feeldb

Wedding Daze

2006 · 90 min · Director: Michael Ian Black, Michael Ian Black ★ IMDb 5.6 · 19,597 ratings

Show plot summary (may contain spoilers)

This is a comedy that shows us that love has nothing to do with perfection. After losing the woman of his dreams, Anderson is convinced he'll never fall in love again. But at the urging of his best friend, he spontaneously proposes to a dissatisfied waitress named Katie and an innocent dare evolves into the kind of love that they both have been looking for all along.

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Emotional fingerprint

Wedding Daze (2006) — Movie. Top emotional signals: Love 35%, Humor 25%, Smile 20%. Source: AI estimate. Shares describe emotional signal, not percentages of people. Your experience may differ. How we measure

35%Love
25%Humor
20%Smile
  1. Love35%
  2. Humor25%
  3. Smile20%
  4. Hope10%

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 Love, Humor, Smile. Genres: Comedy, Romance. AI estimate.

Is it worth watching?

Consider this title if you are looking for Love, Humor and Smile. Its IMDb rating of 5.6/10 suggests a mixed audience reception; consider how well the emotional profile suits you. For these leading emotions, its Feel Score is 59/100.

How did it make you feel?

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Emotional journey

AI · from subtitles
  • Humor
  • Love
  • Joy

Not enough subtitle evidence

No dominant emotion

Dominant emotion: Humor

Dominant emotion: Sadness

Dominant emotion: Love

Dominant emotion: Tension

Humor
Love
Joy
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.
Ending hidden

Dominant emotion

Intensity dips around 28 %, then peaks around 88 %.Ending hidden

Emotional journey
%Approximate minuteDominant emotionOverall intensityHumorLoveJoy
2.5 %≈ 2′Humor49 %45 %28 %18 %
7.5 %≈ 7′Humor48 %44 %26 %15 %
12.5 %≈ 11′Sadness48 %43 %24 %13 %
17.5 %≈ 16′Humor48 %44 %24 %16 %
22.5 %≈ 20′Humor46 %41 %29 %20 %
27.5 %≈ 25′Love43 %35 %29 %16 %
32.5 %≈ 29′Humor45 %38 %24 %14 %
37.5 %≈ 34′Humor46 %41 %23 %15 %
42.5 %≈ 38′Humor46 %40 %24 %16 %
47.5 %≈ 43′Humor48 %43 %30 %20 %
52.5 %≈ 47′Humor52 %48 %29 %20 %
57.5 %≈ 52′Humor57 %48 %19 %14 %
62.5 %≈ 56′Sadness56 %38 %16 %8 %
67.5 %≈ 61′Sadness49 %31 %23 %13 %
72.5 %≈ 65′Love51 %35 %30 %21 %
77.5 %≈ 70′Tension59 %41 %26 %16 %
82.5 %≈ 74′Tension63 %45 %28 %20 %
87.5 %≈ 79′Love64 %44 %46 %41 %
92.5 %≈ 83′Love59 %35 %54 %45 %
97.5 %≈ 88′Love52 %22 %47 %32 %
Cinderella

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 ↗

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

MW
Michael Weston

MC
Mark Consuelos

Morty

AB
Audra Blaser

Vanessa

Matt Malloy

Stuart

KA
Kevin Allison

Hal

RR
Roger Robinson

Dr. Favreau

TB
Teodorina Bello

Rhonda

RM
Regan Mizrahi

Diner Kid

CA
Chuck Ardezzone

Scary-Looking Con

Details

Type
Movies
Released
2006
Runtime
90 min
Country
United States
Ratings
★ IMDb 5.6 · 19,597 ratings
Feels mostly
Love
Data updated

Where to watch

Also on

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Data: JustWatch · Wikidata

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