RallyIQ

Game plan

Jule Niemeier v Peyton Stearns

Every number combines what Jule Niemeier does well with what Peyton Stearns allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Jule Niemeier wins, best of 3 36%90%: 11%–70% · best of 5: 32%
Serve points won 54.0% / 56.7% Jule / Peyton · tour 56.3%
Strengths only, no similarity priors 36%serve 54.0% / 56.7%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerJulePeyton
Direction choice−0.06 ±0.09
better than 41%
+0.01 ±0.13
better than 55%
Shot selection+0.21 ±0.30
better than 68%
+0.40 ±0.24
better than 90%
Execution−2.75 ±0.94
better than 2%
−1.43 ±0.74
better than 12%
Points left on the table2.67 ±0.13
lower than 37%
2.46 ±0.11
lower than 68%

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.

Jule Niemeier serving

Deuce court

1st serveNowJule winsv PeytonMatchupOptimal
Wide37%66%69%69.5%±9.352% ▲
Body19%63%62%66.9%±10.77% ▼
T43%65%72%70.1%±9.041% ▼

Optimal v Peyton Stearns: +0.3±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +0.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJule winsv PeytonMatchupOptimal
Wide33%63%63%59.8%±10.246% ▲
Body24%56%57%57.5%±11.521% ▼
T42%62%61%57.7%±10.733% ▼

Optimal v Peyton Stearns: ±0.0±0.9 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.

Peyton Stearns serving

Deuce court

1st serveNowPeyton winsv JuleMatchupOptimal
Wide38%58%72%64.4%±9.551% ▲
Body33%59%59%61.0%±9.833%
T29%62%69%63.9%±10.716% ▼

Optimal v Jule Niemeier: +0.1±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowPeyton winsv JuleMatchupOptimal
Wide41%61%61%56.3%±9.457% ▲
Body23%54%62%60.6%±10.723%
T36%54%69%58.8%±11.520% ▼

Optimal v Jule Niemeier: +0.3±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body 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.

Jule Niemeier returning

1st serve to the forehand

ReturnNowTourOwnv PeytonValue
FH through the middle51%+4.2−0.8+0.3+3.7±3.0
FH crosscourt31%+5.3−0.8+3.2+7.7±4.2
FH down the line13%+1.5−1.5+3.3+3.3±4.4
FH slice through the middle5%−6.7−0.1−2.5−9.3±2.0

Lean FH crosscourt: +3.5±3.4 per 100 returns v the current mix (121 returns charted)

1st serve to the backhand

ReturnNowTourOwnv PeytonValue
BH through the middle46%+6.0−0.2−1.4+4.4±2.8
BH crosscourt31%+7.7−0.2−0.5+7.1±3.5
BH down the line8%+2.2+1.5−2.7+1.0±4.2
BH slice through the middle7%−6.2+0.2+2.0−4.1±2.2
BH slice crosscourt5%−4.2−0.2−0.2−4.6±2.2

Lean BH crosscourt: +3.8±2.7 per 100 returns v the current mix (143 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv PeytonValue
BH through the middle39%−2.6−1.3+0.5−3.4±2.7
BH crosscourt34%+1.5−1.7+0.5+0.3±3.5
BH down the line11%−0.5−3.5−1.4−5.5±4.5
FH inside-out9%+1.4+0.6+1.5+3.4±3.6
FH through the middle7%−2.7−0.5−0.3−3.4±2.2

Lean BH crosscourt: +2.0±2.6 per 100 returns v the current mix (76 returns charted, inside the 90% margin)

Peyton Stearns returning

1st serve to the forehand

ReturnNowTourOwnv JuleValue
FH through the middle53%+4.2−0.5−2.0+1.6±3.0
FH crosscourt28%+5.3−3.1−3.0−0.8±4.4
FH down the line20%+1.5−2.9−2.6−3.9±4.6

Lean FH through the middle: +1.8±2.1 per 100 returns v the current mix (174 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JuleValue
BH through the middle37%+6.0−0.9+0.4+5.6±2.8
BH crosscourt32%+7.7−1.0−1.3+5.4±3.6
BH down the line13%+2.2−1.5−0.8−0.1±4.5
BH slice through the middle8%−6.2−1.5−1.8−9.5±2.3
BH slice crosscourt7%−4.2−1.4±0.0−5.6±1.9

Lean BH through the middle: +3.2±2.2 per 100 returns v the current mix (238 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JuleValue
FH down the line41%−0.6+3.1−1.8+0.8±4.9
FH through the middle39%−3.2+0.2+0.5−2.5±3.0
FH crosscourt20%+0.5−2.1+0.7−0.9±4.0

Lean FH down the line: +1.6±3.2 per 100 returns v the current mix (51 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JuleValue
BH crosscourt28%+1.5+0.3+0.2+2.0±3.6
BH through the middle24%−2.6+1.0+2.8+1.2±2.8
FH inside-in16%+0.7−2.1+0.7−0.6±4.6
FH through the middle15%−2.7−0.3+0.5−2.5±2.6
FH inside-out10%+1.4−2.3−1.8−2.7±3.9

Lean BH crosscourt: +1.7±2.8 per 100 returns v the current mix (144 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.

Jule Niemeier

Favour

ShotEdgeOwnTheirs
FH to their forehand · return+4.0±4.2+0.2+3.7
FH to the middle · return−0.6±2.6−1.1+0.5
BH to their backhand · return−0.8±3.3−1.1+0.3
BH to the middle · rally−0.9±2.4−0.8−0.1
FH to their forehand · rally−1.7±3.3−1.4−0.3
BH to their backhand · rally−1.8±3.2−2.1+0.3

Avoid

ShotEdgeOwnTheirs
FH to the middle · serve +1−5.8±2.7−2.9−2.9
FH to their backhand · serve +1−5.3±4.1−4.3−1.1
FH to the middle · rally−5.1±2.6−3.0−2.1
FH to their backhand · rally−4.5±3.7−3.6−0.9
BH to the middle · return−3.4±2.4−2.8−0.6

Peyton Stearns

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+2.3±3.1+0.2+2.1
BH to the middle · return+1.5±2.5−0.1+1.6
BH to the middle · serve +1+1.2±2.7+1.5−0.3
BH to their backhand · serve +1+0.6±3.8+0.9−0.3
FH to the middle · serve +1+0.2±2.7+0.7−0.5
BH to their backhand · return−1.1±3.5−0.3−0.7

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−6.8±4.8−6.9+0.1
FH to their backhand · return−6.3±4.3−3.1−3.2
BH to their backhand · rally−5.8±3.1−4.1−1.7
FH to their backhand · rally−5.7±3.4−1.8−4.0
FH to their forehand · return−4.6±4.2−2.8−1.8

Against Peyton Stearns-like opponents

Jule Niemeier vMatchesServe pts wonReturn pts won
All charted opponents–52.2%40.6%

Similar by tactical fingerprint: Madison Keys, Xin Yu Wang, Tamara Zidansek, Lulu Sun, Katie Boulter, Nao Hibino, Daria Saville, Misaki Doi, Ana Ivanovic. When two players have rarely met, their records against these lookalikes fill the gap.