Thin sample this season. Nikola Moro has played 5 matches (135 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
Central, Middle third — mostly in the middle third (64% of his 90 passes)
82% completion · 90× in 5/5 matches
↓
PROGRESS
drive or pass into the final third
12.0 prog/90 · 18× in 5/5 matches
Signature: Receive → Progress — the only steps proven repeatable this season (2 of 4 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: arrive — 2× (low confidence, shown as a number only, no tactical conclusion drawn); create / finish — 1× (low confidence, shown as a number only, no tactical conclusion drawn) — omitted from the signature rather than presented as one.
In possession
In possession
What he does with the ball: build-up, progression, creation, carrying and finishing.
29 tracked carries (19.3/90, 11 progressive, 319m 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 29 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 11m, longest 20m
By zone — where the carry started → where it ended
First (22)Second (7)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Dribbles (1v1s)
Only 0 dribbles attempted this season — too little volume to map a location pattern.
03
How does he progress play?
How much he drives the ball forward. Progressive = completed pass advancing ≥15 toward goal.
18
progressive · 12.0/90
18
final-third entries · 12.0/90
2
box entries · 1.33/90
35
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.
02
How does he create chances?
1 key passes (0.67/90), 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
09
Where does he become vulnerable?
16 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.
5
attacking third (cheap)
4
middle third
7
own third (dangerous)
Vision AI 31% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 4.42 danger-index/90 · 0.414 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
06
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.
own goal left, attacking →
Highest-value routes (xT)
0.33
Right Half-Space Def third → Right Wing Att third
2 passes
0.24
Central Att third → Right Half-Space Att third
1 passes
0.19
Right Half-Space Mid third → Central Att third
1 passes
0.16
Left Half-Space Mid third → Left Wing Att third
2 passes
0.14
Left Wing Mid third → Left Wing Att third
1 passes
0.11
Central Def third → Left Half-Space Mid third
1 passes
04
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 switches it out from the right hs to the right wing, advancing it forward in the defensive third — 2 passes worth 0.33 xT.
Where do his chances come from?
Of 1 key passes, his busiest route is a delivery where he plays inside from the right wing toward the right hs, advancing it forward 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 middle third: 17% of his 12 touches there are lost (2 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 29 ball-carries, his dominant tendency is that he carries through central areas (90%). He carries from outside into the middle 1 times and out toward the touchline 0 — a genuine inside forward who cuts in with the ball.
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
0 · 0%
Progressive / key pass
2 · 7%
Simple pass
27 · 93%
No clean link
0 · 0%
Of 29 carries, 0% flow straight into a shot of his own, 7% into a key or progressive pass — a genuine end product to the carry, not just ball retention. 0% have no clean link to a next touch of his own close to where the carry ended.
19 defensive actions across the season (12.7/90). 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 →
1
tackles · 100% won
1
interceptions · 0.7/90
8
recoveries · 5.3/90
3
clearances · 2.0/90
0
blocks
32
avg action height
2
won high (att 3rd)
5
middle third
12
own third
Vision AI A deep-defending defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 10 proactive ball-wins (6.7/90), tackle success 100%. He defends mostly around the middle third.
Team
Team context
How much of the team runs through him, and what changes without him.
Bologna's output per match with Nikola Moro (5 matches) versus without him (3 matches). Insufficient evidence — the without-sample is only 3 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.
WITH (5)
WITHOUT (3)
Δ
goals for /match
0.80
1.33
-0.53
xG for /match
1.00
1.85
-0.84
goals against /match
1.60
0.67
+0.93
points /match
0.40
2.00
-1.60
12
His Share of the Team
Of everything Bologna produced this season, the categories where the biggest share ran through Nikola Moro specifically — his share of the team total, not a per-90 rate.
category
share
him / team
final-third entries
13%
222 / 1769
threat added by passing (xT)
9%
39.7 / 449.3
half-space entries
9%
84 / 971
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 383 central 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
96
Progression
87
Final-third threat
86
Carrying
83
Transition ~proxy
82
Line-breaking
80
Build-up
79
Press resistance ~proxy
72
Retention
72
Crossing
71
Dribbling
69
Receiving zones
65
Through-balls ~proxy
55
Ball-winning
54
Box threat
47
Creativity
47
Defensive aggression
44
Territory (wide vs central)
16
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: 183 cm / 77 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 Serie A, Bundesliga, La Liga, Ligue 1 and Premier League, 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.
Declan Rice Arsenal · Premier League · 188 cm / 76 kg
89%
Driven by: transition (16%), final-third threat (14%), progression (13%). Different mechanism — Moro more via dribbling; Rice more via through-balls, territory (wide vs central).
Angelo Stiller Stuttgart · Bundesliga · 183 cm / 77 kg
88%
Driven by: transition (13%), passing directness (11%), progression (11%). Different mechanism — Stiller more via creativity, receiving zones.
Joshua Kimmich Bayern · Bundesliga · 177 cm / 75 kg
86%
Driven by: transition (13%), progression (13%), final-third threat (12%). Different mechanism — Kimmich more via through-balls, receiving zones.
Luka Modric AC Milan · 172 cm / 66 kg
86%
Driven by: transition (16%), progression (11%), passing directness (11%). Different mechanism — Modric more via creativity, receiving zones.
Piotr Zielinski Inter · 180 cm / 76 kg
85%
Driven by: transition (14%), passing directness (10%), carrying (10%). Different mechanism — Moro more via ball-winning; Zielinski more via receiving zones, box threat.
Billy Gilmour Napoli · 170 cm / 60 kg
85%
Driven by: transition (14%), build-up (10%), progression (10%). Different mechanism — Moro more via crossing; Gilmour more via receiving zones, dribbling.
15
Summary
Nikola Moro is a deep-lying playmaker / tempo controller: 12.0 progressive passes, 0.67 key passes /90, 2 box entries, 0 goals from 0.00 xG. A box-to-box contributor across every phase.
Based on 5 matches (135 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a deep-lying playmaker / tempo controller — 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.