Game plan

Jesper De Jong v Botic Van De Zandschulp

Every number combines what Jesper De Jong does well with what Botic Van De Zandschulp allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Jesper De Jong wins, best of 3 49%90%: 22%–76% · best of 5: 49%

Serve points won 62.7% / 62.9% Jesper / Botic · tour 63.5%

Strengths only, no similarity priors 49%serve 62.7% / 62.9%

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. Both were charted enough in the last three seasons, so those carry the most weight. The result is then nudged by Jesper De Jong's record against Botic Van De Zandschulp'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

Career	Jesper	Botic
Direction choice	−0.14 ±0.06 better than 21%	−0.09 ±0.03 better than 32%
Shot selection	+0.30 ±0.12 better than 80%	+0.08 ±0.08 better than 62%
Execution	−0.72 ±0.35 better than 36%	−1.07 ±0.25 better than 23%
Points left on the table	2.79 ±0.11 lower than 32%	2.53 ±0.06 lower than 58%

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.

Structural compatibility

Expected edge per 100 rally shots from style alone: Jesper De Jong −0.52, Botic Van De Zandschulp −0.83. Each player's shot mix weighted by their own skill with each shot and by how much the other gives up against it. This is why some rankings gaps don't hold in a given matchup.

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.

Jesper De Jong serving

Deuce court

1st serve	Now	Jesper wins	v Botic	Matchup	Optimal
Wide	44%	73%	72%	71.8%±4.1	39% ▼
Body	7%	54%	63%	54.2%±8.6	0% ▼
T	48%	81%	70%	77.4%±4.0	61% ▲

Optimal v Botic Van De Zandschulp: +0.5±0.5 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.2 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Jesper wins	v Botic	Matchup	Optimal
Wide	44%	73%	71%	70.4%±4.4	57% ▲
Body	9%	56%	64%	56.6%±8.8	0% ▼
T	47%	71%	69%	68.4%±4.4	43% ▼

Optimal v Botic Van De Zandschulp: +0.5±0.6 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.

Botic Van De Zandschulp serving

Deuce court

1st serve	Now	Botic wins	v Jesper	Matchup	Optimal
Wide	41%	72%	72%	71.2%±4.2	40% ▼
Body	12%	63%	64%	64.1%±7.2	0% ▼
T	47%	77%	75%	77.4%±3.6	60% ▲

Optimal v Jesper De Jong: +0.7±0.7 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.1 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Botic wins	v Jesper	Matchup	Optimal
Wide	37%	72%	73%	73.1%±4.2	50% ▲
Body	15%	58%	58%	52.0%±8.0	2% ▼
T	47%	70%	64%	61.8%±5.0	48%

Optimal v Jesper De Jong: +0.9±0.7 per 100 first serves (faults included) over the current mix. Serving wide every time would read +8.6 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.

Jesper De Jong returning

1st serve to the forehand

Return	Now	Tour	Own	v Botic	Value
FH through the middle	50%	+4.3	−0.1	−0.1	+4.1±1.8
FH down the line	18%	+1.7	−1.9	−2.1	−2.3±3.6
FH crosscourt	15%	+5.5	+0.1	−3.5	+2.1±3.6
FH slice through the middle	12%	−4.2	−2.1	−1.6	−7.9±2.0
FH slice down the line	5%	−4.3	−0.9	−3.0	−8.2±3.0

Lean FH through the middle: +3.6±1.3 per 100 returns v the current mix (543 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Botic	Value
BH through the middle	37%	+6.4	−0.2	+0.6	+6.8±1.8
BH slice through the middle	18%	−4.2	−1.3	−2.8	−8.3±2.0
BH crosscourt	18%	+8.8	−2.8	−2.8	+3.3±2.7
BH down the line	15%	+4.2	−1.5	−5.8	−3.1±4.0
BH slice crosscourt	8%	+0.5	−0.8	−4.7	−5.0±2.8

Lean BH through the middle: +6.7±1.4 per 100 returns v the current mix (672 returns charted)

2nd serve to the forehand

Return	Now	Tour	Own	v Botic	Value
FH through the middle	61%	−3.5	−0.7	+0.7	−3.5±2.2
FH crosscourt	21%	−0.2	−0.4	−2.5	−3.1±3.7
FH down the line	18%	−1.8	+0.7	−0.4	−1.5±3.9

Lean FH down the line: +1.5±3.5 per 100 returns v the current mix (156 returns charted, inside the 90% margin)

2nd serve to the backhand

Return	Now	Tour	Own	v Botic	Value
BH through the middle	43%	−2.9	±0.0	+0.8	−2.1±1.8
BH crosscourt	26%	+1.0	−0.9	−1.6	−1.5±2.6
FH through the middle	11%	−2.9	+0.9	+0.7	−1.3±1.9
FH inside-out	8%	+1.0	+2.1	−0.4	+2.6±3.1
BH down the line	7%	−0.2	−2.4	−0.1	−2.6±4.5

Lean FH inside-out: +4.4±3.1 per 100 returns v the current mix (442 returns charted)

Botic Van De Zandschulp returning

1st serve to the forehand

Return	Now	Tour	Own	v Jesper	Value
FH through the middle	48%	+4.3	+1.5	+0.2	+5.9±1.8
FH crosscourt	22%	+5.5	−3.9	−3.4	−1.8±3.5
FH down the line	16%	+1.7	−1.6	−2.4	−2.3±3.5
FH slice through the middle	9%	−4.2	−1.9	−1.0	−7.1±2.1
FH slice down the line	3%	−4.3	−4.2	−2.0	−10.4±3.2

Lean FH through the middle: +5.0±1.4 per 100 returns v the current mix (2055 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Jesper	Value
BH through the middle	42%	+6.4	−0.3	−2.1	+4.0±1.7
BH crosscourt	28%	+8.8	−2.7	−1.4	+4.8±2.5
BH slice through the middle	14%	−4.2	−1.4	−2.3	−7.9±2.2
BH down the line	8%	+4.2	−0.9	+0.1	+3.5±4.1
BH slice crosscourt	6%	+0.5	−3.3	−5.2	−7.9±2.9

Lean BH crosscourt: +3.3±2.0 per 100 returns v the current mix (2166 returns charted)

2nd serve to the forehand

Return	Now	Tour	Own	v Jesper	Value
FH through the middle	53%	−3.5	−0.4	−0.8	−4.7±2.2
FH crosscourt	31%	−0.2	−1.8	+0.2	−1.9±4.1
FH down the line	14%	−1.8	−5.4	−2.4	−9.6±4.5
FH slice through the middle	2%	−12.7	−1.2	±0.0	−13.9±1.2

Lean FH crosscourt: +2.8±3.1 per 100 returns v the current mix (449 returns charted, inside the 90% margin)

2nd serve to the backhand

Return	Now	Tour	Own	v Jesper	Value
BH through the middle	48%	−2.9	−2.0	−1.1	−6.0±1.6
BH crosscourt	41%	+1.0	−4.5	−0.3	−3.8±2.3
BH down the line	6%	−0.2	+0.3	−1.0	−0.9±4.8
FH through the middle	2%	−2.9	−0.4	−0.8	−4.1±2.1
FH inside-out	1%	+1.0	−1.9	−2.4	−3.3±3.2

Lean BH down the line: +3.8±4.7 per 100 returns v the current mix (1291 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.

Jesper De Jong

Favour

Shot	Edge	Own	Theirs
FH to the middle · return +1	+3.0±2.0	+0.7	+2.3
BH to their backhand · return +1	+2.6±2.4	+3.0	−0.4
FH to the middle · rally	+2.4±1.2	+1.7	+0.7
BH to the middle · serve +1	+2.0±1.8	+1.3	+0.7
BH to the middle · return +1	+1.5±1.7	+0.5	+1.0
BH to their backhand · rally	+1.5±1.3	+0.5	+1.0

Avoid

Shot	Edge	Own	Theirs
BH volley to their forehand · rally	−9.1±5.5	−5.5	−3.7
BH slice to their forehand · rally	−6.5±3.1	−4.7	−1.8
BH slice to their backhand · return	−5.6±2.7	−1.2	−4.4
BH drop shot to their forehand · rally	−4.8±5.1	−4.7	−0.1
BH to their forehand · return	−4.7±3.5	−1.5	−3.3

Botic Van De Zandschulp

Favour

Shot	Edge	Own	Theirs
BH to the middle · rally	+2.9±1.2	+0.9	+2.0
BH to the middle · return +1	+2.5±1.8	+1.4	+1.1
FH to the middle · rally	+2.4±1.3	+1.1	+1.2
FH to the middle · return +1	+1.9±2.1	+2.0	−0.1
FH to their forehand · rally	+1.3±1.4	+0.4	+0.9
BH to the middle · serve +1	+0.9±1.9	−0.3	+1.2

Avoid

Shot	Edge	Own	Theirs
BH volley to their forehand · rally	−8.8±5.7	−5.3	−3.5
FH volley to their backhand · rally	−6.4±5.3	−2.7	−3.8
FH to their backhand · return	−5.8±2.7	−2.9	−2.9
BH to their backhand · return	−3.7±1.9	−2.9	−0.8
FH to their forehand · return	−3.5±3.2	−1.2	−2.3

Against Botic Van De Zandschulp-like opponents

Jesper De Jong v	Matches	Serve pts won	Return pts won
All charted opponents	–	63.5%	37.3%

Similar by tactical fingerprint: Zhizhen Zhang, Aleksandar Kovacevic, Nuno Borges, Zizou Bergs, Miomir Kecmanovic, Mackenzie Mcdonald, Jordan Thompson, Emil Ruusuvuori, Andreas Seppi. When two players have rarely met, their records against these lookalikes fill the gap.