RallyIQ

Game plan

Taylor Fritz v Andreas Seppi

Every number combines what Taylor Fritz does well with what Andreas Seppi allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Taylor Fritz wins, best of 3 75%90%: 52%–90% · best of 5: 80%
Serve points won 68.2% / 62.8% Taylor / Andreas · tour 63.4%
Strengths only, no similarity priors 78%serve 68.1% / 61.9%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Taylor Fritz's record against Andreas Seppi's tactical lookalikes and in their charted head-to-heads (lookalikes: +1.1 on serve, −12.4 on return vs expectation (247 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

CareerTaylorAndreas
Direction choice+0.03 ±0.04
better than 64%
−0.08 ±0.05
better than 36%
Shot selection−0.11 ±0.06
better than 38%
−0.27 ±0.12
better than 26%
Execution+0.66 ±0.27
better than 88%
−0.27 ±0.42
better than 54%
Points left on the table2.35 ±0.06
lower than 78%
2.46 ±0.08
lower than 67%

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.

Taylor Fritz serving

Deuce court

1st serveNowTaylor winsv AndreasMatchupOptimal
Wide48%76%72%75.7%±3.838% ▼
Body3%66%64%66.3%±9.90% ▼
T49%82%78%84.3%±3.162% ▲

Optimal v Andreas Seppi: +0.3±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowTaylor winsv AndreasMatchupOptimal
Wide52%80%79%84.6%±3.165% ▲
Body4%62%65%64.0%±10.40% ▼
T45%76%75%78.9%±3.935% ▼

Optimal v Andreas Seppi: +0.4±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.3 per 100 first serves in before the returner adjusts.

Andreas Seppi serving

Deuce court

1st serveNowAndreas winsv TaylorMatchupOptimal
Wide48%68%74%69.2%±4.261% ▲
Body4%62%63%62.5%±11.10% ▼
T49%72%77%74.9%±4.239% ▼

Optimal v Taylor Fritz: +0.3±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAndreas winsv TaylorMatchupOptimal
Wide49%72%76%75.5%±4.162% ▲
Body6%55%63%54.6%±10.60% ▼
T45%67%74%68.3%±4.638% ▼

Optimal v Taylor Fritz: +0.6±0.6 per 100 first serves (faults included) over the current mix. Serving wide every time would read +4.5 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.

Taylor Fritz returning

1st serve to the forehand

ReturnNowTourOwnv AndreasValue
FH through the middle46%+4.3+1.3+1.9+7.4±1.7
FH down the line22%+1.7+0.4−1.5+0.6±3.4
FH slice through the middle12%−4.2+0.1−1.3−5.4±2.0
FH crosscourt10%+5.5+1.8+0.8+8.1±3.7
FH slice down the line7%−4.3+0.4±0.0−3.9±2.4

Lean FH crosscourt: +4.7±3.5 per 100 returns v the current mix (2456 returns charted)

1st serve to the backhand

ReturnNowTourOwnv AndreasValue
BH through the middle47%+6.4+2.1−1.2+7.3±1.8
BH crosscourt29%+8.8−1.8+6.1+13.1±2.8
BH down the line9%+4.2+1.7+1.9+7.8±4.2
BH slice through the middle9%−4.2−2.5+0.2−6.5±2.2
BH slice crosscourt3%+0.5−3.9+1.3−2.1±3.0

Lean BH crosscourt: +6.2±2.2 per 100 returns v the current mix (2022 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv AndreasValue
FH through the middle51%−3.5−0.7−1.0−5.2±2.3
FH down the line25%−1.8−3.4+3.1−2.1±4.3
FH crosscourt14%−0.2+1.8+1.3+2.9±4.2
FH slice through the middle4%−12.7−1.6±0.0−14.3±1.6
FH slice down the line3%−9.4+1.8±0.0−7.6±2.1

Lean FH crosscourt: +6.5±4.0 per 100 returns v the current mix (707 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv AndreasValue
BH through the middle42%−2.9+0.8+1.2−0.9±1.7
BH crosscourt34%+1.0−0.8+1.4+1.6±2.3
BH down the line13%−0.2−1.3+2.9+1.5±4.6
FH through the middle6%−2.9+0.2−1.0−3.7±2.3
FH inside-in3%+0.6−0.5+1.3+1.4±4.4

Lean BH crosscourt: +1.5±1.8 per 100 returns v the current mix (1417 returns charted, inside the 90% margin)

Andreas Seppi returning

1st serve to the forehand

ReturnNowTourOwnv TaylorValue
FH through the middle50%+4.3+0.8−0.6+4.5±1.9
FH down the line21%+1.7−0.7−0.9+0.2±3.7
FH crosscourt19%+5.5−0.1−0.6+4.8±3.7
FH slice through the middle5%−4.2−0.8±0.0−5.0±1.9
FH slice down the line2%−4.3−3.1+1.3−6.1±2.7

Lean FH crosscourt: +2.1±3.3 per 100 returns v the current mix (470 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv TaylorValue
BH through the middle34%+6.4±0.0+0.6+7.1±2.0
BH slice through the middle25%−4.2−2.3−0.3−6.8±2.0
BH crosscourt18%+8.8+1.4−0.5+9.7±3.0
BH slice crosscourt8%+0.5−1.5−1.8−2.8±2.7
BH slice down the line8%−8.4−1.8+0.2−10.0±3.4

Lean BH crosscourt: +8.3±2.6 per 100 returns v the current mix (479 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv TaylorValue
FH through the middle50%−3.5+1.4+0.4−1.7±2.3
FH down the line28%−1.8−0.1−1.6−3.5±4.0
FH crosscourt22%−0.2−1.0−1.1−2.3±3.8

Lean FH through the middle: +0.6±1.8 per 100 returns v the current mix (127 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv TaylorValue
BH through the middle43%−2.9−0.3+0.8−2.3±1.8
BH crosscourt37%+1.0+2.2−0.9+2.4±2.4
BH down the line13%−0.2+2.4−0.4+1.9±4.4
BH slice through the middle2%−11.3−2.1−0.4−13.8±2.1
FH inside-in2%+0.6−0.5−1.1−1.1±3.0

Lean BH crosscourt: +2.7±1.8 per 100 returns v the current mix (338 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.

Taylor Fritz

Favour

ShotEdgeOwnTheirs
BH to their forehand · return+3.3±3.6+0.4+2.9
FH to their forehand · return+2.7±3.3+1.6+1.2
BH to their backhand · return+2.4±2.0−0.4+2.8
FH to the middle · return+2.4±1.5+0.8+1.6
BH to their backhand · serve +1+1.7±2.2−0.6+2.3
FH to their forehand · serve +1+1.6±2.4−0.1+1.7

Avoid

ShotEdgeOwnTheirs
BH slice to their backhand · return +1−3.8±2.7−3.0−0.8
BH slice to the middle · rally−3.8±2.0−3.9+0.1
BH slice to their backhand · rally−3.7±2.0−3.7+0.1
BH slice to the middle · return +1−3.0±2.3−1.9−1.2
BH to their forehand · return +1−3.0±4.1+0.5−3.5

Andreas Seppi

Favour

ShotEdgeOwnTheirs
BH to their forehand · serve +1+3.2±4.0+1.7+1.5
BH to their backhand · serve +1+2.6±2.2+1.6+1.0
FH to their backhand · serve +1+1.8±2.0+0.5+1.4
BH to their forehand · rally+1.3±2.7−0.3+1.6
BH to their backhand · rally+1.2±1.3+0.2+1.1
BH to the middle · return +1+1.0±1.9+0.8+0.2

Avoid

ShotEdgeOwnTheirs
BH to their forehand · return +1−2.7±4.3+0.2−2.9
FH to their backhand · return +1−2.7±3.1−0.2−2.5
BH slice to the middle · return−2.3±1.9−2.5+0.2
FH to their backhand · rally−2.2±1.6−1.6−0.6
BH to their forehand · return−2.1±3.6+0.6−2.7

Against Andreas Seppi-like opponents

Taylor Fritz vMatchesServe pts wonReturn pts won
All charted opponents–68.5%34.5%
Players most similar to Andreas Seppi1 69.2%23.1%

Similar by tactical fingerprint: Gael Monfils, Marcos Giron, Rinky Hijikata, Alexandre Muller, Arthur Cazaux, Borna Coric, Andy Murray, Karim Mohamed Maamoun, Marcos Baghdatis. When two players have rarely met, their records against these lookalikes fill the gap.