarely met, their records against these lookalikes fill the gap.