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
Right Wing, Attacking third — between the lines — mostly in the attacking third (49% of his 82 passes)
71% completion · 82× in 6/6 matches
↓
TURN / BEAT MAN
face forward in the pocket
25% won · 4× in 2/6 matches
↓
CREATE
through-ball, cut-back, key pass
3.20/90 · 7× in 3/6 matches
↓
FINISH
arrive and shoot from central zones
0 goals · 0.34 xG · 5× in 3/6 matches
Signature: receive between the lines → turn → create or finish.
In possession
In possession
What he does with the ball: build-up, progression, creation, carrying and finishing.
30 tracked carries (13.7/90, 10 progressive, 340m 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 30 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 10m, longest 27m
By zone — where the carry started → where it ended
First (16)Second (14)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Dribbles (1v1s)
Only 4 dribbles attempted this season — too little volume to map a location pattern.
02
How does he create chances?
7 key passes (3.20/90), 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 (7)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 (4)from the right (3)of 7 key passes landing in the final thirdattacking ↑ toward goal
08
Where does he become vulnerable?
27 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.
19
attacking third (cheap)
7
middle third
1
own third (dangerous)
Vision AI 70% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 1.90 danger-index/90 · 0.154 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
06
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 7 key passes, his busiest route is a delivery where he plays inside from the right wing toward the central in the final third — 3 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 wing in the final third: 47% of his 15 touches there are lost (7 times).
05
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 30 ball-carries, his dominant tendency is that he drives along the touchline (43%). He carries from outside into the middle 4 times and out toward the touchline 1 — a genuine inside forward who cuts in with the ball.
07
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
2 · 7%
Progressive / key pass
4 · 13%
Simple pass
15 · 50%
No clean link
9 · 30%
Of 30 carries, 7% flow straight into a shot of his own, 13% into a key or progressive pass — a genuine end product to the carry, not just ball retention. 30% have no clean link to a next touch of his own close to where the carry ended.
04
Crosses & Cutbacks
7 crosses (3.20/90, 4 completed) and 4 cutbacks (1.83/90, 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
18 defensive actions across the season (8.2/90). 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 →
5
tackles · 60% won
0
interceptions · 0.0/90
4
recoveries · 1.8/90
1
clearances · 0.5/90
0
blocks
47
avg action height
4
won high (att 3rd)
10
middle third
4
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 9 proactive ball-wins (4.1/90), tackle success 60%. 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.
7
attacking-half actions · 3.20/90
09
Against Different Pressing Intensities
Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Kaito Mizuta keep producing when the game is tight and the press is high? Tiers of ~2-2 matches — directional evidence, not proof.
press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 4.0, 2m)
1.25
2.0
3.96
0%
Mid press (PPDA 4.5, 2m)
1.76
0.0
6.00
33%
Low press (PPDA 4.7, 2m)
1.25
3.6
1.18
0%
Team
Team context
How much of the team runs through him, and what changes without him.
Le Havre's output per match with Kaito Mizuta (6 matches) versus without him (2 matches). Insufficient evidence — the without-sample is only 2 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.
WITH (6)
WITHOUT (2)
Δ
goals for /match
0.83
1.50
-0.67
xG for /match
1.37
2.26
-0.89
goals against /match
1.67
2.50
-0.83
points /match
0.33
0.00
+0.33
12
His Share of the Team
Of everything Le Havre produced this season, the categories where the biggest share ran through Kaito Mizuta specifically — his share of the team total, not a per-90 rate.
category
share
him / team
box entries
4%
10 / 279
zone-14 entries
3%
4 / 136
shots
1%
5 / 336
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 294 attacking mids in the pool (min 180 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)77%Half-space creator68%
Why Advanced playmaker (8) 77%: a weighted blend of creativity 68 (weight 35%) + final-third threat 87 (weight 25%) + progression 77 (weight 25%) + box threat 62 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
aerial ability, marking, off-ball running — not in event data
Final-third threat
87
Progression
77
Through-balls ~proxy
77
Carrying
76
Defensive aggression
74
Passing directness
73
Territory (wide vs central)
71
Creativity
68
Receiving zones
63
Box threat
62
Crossing
62
Transition ~proxy
59
Ball-winning
39
Build-up
38
Line-breaking
29
Retention
20
Press resistance ~proxy
18
Dribbling
14
14
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: 182 cm / 71 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 Ligue 1, Bundesliga, La Liga, Premier League 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.
Arsen Zakharyan Real Sociedad · La Liga · 182 cm / 73 kg
73%
Driven by: press resistance (21%), dribbling (20%), final-third threat (12%). Different mechanism — Mizuta more via carrying, creativity; Zakharyan more via line-breaking.
Lorenzo Pellegrini Roma · Serie A · 186 cm / 77 kg
72%
Driven by: press resistance (19%), dribbling (17%), final-third threat (13%). Different mechanism — Mizuta more via carrying, defensive aggression; Pellegrini more via line-breaking.
Anthony Bermont Angers · 180 cm / 54 kg
70%
Driven by: dribbling (14%), final-third threat (12%), press resistance (12%). Different mechanism — Bermont more via retention, line-breaking.
Jack Rudoni Coventry · Premier League · 186 cm / 77 kg
70%
Driven by: press resistance (14%), defensive aggression (12%), final-third threat (12%). Different mechanism — Mizuta more via receiving zones, carrying; Rudoni more via line-breaking, ball-winning.
Muhammed Damar Hoffenheim · Bundesliga 25/26 · 185 cm / 73 kg
70%
Driven by: press resistance (15%), dribbling (14%), final-third threat (12%). Different mechanism — Mizuta more via carrying; Damar more via line-breaking, box threat.
Álex Berenguer Athletic Club · La Liga · 175 cm / 73 kg
68%
Driven by: press resistance (13%), retention (12%), final-third threat (12%). Different mechanism — Mizuta more via passing directness, carrying; Berenguer more via line-breaking, dribbling.
15
Summary
Kaito Mizuta is an advanced playmaker (8) / half-space creator: 3.20 key passes /90, 2.3 progressive passes, 0 goals from 0.34 xG. A between-the-lines creator. [Off-ball movement into pockets needs tracking.]
Based on 6 matches (197 minutes) — an early read, treat with caution until more minutes are logged. He profiles as an advanced playmaker (8) / half-space creator — best used in a system built around that identity.
His biggest room for growth is box 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.