RallyIQ

Game plan

Nuria Parrizas Diaz v Anna Lena Friedsam

Every number combines what Nuria Parrizas Diaz does well with what Anna Lena Friedsam allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Nuria Parrizas Diaz wins, best of 3 54%90%: 21%–84% · best of 5: 55%
Serve points won 55.4% / 54.6% Nuria / Anna · tour 56.3%
Strengths only, no similarity priors 54%serve 55.4% / 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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Nuria Parrizas Diaz's record against Anna Lena Friedsam'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

CareerNuriaAnna
Direction choice+0.06 ±0.12
better than 64%
±0.00 ±0.15
better than 52%
Shot selection+0.20 ±0.15
better than 66%
−0.47 ±0.33
better than 12%
Execution+0.01 ±1.06
better than 61%
−0.06 ±1.00
better than 58%
Points left on the table2.11 ±0.09
lower than 98%
2.54 ±0.20
lower than 61%

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.

Nuria Parrizas Diaz serving

Deuce court

1st serveNowNuria winsv AnnaMatchupOptimal
Wide25%55%60%48.5%±11.615% ▼
Body46%55%60%58.4%±11.540% ▼
T30%61%64%57.3%±10.645% ▲

Optimal v Anna Lena Friedsam: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +2.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowNuria winsv AnnaMatchupOptimal
Wide50%57%71%63.0%±9.851%
Body36%55%64%63.1%±11.720% ▼
T14%60%70%65.8%±12.029% ▲

Optimal v Anna Lena Friedsam: +1.0±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.4 per 100 first serves in before the returner adjusts.

Anna Lena Friedsam serving

Deuce court

1st serveNowAnna winsv NuriaMatchupOptimal
Wide37%62%63%58.5%±10.222% ▼
Body29%62%59%63.8%±10.029%
T34%58%62%51.1%±11.349% ▲

Optimal v Nuria Parrizas Diaz: +0.1±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +6.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAnna winsv NuriaMatchupOptimal
Wide49%69%69%72.3%±8.564% ▲
Body20%51%51%46.2%±11.55% ▼
T31%63%64%63.1%±11.131%

Optimal v Nuria Parrizas Diaz: +2.0±1.1 per 100 first serves (faults included) over the current mix. Serving wide every time would read +8.0 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.

Nuria Parrizas Diaz returning

1st serve to the forehand

ReturnNowTourOwnv AnnaValue
FH through the middle58%+4.2+0.1+0.8+5.1±3.1
FH crosscourt30%+5.3+0.1+1.0+6.5±4.3
FH down the line12%+1.5−0.5−2.3−1.2±4.4

Lean FH crosscourt: +1.7±3.5 per 100 returns v the current mix (124 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv AnnaValue
BH through the middle50%+6.0+1.1+2.0+9.2±2.8
BH crosscourt37%+7.7+1.4+1.8+10.9±3.7
BH down the line9%+2.2−1.4−1.6−0.8±4.3
BH slice through the middle4%−6.2±0.0−0.3−6.6±2.0

Lean BH crosscourt: +2.5±2.7 per 100 returns v the current mix (142 returns charted, inside the 90% margin)

2nd serve to the forehand

ReturnNowTourOwnv AnnaValue
FH crosscourt43%+0.5+1.2+0.7+2.4±4.3
FH through the middle37%−3.2−0.9+1.5−2.5±3.0
FH down the line19%−0.6+2.1−0.4+1.1±4.3

Lean FH crosscourt: +2.1±2.8 per 100 returns v the current mix (67 returns charted, inside the 90% margin)

Anna Lena Friedsam returning

1st serve to the forehand

ReturnNowTourOwnv NuriaValue
FH through the middle48%+4.2−1.9+0.4+2.7±3.1
FH crosscourt18%+5.3+3.5+3.2+12.1±4.2
FH slice through the middle15%−6.7+0.1±0.0−6.6±1.6
FH down the line14%+1.5−2.7+0.3−0.8±4.4
FH slice down the line5%−10.5+0.6±0.0−9.9±1.5

Lean FH crosscourt: +10.3±3.8 per 100 returns v the current mix (119 returns charted)

1st serve to the backhand

ReturnNowTourOwnv NuriaValue
BH through the middle39%+6.0+1.7+0.7+8.5±2.7
BH crosscourt24%+7.7−1.5−1.6+4.6±3.6
BH slice through the middle19%−6.2−0.7±0.0−6.9±1.8
BH down the line7%+2.2−1.0+1.7+2.9±4.2
BH slice crosscourt5%−4.2−0.4±0.0−4.6±1.5

Lean BH through the middle: +6.0±1.9 per 100 returns v the current mix (157 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv NuriaValue
FH through the middle56%−3.2−4.0+2.0−5.2±3.0
FH crosscourt44%+0.5−1.2+2.8+2.1±3.8

Lean FH crosscourt: +4.1±2.7 per 100 returns v the current mix (41 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv NuriaValue
BH crosscourt52%+1.5+0.4+1.1+3.1±3.5
BH through the middle33%−2.6−0.7−0.1−3.4±2.7
BH down the line15%−0.5−3.0−1.5−5.0±4.4

Lean BH crosscourt: +3.4±2.0 per 100 returns v the current mix (79 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.

Nuria Parrizas Diaz

Favour

ShotEdgeOwnTheirs
FH to their backhand · rally+3.4±3.4−0.3+3.7
BH to the middle · return+2.9±2.5+0.8+2.2
BH to their forehand · rally+2.9±4.2+2.1+0.9
BH to the middle · return +1+2.7±2.6+0.2+2.5
FH to their forehand · serve +1+2.3±4.0+2.3±0.0
BH to their backhand · return+0.6±3.7−0.3+0.9

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−3.8±2.7−1.8−2.0
FH to their forehand · return +1−3.4±4.0−2.1−1.3
FH to their forehand · rally−0.9±2.9+0.1−1.0
FH to their backhand · serve +1−0.8±4.2−2.2+1.4
BH to the middle · rally−0.8±2.2−1.5+0.7

Anna Lena Friedsam

Favour

ShotEdgeOwnTheirs
BH to their backhand · rally+2.5±3.0+1.9+0.6
BH to their forehand · rally+2.4±4.6+2.4±0.0
FH to their backhand · rally+2.1±3.4−0.8+2.9
BH to the middle · serve +1+1.9±2.7±0.0+1.8
FH to the middle · serve +1+1.9±2.8+0.3+1.5
BH to the middle · rally+1.2±2.3+0.9+0.3

Avoid

ShotEdgeOwnTheirs
FH to their forehand · serve +1−2.5±4.1−2.1−0.5
BH slice to their backhand · rally−2.3±2.9−2.2−0.2
FH to the middle · return−1.7±2.8−3.3+1.6
BH to their backhand · return−1.4±3.5−1.5+0.1
BH to their forehand · return−1.3±4.7−2.2+0.9

Against Anna Lena Friedsam-like opponents

Nuria Parrizas Diaz vMatchesServe pts wonReturn pts won
All charted opponents–52.6%46.4%

Similar by tactical fingerprint: Diana Shnaider, Jasmine Paolini, Jil Teichmann, Emma Raducanu, Varvara Gracheva, Yue Yuan, Olivia Gadecki, Ana Bogdan, Andrea Petkovic, Elena Vesnina. When two players have rarely met, their records against these lookalikes fill the gap.