Thin sample this season. Frank Onyeka has played 7 matches (409 min) so far, so sections that need a bigger sample to say anything reliable are not shown here — they are missing on purpose, not broken. See all seasons combined →
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 (63% of his 116 passes)
71% completion · 116× in 7/7 matches
↓
PROGRESS CENTRAL
break a line through the middle
2.0 prog/90 · 17× in 6/7 matches
↓
SCREEN / WIN BALL
protect the back four
7.7 ball-wins/90 · 35× in 7/7 matches
↓
RECYCLE / PROGRESS
keep it ticking, feed the final third
1.5 f3-entries/90 · 7× in 5/7 matches
Signature: Receive → Progress Central → Screen / Win Ball → Recycle / Progress — the only steps proven repeatable this season (4 of 5 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: escape pressure — 2× (low confidence, shown as a number only, no tactical conclusion drawn) — omitted from the signature rather than presented as one.
13
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 →
17
passes / match
15.0
def actions / 90
2–30
pass range (matches)
4
clearances
Pass range = his fewest and most passes in any single match this season (2 at the low end, 30 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.
22 tracked carries (4.8/90, 1 progressive, 161m 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.
progressivelateral/short% of his 22 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 6m, longest 21m
By zone — where the carry started → where it ended
First (22)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).
10
tackle duels
5
won
5
beaten · 50%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 40%
OUTSIDE 60%
Tackle-duel location — 4 inside · 6 outside
Right Wing
5 · 50%
Right Half-Space
1 · 10%
Central
3 · 30%
Left Half-Space
0 · 0%
Left Wing
1 · 10%
Vision AI beaten in 5 of 10 tackle duels (50% loss rate) — a real defensive leak worth flagging.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →
He attempted only 2 dribbles of his own all season — dribbling is not part of this role; his ball-carrying is covered above, his defending against the dribble below.
04
How does he create chances?
1 key passes (0.22/90), 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
03
Where does he become vulnerable?
36 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.
7
attacking third (cheap)
23
middle third
6
own third (dangerous)
Vision AI 19% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 2.98 danger-index/90 · 0.377 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
05
Where Does He Receive?
The zones where Frank Onyeka 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
19%
Primary
Right Half-Space, Middle third
17%
Secondary
Central, Middle third
17%
Third
Right Wing, Middle third
These are the zones where he collected the ball most.
06
Where Does He Operate? — Every Zone
Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Frank Onyeka 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 →
08
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 inside from the right hs toward the central 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 half-space in the middle third: 38% of his 8 touches there are lost (3 times).
68 defensive actions across the season (15.0/90). 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 →
10
tackles · 50% won
6
interceptions · 1.3/90
19
recoveries · 4.2/90
4
clearances · 0.9/90
4
blocks
37
avg action height
8
won high (att 3rd)
28
middle third
32
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 35 proactive ball-wins (7.7/90), tackle success 50%. He defends mostly around the middle third.
10
Can he play under pressure?
Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Frank Onyeka 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 ~2-3 matches — directional evidence, not proof.
press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 2.8, 2m)
62%
2.7
3.4
0.46
Mid press (PPDA 3.2, 2m)
71%
3.2
4.8
0.62
Low press (PPDA 4.5, 3m)
75%
1.2
3.7
0.21
Team
Team context
How much of the team runs through him, and what changes without him.
Coventry's output per match with Frank Onyeka (7 matches) versus without him (1 matches). Insufficient evidence — the without-sample is only 1 matches; treat every Δ below as noise until more games exist. What his own defending should move — goals conceded and results — leads; attacking output (largely out of a defender's hands) is shown after, for context. A proper on-off model needs many more minutes.
WITH (7)
WITHOUT (1)
Δ
goals against /match
2.00
1.00
+1.00
points /match
0.86
0.00
+0.86
goals for /match
0.86
0.00
+0.86
xG for /match
0.94
0.00
+0.94
12
His Share of the Team
Of everything Coventry produced this season, the categories where the biggest share ran through Frank Onyeka specifically — his share of the team total, not a per-90 rate.
category
share
him / team
tackles
8%
12 / 160
interceptions
4%
6 / 137
ball recoveries
4%
24 / 626
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 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.
aerial ability, marking, off-ball running — not in event data
Passing directness
93
Territory (wide vs central)
72
Transition ~proxy
36
Ball-winning
31
Dribbling
25
Defensive aggression
24
Press resistance ~proxy
21
Build-up
17
Creativity
17
Retention
10
Progression
9
Carrying
9
Final-third threat
9
Box threat
7
Crossing
5
Through-balls ~proxy
4
Line-breaking
2
Receiving zones
2
15
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 / 70 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.
Josh Laurent Burnley 25/26 · 188 cm / 70 kg
90%
Driven by: receiving zones (11%), final-third threat (9%), creativity (9%). Different mechanism — Laurent more via box threat, crossing.
Urko González de Zárate Espanyol · La Liga · 189 cm / 83 kg
87%
Driven by: crossing (12%), creativity (11%), receiving zones (9%). Different mechanism — Onyeka more via territory (wide vs central), passing directness; Zárate more via dribbling, through-balls.
Carlos Protesoni Alaves · La Liga · 185 cm / 76 kg
82%
Driven by: receiving zones (11%), press resistance (9%), carrying (9%). Different mechanism — Protesoni more via box threat, crossing.
Jan Schöppner Heidenheim · Bundesliga 25/26 · 190 cm / 78 kg
79%
Driven by: retention (14%), press resistance (10%), final-third threat (10%). Different mechanism — Onyeka more via passing directness; Schöppner more via box threat, through-balls.
Tomás Soucek West Ham 25/26 · 192 cm / 86 kg
78%
Driven by: crossing (11%), press resistance (9%), progression (9%). Different mechanism — Onyeka more via passing directness, ball-winning; Soucek more via box threat, defensive aggression.
Soungoutou Magassa West Ham 25/26 · 188 cm / 80 kg
76%
Driven by: crossing (17%), receiving zones (12%), final-third threat (10%). Different mechanism — Magassa more via dribbling, ball-winning.
16
Summary
Frank Onyeka is a ball-winning 6: 71% completion, 17 line-breaks and 2.0 progressive passes /90, resisting pressure with 0% dribble success. A central controller. [Off-ball screening position and scanning need tracking data.]
Based on 7 matches (409 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a ball-winning 6 — best used in a system built around that identity.
His biggest room for growth is progression — even a modest improvement there would meaningfully lift his overall ball-winning 6 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.