feeldb

Wrong Side of Town

2010 · 88 min · Director: David DeFalco ★ IMDb 3.8 · 3,240 ratings

Show plot summary (may contain spoilers)

Ex-Navy Seal Bobby Kalinowski lives a quiet, peaceful life as a landscape architect in an LA suburb with his wife Dawn and 16 year old daughter Brianna. Tonight they are invited out for an evening on the town by new neighbors clay and Elise Freeman to a happening club downtown. Little did they know that this would be the start of a life or death ordeal for the group. While at the club, Dawn is accosted by one of the club owners, Ethan Bordas. When Bobby intervenes and accidentally kills Ethan defending his wife, his enraged older brother, Seth, puts a one hundred thousand dollar bounty on his head. Now Bobby must escape LA while being pursued by every criminal, wise guy and thug in the city. Bobby decides to separate from his wife and neighbors and revert to his Navy Seal training to survive. To complicate matters, Seth has a corrupt police sergeant preventing Bobby from getting any help from the law! However, they all underestimate the fighting skills and abilities of Bobby Kalinowski who battles through an army of thugs to finally make it back home. But, relentless, Seth doesn't stop there. He targets Bobby's family next and kidnaps his daughter. His plan is successful and he lures Bobby to his seedy warehouse complex for the final showdown.

Ask Kadri

Trailer for Wrong Side of Town

Playing the trailer connects to YouTube. No connection is made until you choose to play.

Rate how it felt
Working…

Your viewing check-in

Emotional fingerprint

Wrong Side of Town (2010) — Movie. Top emotional signals: Excitement 35%, Tension 25%, Fear 20%. Source: AI estimate. Shares describe emotional signal, not percentages of people. Your experience may differ. How we measure

  1. Fear20%
  2. Anger10%
  3. Relief10%

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, Fear. Genres: Thriller, Crime, Action. AI estimate.

Is it worth watching?

Consider this title if you are looking for Excitement, Tension and Fear. Its IMDb rating of 3.8/10 suggests a mixed audience reception; consider how well the emotional profile suits you. For these leading emotions, its Feel Score is 56/100.

How did it make you feel?

Votes are saved to the fingerprint once you’re signed in.

Pick up to three · 0/3

1
2
3

Emotional journey

AI · from subtitles
  • Tension
  • Fear
  • Relief

Not enough subtitle evidence

No dominant emotion

Dominant emotion: Tension

Dominant emotion: Humor

Dominant emotion: Relief

Tension
Fear
Relief
Emotional journey Emotional intensity over the film’s runtime, from quieter to stronger on a fixed 0–1 scale. Hatched intervals have insufficient subtitle evidence. The table provides the values. Not enough subtitle evidence
Ending hidden

Dominant emotion

Intensity peaks around 3 %, then dips around 13 %, then peaks around 83 %.Ending hidden

Emotional journey
%Approximate minuteDominant emotionOverall intensityTensionFearRelief
2.5 %≈ 2′Tension72 %65 %57 %12 %
7.5 %≈ 7′Humor51 %35 %29 %18 %
12.5 %≈ 11′Humor43 %25 %16 %9 %
17.5 %≈ 15′Tension61 %55 %39 %3 %
22.5 %≈ 20′Tension78 %78 %56 %10 %
27.5 %≈ 24′Tension80 %80 %57 %13 %
32.5 %≈ 29′Tension80 %80 %59 %10 %
37.5 %≈ 33′Tension74 %73 %53 %14 %
42.5 %≈ 37′Tension66 %64 %43 %18 %
47.5 %≈ 42′Tension66 %64 %40 %14 %
52.5 %≈ 46′Tension70 %68 %44 %5 %
57.5 %≈ 51′Tension75 %74 %51 %3 %
62.5 %≈ 55′Tension71 %60 %40 %19 %
67.5 %≈ 59′Relief68 %45 %31 %31 %
72.5 %≈ 64′Tension76 %65 %54 %19 %
77.5 %≈ 68′Tension84 %84 %69 %19 %
82.5 %≈ 73′Tension88 %88 %70 %45 %
87.5 %≈ 77′Tension84 %68 %55 %64 %
92.5 %≈ 81′Relief73 %30 %25 %67 %
97.5 %≈ 86′Not enough subtitle evidenceNot enough subtitle evidenceNot enough subtitle evidenceNot enough subtitle evidenceNot enough subtitle evidence
Man in a hole

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

AI

Ask anything about Wrong Side of Town. From the film’s own dialogue and FeelDB data, at your spoiler level.

Kadri

Hi, I’m Kadri. Ask me anything about Wrong Side of Town — I’ll stay inside your spoiler line.

Premise only
Enter to send · Shift + Enter for a new line
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

RV
Rob Van Dam

RS
Rob Szatkowski

Bobby Kalinowsky

LG
Lara Grice

EB
Edrick Browne

RR
Randal Reeder

Trouble

JR
Ja Rule

Razor

RB
Ross Britz

Ethan Bordas

Edrick Browne

Clay Freeman

AK
Ava Knighten Santana

Elise Freeman

SD
Stormy Daniels

Stormy

JK
Jerry Katz

Seth Bordas

BF
Brooke Frost

Brianna

NF
Nelson Frazier Jr.

Animal

DL
Damon Lipari

Nicky

DD
David DeFalco

Demon

MC
Marrese Crump

Markus

O
Omarion

Stash

Q
Quess

Dawg

RJ
Ramar Jenkins

Big Dog

Details

Directed by
David DeFalco
Written by
David DeFalco
Type
Movies
Released
2010
Runtime
88 min
Country
USA
Ratings
★ IMDb 3.8 · 3,240 ratings
Feels mostly
Excitement
Data updated

Where to watch

Also on

Availability varies by country

Data: JustWatch · Wikidata

Feels similar

More like this →

Emotion overlap shows mood similarity, not a prediction of enjoyment.