Thin sample this season. Riccardo Orsolini has played 4 matches (194 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
Right Half-Space, Attacking third — mostly in the middle third (50% of his 52 passes)
33% of touches wide right · 52× in 4/4 matches
↓
PROGRESS
drive the ball into the final third
3.2 progressive · 1.9 f3/90 · 7× in 3/4 matches
↓
CREATE / FINISH
cut-back or shot from inside
1.39 key passes /90 · 1 goals · 4× in 2/4 matches
Signature: Receive → Progress → Create / 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: carry / beat man — 3× (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.
16 tracked carries (7.4/90, 3 progressive, 140m 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 16 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 7m, longest 26m
By zone — where the carry started → where it ended
First (16)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Dribbles (1v1s)
Only 3 dribbles attempted this season — too little volume to map a location pattern.
02
How does he create chances?
3 key passes (1.39/90), 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 (2)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 (0)from the right (2)of 2 key passes landing in the final thirdattacking ↑ toward goal
05
Where does he become vulnerable?
20 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.
11
attacking third (cheap)
7
middle third
2
own third (dangerous)
Vision AI 55% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 2.37 danger-index/90 · 0.256 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
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 from the right hs to the left hs, advancing it forward in the middle third — 1 passes worth 0.14 xT.
Where do his chances come from?
Of 3 key passes, his busiest route is a delivery where he plays inside from the right wing toward the right hs, playing it back 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 right wing in the final third: 44% of his 9 touches there are lost (4 times).
18 defensive actions across the season (8.4/90). 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 →
2
tackles · 100% won
0
interceptions · 0.0/90
7
recoveries · 3.2/90
4
clearances · 1.9/90
0
blocks
44
avg action height
2
won high (att 3rd)
11
middle third
5
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 9 proactive ball-wins (4.2/90), tackle success 100%. 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.
9
attacking-half actions · 4.18/90
Team
Team context
How much of the team runs through him, and what changes without him.
Bologna's output per match with Riccardo Orsolini (4 matches) versus without him (4 matches). Insufficient evidence — the without-sample is only 4 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.
WITH (4)
WITHOUT (4)
Δ
goals for /match
0.75
1.25
-0.50
xG for /match
1.49
0.00
+1.49
goals against /match
1.00
1.50
-0.50
points /match
1.00
1.00
+0.00
08
His Share of the Team
Of everything Bologna produced this season, the categories where the biggest share ran through Riccardo Orsolini specifically — his share of the team total, not a per-90 rate.
category
share
him / team
expected goals (xG)
19%
10.2 / 53.9
shots
15%
83 / 563
successful take-ons
10%
32 / 307
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 180 wingers 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.
Why Transition runner 49%: a weighted blend of box threat 83 (weight 25%) + defensive aggression 53 (weight 30%) + transition 35 (weight 45%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
passing directness
Strong
box threat
Average
territory (wide vs central), defensive aggression, through-balls, line-breaking, dribbling
aerial ability, marking, off-ball running — not in event data
Passing directness
90
Box threat
83
Territory (wide vs central)
58
Defensive aggression
53
Through-balls ~proxy
52
Line-breaking
50
Dribbling
44
Build-up
37
Receiving zones
36
Progression
36
Transition ~proxy
35
Press resistance ~proxy
35
Crossing
32
Final-third threat
27
Ball-winning
27
Creativity
24
Carrying
19
Retention
19
10
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 / 73 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.
Sirlord Conteh Heidenheim · Bundesliga 25/26 · 178 cm / 78 kg
76%
Driven by: retention (14%), carrying (13%), press resistance (10%). Different mechanism — Orsolini more via territory (wide vs central), line-breaking.
Daniel James Leeds · Premier League · 171 cm / 63 kg
71%
Driven by: retention (18%), passing directness (18%), ball-winning (11%). Different mechanism — Orsolini more via box threat, line-breaking; James more via transition, carrying.
Jorge de Frutos Rayo Vallecano · La Liga · 173 cm / 72 kg
68%
Driven by: creativity (16%), carrying (14%), final-third threat (13%). Different mechanism — Orsolini more via passing directness, line-breaking.
Saïd El Mala Koln · Bundesliga · 183 cm / 72 kg
67%
Driven by: creativity (15%), final-third threat (13%), box threat (12%). Different mechanism — Orsolini more via through-balls, passing directness; Mala more via carrying.
Álvaro García Rayo Vallecano · La Liga · 167 cm / 61 kg
66%
Driven by: retention (17%), carrying (16%), press resistance (13%). Different mechanism — Orsolini more via dribbling, line-breaking; García more via ball-winning, creativity.
Zito Luvumbo Cagliari · La Liga 25/26 · 171 cm / 65 kg
66%
Driven by: retention (15%), ball-winning (13%), creativity (11%). Different mechanism — Orsolini more via line-breaking, box threat; Luvumbo more via carrying.
11
Summary
Riccardo Orsolini is a wide, outside-first right carrier: 33% of dribbles in the wing lane, 48% of passes from wide — but 71% land inside. 3.2 progressive passes and 1.39 key passes /90 plus 1 goals from 0.07 xG. A carry-and-deliver threat.
Based on 4 matches (194 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a transition runner — best used in a system built around that identity.
His biggest room for growth is transition — even a modest improvement there would meaningfully lift his overall transition runner 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.