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
Left Wing, Attacking third — between the lines — mostly in the attacking third (50% of his 145 passes)
60% completion · 145× in 8/8 matches
↓
TURN / BEAT MAN
face forward in the pocket
21% won · 28× in 8/8 matches
↓
FINISH
arrive and shoot from central zones
3 goals · 2.14 xG · 18× in 6/8 matches
Signature: Receive → Turn / Beat Man → Finish — the only steps proven repeatable this season (3 of 4 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: create — 1× (insufficient confidence, hidden — not enough evidence yet) — omitted from the signature rather than presented as one.
17
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 →
18
passes / match
3.5
dribbles / match
8–30
pass range (matches)
1–7
dribble range (matches)
Pass range = his fewest and most passes in any single match this season (8 at the low end, 30 at the high) — a measure of match-to-match involvement, not pass distance. Dribble range works the same way, for dribbles/carries per match.
In possession
In possession
What he does with the ball: build-up, progression, creation, carrying and finishing.
32 tracked carries (4.6/90, 11 progressive, 354m total) — the ball moving with his touches, a different signal from dribbles below (beating an opponent 1v1). this counts every touch-carry, not just his dribble attempts below — a fuller picture of how much of his ball-carrying is control-and-move rather than beating a man.
progressivelateral/short% of his 32 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 9m, longest 33m
By zone — where the carry started → where it ended
First (22)Second (10)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Dribbles (1v1s)
Does he carry to create or drift wide? Dribbles by channel. Season rate: 3.99 dribbles attempted /90.
brighter band = more dribbles · own goal left, attacking →
INSIDE 29%
OUTSIDE 71%
Dribble location — 8 inside · 20 outside
Right Wing
4 · 14%
Right Half-Space
0 · 0%
Central
2 · 7%
Left Half-Space
6 · 21%
Left Wing
16 · 57%
Vision AI His carries cluster wide — a drifting playmaker.
02
How does he create chances?
1 key passes (0.14/90), 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:
chance creation (1)assist (0)% of the selected group's key passes originating in each zone
Box deliveries — key passes reaching the final third, by flank
from the left (1)from the right (0)of 1 key passes landing in the final thirdattacking ↑ toward goal
11
Can he finish?
18 shots · 2.14 xG · 3 goals (+0.86 vs xG). Mostly right-footed. Circle size = xG.
shots 18 on target 12 goals 3 xG 2.14 xG on target 1.46 xG / shot 0.119
Where he shoots from — click an area of the box
10
Where does he become vulnerable?
80 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.
43
attacking third (cheap)
27
middle third
10
own third (dangerous)
Vision AI 54% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 2.61 danger-index/90 · 0.228 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
03
Where Does He Receive?
The zones where Kevin Schade 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).
1 = primary, 2 = secondary, 3 = third · own goal left, attacking →
His collection zones
24%
Primary
Left Wing, Attacking third
16%
Secondary
Left Half-Space, Attacking third
16%
Third
Left Wing, Middle third
These are the zones where he collected the ball most.
04
Where Does He Operate? — Every Zone
Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Kevin Schade 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:
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.
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.
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 →
Where do his chances come from?
Of 1 key passes, his busiest route is a delivery where he plays straight through the left hs in the final 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 left wing in the final third: 49% of his 35 touches there are lost (17 times).
06
Does he carry inside or outside — his ball-carries across the pitch
Four arrows, one per movement class of his ball-carries: outside→inside (cutting in with the ball), inside→outside (carrying wide), outside→outside (down the touchline) and inside→inside (through the middle). Each count is measured from the carry's real start and end coordinates.
own goal left, attacking →
Across 32 ball-carries, his dominant tendency is that he drives along the touchline (38%). He carries from outside into the middle 5 times and out toward the touchline 4 — balanced between cutting in and holding width.
08
What happens right after he carries the ball
Every carry's end point matched against his own very next pass or shot in the same match, when one starts almost exactly there — the direct continuation of that touch, not a separate stat. “No clean link” means no pass or shot of his own started close enough to count (often the carry ended in a tackle or a loss); it isn't a claim about exactly what happened, only that nothing traceable followed.
Shot
1 · 3%
Progressive / key pass
6 · 19%
Simple pass
9 · 28%
No clean link
16 · 50%
Of 32 carries, 3% flow straight into a shot of his own, 19% into a key or progressive pass — a genuine end product to the carry, not just ball retention. 50% have no clean link to a next touch of his own close to where the carry ended.
09
Crosses & Cutbacks
5 crosses (0.71/90, 1 completed) and 8 cutbacks (1.14/90, 2 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
104 defensive actions across the season (14.8/90). 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 →
12
tackles · 67% won
1
interceptions · 0.1/90
29
recoveries · 4.1/90
10
clearances · 1.4/90
2
blocks
47
avg action height
29
won high (att 3rd)
41
middle third
34
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 42 proactive ball-wins (6.0/90), tackle success 67%. He defends high, stepping out to intercept — suits a high line.
Defensive work in the attacking half
Ball-wins in the attacking half only (own half vs. attacking half, a simple 2-way split, not the usual thirds) — the clearest single signal of how much he presses and recovers the ball high up the pitch.
51
attacking-half actions · 7.27/90
13
Against Different Pressing Intensities
Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Kevin Schade keep producing when the game is tight and the press is high? Tiers of ~2-4 matches — directional evidence, not proof.
press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 3.0, 2m)
0.76
0.5
0.47
12%
Mid press (PPDA 3.8, 2m)
0.37
1.2
0.00
22%
Low press (PPDA 4.3, 4m)
0.36
1.5
0.00
27%
Team
Team context
How much of the team runs through him, and what changes without him.
Insufficient sample: Kevin Schade played nearly every Brentford 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.
16
His Share of the Team
Of everything Brentford produced this season, the categories where the biggest share ran through Kevin Schade specifically — his share of the team total, not a per-90 rate.
category
share
him / team
goals
21%
3 / 14
expected goals (xG)
14%
11.4 / 82.1
shots
11%
75 / 675
Recruitment
Style and verdict
Style profile, closest comparables, and the summary.
Not raw event counts — football style scores: weighted models scored 0–100 against the 247 attacking 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.
Advanced playmaker (8)19%Half-space creator19%
Why Advanced playmaker (8) 19%: a weighted blend of box threat 63 (weight 15%) + creativity 21 (weight 35%) + progression 15 (weight 25%) + final-third threat 11 (weight 25%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
passing directness
Strong
defensive aggression
Average
box threat, territory (wide vs central), ball-winning, transition
aerial ability, marking, off-ball running — not in event data
Passing directness
92
Defensive aggression
73
Box threat
63
Territory (wide vs central)
54
Ball-winning
54
Transition ~proxy
41
Build-up
34
Crossing
29
Creativity
21
Line-breaking
19
Through-balls ~proxy
17
Press resistance ~proxy
16
Progression
15
Dribbling
13
Carrying
12
Receiving zones
12
Final-third threat
11
Retention
9
19
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: 183 cm / 74 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.
Vítinha Genoa · Serie A · 178 cm / 74 kg
89%
Driven by: retention (12%), final-third threat (10%), receiving zones (10%). Different mechanism — Vítinha more via dribbling, carrying.
Jens Odgaard Bologna · Serie A · 188 cm / 83 kg
89%
Driven by: progression (11%), creativity (10%), final-third threat (10%). Different mechanism — Schade more via territory (wide vs central); Odgaard more via retention.
Ismaïla Sarr Crystal Palace · 185 cm / 76 kg
87%
Driven by: press resistance (14%), retention (10%), dribbling (10%). Different mechanism — Schade more via territory (wide vs central), defensive aggression.
Brennan Johnson Everton · 186 cm / 73 kg
86%
Driven by: press resistance (12%), retention (11%), progression (10%). Different mechanism — Schade more via box threat, passing directness.
Omri Gandelman Lecce · Serie A · 188 cm / 84 kg
85%
Driven by: press resistance (11%), retention (9%), dribbling (9%). Different mechanism — Schade more via box threat, ball-winning.
Federico Chiesa Liverpool · 175 cm / 70 kg
85%
Driven by: press resistance (14%), retention (12%), dribbling (12%). Different mechanism — Schade more via defensive aggression; Chiesa more via receiving zones, carrying.
20
Summary
Kevin Schade is an advanced playmaker (8): 0.14 key passes /90, 1.1 progressive passes, 3 goals from 2.14 xG. A between-the-lines creator. [Off-ball movement into pockets needs tracking.]
Based on 8 matches (631 minutes) — an early read, treat with caution until more minutes are logged. He profiles as an advanced playmaker (8) — best used in a system built around that identity.
His biggest room for growth is final-third threat — even a modest improvement there would meaningfully lift his overall advanced playmaker (8) 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.