How I Became a Gangster
2019 · 140 min · Director: Maciej Kawulski
Show plot summary (may contain spoilers)
A polish gangster discovers the senselessness of his life.
Emotional fingerprint
How I Became a Gangster (2019) — Movie. Top emotional signals: Excitement 30%, Tension 25%, Sadness 20%. Source: AI estimate. Shares describe emotional signal, not percentages of people. Your experience may differ. How we measure
- Excitement30%
- Tension25%
- Sadness20%
- Anger15%
- Guilt10%
AI estimate · no viewer votes yet
How we measure
AI estimate
Share of emotional signal, not the percentage of people or a probability of enjoyment.
Each viewer contributes one response, split equally across their selected emotions. When available, an automated estimate supplies a prior that is blended with those responses. Counts include distinct viewers, not automated estimates or archived anonymous votes. Fewer than 3 viewers is an early estimate; more responses do not guarantee certainty.
Why it feels this way
The strongest emotional signals are Excitement, Tension, Sadness. Genres: Drama, Crime. AI estimate.
Is it worth watching?
Consider this title if you are looking for Excitement, Tension and Sadness. Its IMDb rating of 6.9/10 suggests a generally positive audience reception. For these leading emotions, its Feel Score is 69/100.
How did it make you feel?
Votes are saved to the fingerprint once you’re signed in.
Pick up to three · 0/3
Emotional journey
- Tension
- Disturbing
- Sadness
Not enough subtitle evidence
No dominant emotion
Dominant emotion: Humor
Dominant emotion: Disturbing
Dominant emotion: Tension
Dominant emotion: Sadness
Dominant emotion
| % | Approximate minute | Dominant emotion | Overall intensity | Tension | Disturbing | Sadness |
|---|---|---|---|---|---|---|
| 2.5 % | ≈ 4′ | Humor | 37 % | 21 % | 18 % | 8 % |
| 7.5 % | ≈ 11′ | Humor | 40 % | 26 % | 24 % | 11 % |
| 12.5 % | ≈ 18′ | Disturbing | 45 % | 35 % | 32 % | 13 % |
| 17.5 % | ≈ 25′ | Tension | 53 % | 47 % | 36 % | 12 % |
| 22.5 % | ≈ 32′ | Tension | 55 % | 48 % | 34 % | 12 % |
| 27.5 % | ≈ 39′ | Humor | 54 % | 44 % | 35 % | 14 % |
| 32.5 % | ≈ 46′ | Tension | 66 % | 57 % | 53 % | 25 % |
| 37.5 % | ≈ 53′ | Disturbing | 71 % | 63 % | 65 % | 30 % |
| 42.5 % | ≈ 60′ | Disturbing | 63 % | 55 % | 55 % | 26 % |
| 47.5 % | ≈ 67′ | Tension | 60 % | 53 % | 45 % | 26 % |
| 52.5 % | ≈ 74′ | Tension | 52 % | 44 % | 35 % | 26 % |
| 57.5 % | ≈ 81′ | Disturbing | 51 % | 45 % | 35 % | 24 % |
| 62.5 % | ≈ 88′ | Tension | 61 % | 56 % | 42 % | 25 % |
| 67.5 % | ≈ 95′ | Tension | 64 % | 56 % | 45 % | 36 % |
| 72.5 % | ≈ 102′ | Sadness | 68 % | 57 % | 55 % | 44 % |
| 77.5 % | ≈ 109′ | Tension | 77 % | 69 % | 67 % | 40 % |
| 82.5 % | ≈ 116′ | Tension | 80 % | 75 % | 64 % | 37 % |
| 87.5 % | ≈ 123′ | Tension | 79 % | 74 % | 55 % | 45 % |
| 92.5 % | ≈ 130′ | Sadness | 79 % | 59 % | 47 % | 50 % |
| 97.5 % | ≈ 137′ | Humor | 73 % | 33 % | 31 % | 33 % |
Riches to rags
Rags to riches: The emotional tone rises from negative to positive.
Riches to rags: The emotional tone falls from positive to negative.
Man in a hole: The tone falls, then recovers.
Icarus: The tone rises, then falls.
Cinderella: The tone rises, falls, then rises again.
Oedipus: The tone falls, rises, then falls again.
AI reading of the film’s English subtitles (dialogue and sound cues) — not viewer votes. How we measure ↗
Kadri — your film companion
AIAsk anything about How I Became a Gangster. From the film’s own dialogue and FeelDB data, at your spoiler level.
Afterward Reveal viewer responses · may contain spoilers
Viewer responses about feelings after the title ended, separate from feelings while watching. No AI estimates.
0 responses so far
Feeling details appear after at least 3 viewers respond, to protect privacy.
Cast
Viola
Daniel
'Łomek'
Marian
Officer Bielawski
'Golum'
'Krater'
'Łom'
'Mariuszek'
Gangster's Mother
'Nowy'
'Ziomas'
Laura
Gangster (12 years old)
Details
- Directed by
- Maciej Kawulski
- Written by
- Krzysztof Gureczny
- Type
- Movies
- Released
- 2019
- Runtime
- 140 min
- Country
- Poland
- Ratings
- Feels mostly
- Excitement
- Data updated
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