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Player reportPremier League 2026

Jayden Bogle

Leeds
Ball-winning 6 (destroyer) DM
14.7 defensive actions/90
Capability Analysis
Breaking Pressure
only 48 pressured-passing actions across 3 high-press matches -- not enough sample (needs 5+ matches and 12+ actions)
Progression36%vs 23 defensive mids
"Can he move the team forward with a pass, not just recycle it sideways?"
Progressive passes /904.5652%
Line-breaking passes /901.5961%
Threat added by passing /900.88xT17%
Pass accuracy72.52%13%
Ball-Winning22%vs 23 defensive mids
"How actively does he win the ball back?"
Interceptions /900.9126%
Ball recoveries /904.0313%
Tackles /901.8930%
Duels won /900.8317%
defensive middeep-lying playmakerpress resistancescreening
643
minutes
8 apps
221
passes
69% completed
69%
pass completion
221 passes
17
progressive passes
2.4/90
105
defensive actions
14.7/90
12
tackles + interceptions
67% tackle win
26
recoveries
3.6/90
33
line-breaking passes
4.6/90
Overview

The player

Who he is and how he compares with his peers.

01

What Patterns Define Him?

His repeatable signature. A step only appears if its reliability score (sample size × match coverage) reaches at least Medium confidence — pattern mining, not anecdotes.

RECEIVE
drop between the centre-backs — mostly in the middle third (48% of his 221 passes)
69% completion · 221× in 8/8 matches
↓
ESCAPE PRESSURE
turn out of a tight central area
47% won · 17× in 7/8 matches
↓
PROGRESS CENTRAL
break a line through the middle
2.4 prog/90 · 33× in 8/8 matches
↓
SCREEN / WIN BALL
protect the back four
5.3 ball-wins/90 · 38× in 8/8 matches
↓
RECYCLE / PROGRESS
keep it ticking, feed the final third
2.0 f3-entries/90 · 14× in 7/8 matches
Signature: drop to receive → escape the press on the turn → progress centrally or recycle → screen the counter. Block the central lane and press his first touch to force him backwards.
18

Where is he influential — vs where is he merely present?

Red fill = raw touch territory. Gold rings = zones where his influence (xT added, progression, line-breaks, key passes) outweighs how often he's actually there — one combined map instead of two separate maps to compare by eye. Red with no ring: present but not dangerous. A ring on faint red: rare touches, outsized impact.

own goal left, attacking →
28
passes / match
14.7
def actions / 90
13–43
pass range (matches)
17
clearances
Pass range = his fewest and most passes in any single match this season (13 at the low end, 43 at the high) — a measure of match-to-match involvement, not pass distance.
In possession

In possession

What he does with the ball: build-up, progression, creation, carrying and finishing.

10

How dangerous are his carries?

Real ball-carries

62 tracked carries (8.7/90, 17 progressive, 642m total) — the ball moving with his touches, a different signal from dribbles below (beating an opponent 1v1). even a player who rarely dribbles past a man can still carry the ball forward constantly in build-up; this is that.

2%21%16%29%23%5%2%2%2%
progressivelateral/short% of his 62 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 8m, longest 30m
By zone — where the carry started → where it ended
7Outside → Inside
9Inside → Inside
36Outside → Outside
10Inside → Outside
First (24)Second (22)Third (12)Fourth (4)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →

Beaten in the tackle

How often an attacker gets past him in a 1v1 defensive duel — the closest signal the data has to "dribbled past" (no attacker-beat-defender field exists directly, so this counts tackles he attempted and lost).

9
tackle duels
6
won
3
beaten · 33%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 56%
OUTSIDE 44%
Tackle-duel location — 5 inside · 4 outside
Right Wing
4 · 44%
Right Half-Space
3 · 33%
Central
2 · 22%
Left Half-Space
0 · 0%
Left Wing
0 · 0%
Vision AI beaten in 3 of 9 tackle duels (33% loss rate) — a solid 1v1 defensive record.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →

Dribbles (1v1s)

Can he escape pressure on the ball? His carries/dribbles in tight central areas, by channel. Season rate: 2.38 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 47%
OUTSIDE 53%
Dribble location — 8 inside · 9 outside
Right Wing
9 · 53%
Right Half-Space
5 · 29%
Central
2 · 12%
Left Half-Space
1 · 6%
Left Wing
0 · 0%
Vision AI 47% of his carries are central — he receives and turns in congested midfield zones rather than out wide.
03

How does he build & move the ball?

How does he escape the first line?

13%
vertical passes
8×
2%
switches
1×
43%
carries
26×
42%
short circulation
25×
Answer: he escapes the press primarily through carrying — stepping out with the ball.

How he moves the ball — his 4 busiest progression routes, not where every pass starts and ends separately. Arrow width = how often, colour = xT gained, dashed = switch of play. The full breakdown is in the lane matrix below.

own goal left, attacking →
Lane transition matrix — when he receives in a lane, where does it go?
TO →RWRHSCLHSLWRW10952%5738%416%73%31%1RHS3129%935%1123%710%33%1C1010%180%810%1LHS250%150%1LW0FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: the right wing in the final third → the right half-space in the final third — 6 progressive passes (19% of his progression) at 0.100 xT each. He moves it inside.

His progression is inward: 61% of progressive passes move the ball toward the middle versus 6% going wider — he cuts in rather than holding width.

Only 7% of his passes switch play, so his threat is same-side — contain the flank he occupies and the route closes.

Quality behind the volume: 10 line-breaking passes and 14 final-third entries, 3.3 total xT added.

Origin and destination are measured on the same event row — no receiver inference. Receiver identity is not recoverable from this data source.
All passes — origin zone share
Filter: from to
5%12%19%25%22%8%0%1%4%0%4%0%
completedincomplete221 passes · any zone → any zone · own goal left, attacking →
221
passes
69%
completed
69
lost
Vision AIIn line with his 69% season completion rate.
05

How does he progress play?

How much he drives the ball forward. Progressive = completed pass advancing ≥15 toward goal.

17
progressive · 2.4/90
14
final-third entries · 2.0/90
7
box entries · 0.98/90
16
progression index /90
Progression index: one composite number — progressive passes + progressive carries + 2% of total distance progressed + 8× positive xT added, all per 90. Weights VOLUME and THREAT together rather than counting progressive actions alone.
11

How does he create chances?

6 key passes (0.84/90), 0 of them assists — where his chance creation specifically comes from, 18 zones (6×3), showing his share of key passes originating there.

Chance creation — key pass origin zone share
Filter:
17%33%33%17%
chance creation (6)assist (0)% of the selected group's key passes originating in each zone
04

Where does he become vulnerable?

78 times he gave the ball away. For a defender the danger is where — a loss in his own third can turn into a chance against; higher up it costs little.

34
attacking third (cheap)
26
middle third
18
own third (dangerous)
Vision AI 44% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 3.53 danger-index/90 · 0.324 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
06

What is his passing profile?

221
passes attempted
45%
mostly forward
52%
mostly short
Direction
Forward
99 · 45%
Sideways
54 · 24%
Backward
68 · 31%
Length (completed)
Short (<15m)
79 · 52%
Medium
63 · 41%
Long (>30m)
10 · 7%
07

Preferred Progression Routes — xT-weighted

His progressive passes as zone→zone routes, weighted by expected threat (xT) added — arrow width and the number are the total xT generated on each route, not just how often he plays it. This is where he actually moves the needle.

0.520.480.220.160.140.12
own goal left, attacking →
Highest-value routes (xT)
0.52
Right Wing Att third → Left Half-Space Att third
2 passes · 1 to a shot
0.48
Right Wing Att third → Right Half-Space Att third
2 passes
0.22
Right Wing Mid third → Right Wing Att third
2 passes
0.16
Right Half-Space Def third → Right Wing Mid third
1 passes
0.14
Right Wing Mid third → Left Half-Space Att third
1 passes
0.12
Right Wing Mid third → Left Wing Att third
1 passes
08

Where Does He Receive?

The zones where Jayden Bogle gets on the ball — his top three ball-collection areas highlighted (gold = primary). Reception is proxied by where his on-ball actions begin (no explicit receiver is recorded).

123
1 = primary, 2 = secondary, 3 = third · own goal left, attacking →
His collection zones
34%
Primary
Right Wing, Middle third
23%
Secondary
Right Wing, Attacking third
13%
Third
Right Wing, Defensive third
These are the zones where he collected the ball most.
09

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Jayden Bogle actually gets on the ball. Hover any zone for its breakdown by action type, its share of all touches, and the exact coordinate range it covers.

Filter:
111381147112942605119
own goal left, attacking → · brighter + higher number = more touches

Passes only — completed vs incomplete, by zone

Same zone grid, restricted to passes so completed/incomplete and match filters actually mean something — a shot or a dribble has no "completed" in the pass sense.

5%12%19%25%22%8%0%1%4%0%4%0%
own goal left, attacking →
12

Every Pass This Season — completed vs incomplete

Every pass this season, plotted individually — green = completed, grey (dashed) = incomplete, gold = key pass. Filter by outcome or isolate one match below.

6Key pass
12Cross
5Cutback
17Progressive
33Long ball
7Switch
By zone — where the pass started → where it landed
51Outside → Inside
32Inside → Inside
58Outside → Outside
11Inside → Outside
By direction
99Forward
68Backward
54Sideways
own goal left, attacking →
02

Tactical patterns — how his football actually looks

Three clustered sequence diagrams from his own event data — his three busiest routes: the way he progresses, the pattern behind his chances, and where a turnover turns dangerous.

own goal left, attacking →
How does he progress the ball forward?
His most common route for progressing play: he plays inside from the right wing toward the left hs in the final third — 2 passes worth 0.52 xT.
Where do his chances come from?
Of 6 key passes, his busiest route is a delivery where he switches it out from the right hs to the left wing in the middle third — 1 times. The receiver isn't identifiable in this data, only where the pass started and ended.
Where does he lose the ball most?
This is a RATE, not a raw count — the share of his touches in each zone that end in a turnover, so a zone he simply plays in more often doesn't automatically look riskier. His weakest zone is the right half-space in the final third: 56% of his 16 touches there are lost (9 times).
47%14/30 lost25%2/8 lost—1 touch · too few—1 touch · too few—0 touches · too few25%19/76 lost14%3/21 lost12%1/8 lost—1 touch · too few—0 touches · too few31%16/52 lost56%9/16 lost—7 touches · too few—0 touches · too few—0 touches · too fewRWRHSCLHSLWDEFMIDATT
13

Crosses & Cutbacks

12 crosses (1.68/90, 4 completed) and 5 cutbacks (0.70/90, 1 completed) — two separate wide-delivery patterns into the box, each its own map with a completed/failed filter. Neither is a tagged event, so both are inferred from pass geometry — the intended end point of a failed attempt is still real data (an interception doesn’t erase where the ball was aimed): a cross is a pass aimed into the box starting from a wide channel; a cutback starts almost on the byline but is squared back rather than driven forward, aimed centrally around the box. The completed-cross count was checked against this platform’s own real match-level cross totals and lands within about 1 cross of the true count.

Crosses — close-up on the final third
Cutbacks — close-up on the final third
completedfailed (dashed)close-up on the box — attacking ↑ toward goal
Out of possession

Out of possession

Where and how he defends and presses.

14

How & where does he defend?

105 defensive actions across the season (14.7/90). Where he wins the ball, and how — the core question for a defender. Aerial duels are not recorded for this competition, so aerial dominance is not measured here.

click a card to isolate that action type · own goal left, attacking →
9
tackles · 67% won
3
interceptions · 0.4/90
26
recoveries · 3.6/90
17
clearances · 2.4/90
4
blocks
37
avg action height
21
won high (att 3rd)
32
middle third
52
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 38 proactive ball-wins (5.3/90), tackle success 67%. He defends mostly around the middle third.
15

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Jayden Bogle still play out when the opponent presses high? His build-up quality split by press intensity — the key question for a ball-playing defender. Tiers of ~2-4 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 3.1, 2m)
60%
2.8
7.1
0.53
Mid press (PPDA 3.9, 2m)
76%
1.5
5.1
0.70
Low press (PPDA 5.5, 4m)
69%
2.7
3.5
1.00
Team

Team context

How much of the team runs through him, and what changes without him.

16

Impact on the Team

Insufficient sample: Jayden Bogle played nearly every Leeds match in the loaded data, so there is no meaningful "without him" comparison yet. This section fills in as more matches (and the rest of the season) are scraped.

17

His Share of the Team

Of everything Leeds produced this season, the categories where the biggest share ran through Jayden Bogle specifically — his share of the team total, not a per-90 rate.

category
share
him / team
goals
25%
2 / 8
progressive passes
9%
181 / 2125
box entries
8%
54 / 668
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

19

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 258 defensive mids in the pool (min 450 min). This is what separates players who post similar numbers but play differently. Proxy dimensions are inferred from on-ball data; true off-ball running / under-pressure context is not measured.

Deep-lying playmaker23%Ball-winning 619%Tempo controller16%
Why Deep-lying playmaker 23%: a weighted blend of progression 67 (weight 30%) + press resistance 27 (weight 20%) + build-up 12 (weight 30%) + retention 11 (weight 20%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
territory (wide vs central), through-balls
Strong
line-breaking, box threat
Average
progression, crossing, dribbling, final-third threat, carrying
Weak
passing directness, transition, creativity, press resistance, ball-winning, receiving zones, defensive aggression, build-up, retention
Unknown
aerial ability, marking, off-ball running — not in event data
Territory (wide vs central)
91
Through-balls ~proxy
88
Line-breaking
82
Box threat
72
Progression
67
Crossing
63
Dribbling
52
Final-third threat
46
Carrying
44
Passing directness
37
Transition ~proxy
35
Creativity
34
Press resistance ~proxy
27
Ball-winning
23
Receiving zones
23
Defensive aggression
22
Build-up
12
Retention
11
20

Similar Players — in style space

Closest comparables measured on the style scores above, within the same position family — so it separates how players are alike, not just how much they touch the ball. Each line explains the shared strength and the divergent mechanism. A light physical-profile term (height / weight; this player: 178 cm / 69 kg) is included at a quarter of one style axis's weight — enough to break ties between stylistic twins, not to override style. Scope: pooled across the Premier League, Bundesliga, La Liga, Ligue 1 and Serie A, percentiled within each player's own league before comparing — a match from another league is marked with its league name.

Style, not quality: a high match here means two players tend to produce the ball in similar ways — it is not a ranking, a scouting recommendation, or a claim that they are equally good.

Deiver Machado Nantes · Ligue 1 25/26 · 180 cm / 75 kg
88%
Driven by: defensive aggression (16%), build-up (16%), retention (13%). Different mechanism — Machado more via creativity.
Lilian Raolisoa Angers · Ligue 1 · 178 cm / 70 kg
85%
Driven by: build-up (20%), retention (16%), territory (wide vs central) (13%). Different mechanism — Bogle more via box threat, through-balls; Raolisoa more via carrying, creativity.
Giorgi Gocholeishvili Hamburg · Bundesliga 25/26 · 178 cm / 70 kg
83%
Driven by: defensive aggression (17%), territory (wide vs central) (14%), build-up (12%). Different mechanism — Gocholeishvili more via retention, dribbling.
Janik Haberer Union Berlin · Bundesliga · 186 cm / 78 kg
83%
Driven by: retention (12%), through-balls (11%), build-up (10%). Different mechanism — Bogle more via carrying, dribbling; Haberer more via final-third threat, build-up.
Antonio Sánchez Mallorca · La Liga 25/26 · 179 cm / 78 kg
80%
Driven by: build-up (24%), retention (17%), territory (wide vs central) (13%). Different mechanism — Bogle more via box threat, line-breaking; Sánchez more via transition, passing directness.
Tyrick Mitchell Crystal Palace · 175 cm / 68 kg
80%
Driven by: retention (20%), build-up (17%), territory (wide vs central) (14%). Different mechanism — Bogle more via through-balls, box threat; Mitchell more via ball-winning.
21

Summary

Jayden Bogle is a deep-lying playmaker: 69% completion, 33 line-breaks and 2.4 progressive passes /90, resisting pressure with 47% dribble success. A central controller. [Off-ball screening position and scanning need tracking data.]

Based on 8 matches (643 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a deep-lying playmaker — best used in a system built around that identity. His biggest room for growth is retention — even a modest improvement there would meaningfully lift his overall deep-lying playmaker profile.
✨ This report is interactive

Click any stat card to filter its map, hover a dot for the exact match, and use the dropdowns to slice passes zone-to-zone. Nothing here is static.

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