feeldb

Teenage Mutant Ninja Turtles: Out of the Shadows

2016 · 112 min · Director: Dave Green ★ IMDb 5.9 · 108,038 ratings

Show plot summary (may contain spoilers)

The Turtles continue to live in the shadows and no one knows they were the ones who took down Shredder. Vernon is the one everyone thinks is the one who took Shredder down. April O'Neill does some snooping and learns a scientist named Baxter Stockman is working for Shredder. He plans to break him out while he's bringing transported. April tells the turtles, who try to stop it but can't. Stockman tries to teleport Shredder but he some how ends up in another dimension and meets a warlord named Krang who instructs Shredder to assemble a teleportation device he sent to Earth a long time ago. He gives Shredder some mutagen which he uses to transform two criminals who were also in the transport with him, Rock Steady and Bebop, into mutants. They then set out to find the device. April saw the transformation while investigating Stockman. She takes the mutagen and is chased by Shredder's minions, the Foot Clan. She is saved by a man named Casey Jones who was the one transporting Shredder. The Turtles show up and they try to work together. In the melee, the mutagen ends up with the police. Knowing Shredder will try and get it back, April tries to get it first and she asks Vern to help. Eventually she and Casey are arrested. The Turtles get the mutagen and Donatello analyzes it, learns it could make them human, which he tells Leonardo who tells him to forget it and not to tell the others. But Michelangelo tells Raphael who feels that Leonardo doesn't respect them.

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Emotional fingerprint

Teenage Mutant Ninja Turtles: Out of the Shadows (2016) — Movie. Top emotional signals: Excitement 35%, Humor 25%, Smile 20%. Source: AI estimate. Shares describe emotional signal, not percentages of people. Your experience may differ. How we measure

  1. Humor25%
  2. Smile20%

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, Humor, Smile. Genres: Comedy, Adventure, Action. AI estimate.

Is it worth watching?

Consider this title if you are looking for Excitement, Humor and Smile. Its IMDb rating of 5.9/10 suggests a mixed audience reception; consider how well the emotional profile suits you. For these leading emotions, its Feel Score is 61/100.

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Emotional journey

AI · from subtitles
  • Excitement
  • Tension
  • Humor

Not enough subtitle evidence

No dominant emotion

Dominant emotion: Humor

Dominant emotion: Excitement

Dominant emotion: Curiosity

Dominant emotion: Tension

Dominant emotion: Relief

Excitement
Tension
Humor
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 dips around 8 %, then peaks around 18 %, then peaks around 88 %.Ending hidden

Emotional journey
%Approximate minuteDominant emotionOverall intensityExcitementTensionHumor
2.5 %≈ 3′Humor52 %40 %13 %51 %
7.5 %≈ 8′Humor48 %33 %22 %44 %
12.5 %≈ 14′Excitement55 %44 %43 %38 %
17.5 %≈ 20′Excitement66 %58 %57 %37 %
22.5 %≈ 25′Curiosity60 %45 %47 %35 %
27.5 %≈ 31′Humor51 %30 %34 %38 %
32.5 %≈ 36′Curiosity54 %35 %39 %48 %
37.5 %≈ 42′Humor57 %37 %42 %51 %
42.5 %≈ 48′Curiosity56 %27 %40 %45 %
47.5 %≈ 53′Curiosity56 %26 %44 %43 %
52.5 %≈ 59′Humor56 %33 %48 %45 %
57.5 %≈ 64′Tension61 %47 %54 %41 %
62.5 %≈ 70′Excitement70 %63 %64 %39 %
67.5 %≈ 76′Excitement68 %57 %64 %36 %
72.5 %≈ 81′Tension63 %41 %58 %26 %
77.5 %≈ 87′Tension65 %46 %59 %25 %
82.5 %≈ 92′Excitement74 %62 %69 %30 %
87.5 %≈ 98′Tension81 %64 %63 %35 %
92.5 %≈ 104′Relief79 %51 %36 %41 %
97.5 %≈ 109′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 ↗

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Cast

PP
Pete Ploszek

Leonardo

Alan Ritchson

Raphael

JH
Jeremy Howard

Donatello

Noel Fisher

Michelangelo

Stephen Amell

Casey Jones

Will Arnett

Vernon Fenwick

Laura Linney

Chief Vincent

BT
Brian Tee

Shredder

SF
Stephen Farrelly

Rocksteady

PD
Peter Donald Badalamenti II

Splinter

Tony Shalhoub

Splinter (voice)

Brad Garrett

Krang (voice)

OA
Opal Alladin

Security Officer

CF
Connor Fox

Trevor

AA
Alessandra Ambrosio

Self

SD
Stan Demidoff

Uniformed Cop

Details

Directed by
Dave Green
Type
Movies
Released
2016
Runtime
112 min
Country
United States, Hong Kong, China
Ratings
★ IMDb 5.9 · 108,038 ratings
Feels mostly
Excitement
Data updated

Where to watch

Data: JustWatch · Wikidata

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