RallyIQ

Game plan

Jiri Novak v Magnus Norman

Every number combines what Jiri Novak does well with what Magnus Norman allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Jiri Novak wins, best of 3 65%90%: 32%–89% · best of 5: 69%
Serve points won 63.7% / 60.6% Jiri / Magnus · tour 63.4%
Strengths only, no similarity priors 62%serve 63.4% / 60.9%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Jiri Novak's record against Magnus Norman's tactical lookalikes and in their charted head-to-heads (lookalikes: +8.1 on serve, +9.0 on return vs expectation (117 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

CareerJiriMagnus
Direction choice−0.07 ±0.09
better than 40%
+0.12 ±0.08
better than 85%
Shot selection−0.11 ±0.18
better than 39%
+0.05 ±0.12
better than 60%
Execution−0.16 ±0.53
better than 59%
−0.12 ±0.82
better than 62%
Points left on the table2.47 ±0.19
lower than 65%
2.17 ±0.13
lower than 94%

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.

Jiri Novak serving

Deuce court

1st serveNowJiri winsv MagnusMatchupOptimal
Wide57%66%71%64.5%±9.351% ▼
Body8%62%65%63.8%±15.00% ▼
T36%65%79%70.7%±9.349% ▲

Optimal v Magnus Norman: +0.2±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJiri winsv MagnusMatchupOptimal
Wide45%71%74%72.2%±8.732% ▼
Body14%59%72%68.6%±13.814%
T41%63%74%65.8%±10.254% ▲

Optimal v Magnus Norman: +0.2±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.1 per 100 first serves in before the returner adjusts.

Magnus Norman serving

Deuce court

1st serveNowMagnus winsv JiriMatchupOptimal
Wide47%71%74%71.5%±8.060% ▲
Body15%56%67%60.0%±14.32% ▼
T38%76%77%78.1%±8.638%

Optimal v Jiri Novak: +0.8±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMagnus winsv JiriMatchupOptimal
Wide49%68%74%69.3%±8.762% ▲
Body15%66%64%67.4%±14.115%
T36%64%68%59.1%±10.923% ▼

Optimal v Jiri Novak: +0.4±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.9 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.

Jiri Novak returning

1st serve to the forehand

ReturnNowTourOwnv MagnusValue
FH through the middle51%+4.3+0.4+0.2+4.9±2.9
FH down the line35%+1.7+2.0+4.1+7.7±4.4
FH crosscourt14%+5.5+1.4−0.6+6.3±4.4

Lean FH down the line: +1.6±3.3 per 100 returns v the current mix (228 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv MagnusValue
BH through the middle31%+6.4+0.5+0.6+7.5±2.9
BH crosscourt19%+8.8+0.9−1.2+8.5±3.6
BH slice through the middle19%−4.2+0.4+0.3−3.5±2.5
BH slice crosscourt15%+0.5−0.3−2.0−1.8±2.8
BH down the line9%+4.2+0.2−2.1+2.3±3.9

Lean BH crosscourt: +6.0±3.1 per 100 returns v the current mix (216 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MagnusValue
FH through the middle48%−3.5+1.0±0.0−2.5±2.8
FH down the line34%−1.8−0.6+1.0−1.4±4.3
FH crosscourt17%−0.2+1.0+0.5+1.3±3.8

Lean FH crosscourt: +2.8±3.7 per 100 returns v the current mix (87 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MagnusValue
BH crosscourt41%+1.0−0.1−0.5+0.4±3.2
BH through the middle38%−2.9+0.2+1.3−1.4±2.5
BH down the line15%−0.2−0.3+2.4+1.9±4.8
BH slice crosscourt3%−4.0−0.6±0.0−4.6±1.1
BH slice through the middle3%−11.3+0.3+0.4−10.6±1.4

Lean BH down the line: +2.4±4.4 per 100 returns v the current mix (165 returns charted, inside the 90% margin)

Magnus Norman returning

1st serve to the forehand

ReturnNowTourOwnv JiriValue
FH through the middle44%+4.3−1.3−1.3+1.6±2.9
FH crosscourt35%+5.5−1.8+1.4+5.1±4.4
FH down the line15%+1.7−2.1+1.6+1.1±4.2
FH slice through the middle6%−4.2+0.5+3.0−0.7±2.0

Lean FH crosscourt: +2.5±3.2 per 100 returns v the current mix (117 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JiriValue
BH through the middle33%+6.4−1.6−2.2+2.7±2.9
BH crosscourt28%+8.8+0.4+1.3+10.5±3.6
BH slice through the middle19%−4.2+0.9+1.3−2.1±2.4
BH slice crosscourt9%+0.5−0.8+2.8+2.6±2.8
BH down the line7%+4.2−0.1−0.4+3.7±3.9

Lean BH crosscourt: +7.0±2.8 per 100 returns v the current mix (155 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JiriValue
BH crosscourt49%+1.0+1.4+0.2+2.6±3.3
BH through the middle38%−2.9+2.3−0.8−1.4±2.6
BH down the line12%−0.2+1.5−3.6−2.3±4.4

Lean BH crosscourt: +2.1±2.0 per 100 returns v the current mix (130 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.

Jiri Novak

Favour

ShotEdgeOwnTheirs
FH to their forehand · return+2.1±4.7+2.0+0.2
FH to the middle · return+1.4±2.6+0.4+1.0
FH to their backhand · serve +1+1.1±3.5+1.3−0.2
BH to the middle · return+0.9±2.4+0.4+0.4
FH to their forehand · return +1+0.9±4.4−0.6+1.4
FH to the middle · rally±0.0±2.3−1.3+1.3

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−3.7±4.1−0.4−3.3
FH to their forehand · serve +1−3.1±3.9−1.5−1.5
BH to the middle · rally−2.5±2.1−2.7+0.2
BH to their backhand · serve +1−2.2±3.0−1.4−0.8
BH to their backhand · return−1.3±3.2+0.6−1.8

Magnus Norman

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+1.0±2.8+0.2+0.8
BH to their backhand · serve +1+0.9±3.4+1.7−0.8
BH to their backhand · return +1+0.7±3.4+0.6+0.2
FH to their backhand · serve +1+0.7±3.5+0.1+0.5
BH to their backhand · rally+0.5±2.2+0.4+0.1
BH to the middle · rally±0.0±2.1+0.5−0.5

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−5.6±4.2−3.6−2.0
FH to their backhand · return +1−4.5±4.2−2.2−2.4
FH to their forehand · serve +1−3.4±3.9−3.0−0.4
FH to the middle · rally−3.4±2.3−1.5−2.0
BH to the middle · return−2.5±2.4−0.6−1.9

Against Magnus Norman-like opponents

Jiri Novak vMatchesServe pts wonReturn pts won
All charted opponents–60.8%35.8%
Players most similar to Magnus Norman1 69.0%45.8%

Similar by tactical fingerprint: Valentin Vacherot, Tommy Paul, Laslo Djere, Roman Safiullin, David Goffin, Kei Nishikori, Ilya Ivashka, Kyle Edmund, Andre Agassi, Arnaud Clement. When two players have rarely met, their records against these lookalikes fill the gap.