The Frequency of Greatness: A Holiday Movie Analysis
Author
Andrew Ledet
Published
December 23, 2025
🎄 Executive Summary
Does the “Modern Holiday Classic” actually exist, or are we living in an era of quantity over quality? This research project analyzes over 80 years of holiday cinema to identify the “Frequency of Greatness”—measuring how often a “must-own” classic is released compared to the total industry output.
The central question: Even if quality films are still being made at the same rate, does the massive increase in production volume make them effectively invisible?
📊 Methodology
To ensure a rigorous comparison, the following data parameters were applied:
The “Charlie Brown” Exception (Pre-1980): High-scoring TV specials (e.g., Rudolph, Grinch) are included for the 1940s-1970s as they represented the primary holiday medium of that era.
The 70-Minute Guard (Post-1980): To filter out modern “noise,” all entries after 1980 must be feature-length films (70+ minutes). This removes modern concerts, streaming variety specials, and TV episodes.
The “Greatness” Threshold: A film is labeled “Great” if it holds an IMDb score of 7.2 or higher OR a Metacritic score of 70 or higher.
The “Owned” Benchmark: A personal collection of 19 favorites was used as a validation set to test the algorithm’s accuracy.
Code
library(tidyverse)library(plotly)library(ggridges)library(knitr)library(DT) # For interactive tables# Load and Clean Dataraw_data <-read_csv("christmas_movies.csv")df <- raw_data %>%mutate(release_year =as.numeric(release_year),imdb_rating =as.numeric(imdb_rating),runtime =as.numeric(runtime),# IMPROVED GROSS CLEANING: Removes $, commas, and whitespace before convertinggross =as.numeric(gsub("[\\$, ]", "", as.character(gross))),type =coalesce(type, "Movie") ) %>%filter(release_year >=1940&!is.na(imdb_rating))# Keyword Scrubbingexclude_patterns <-"Concert|Live at|Variety Special|Celebration|Episode|Talk-Show"# THE MASTER FILTER: This creates df_clean, which we MUST use for all tablesdf_clean <- df %>%filter(!str_detect(title, regex(exclude_patterns, ignore_case =TRUE))) %>%filter( (release_year <1980) | (release_year >=1980&str_detect(type, "Movie") & runtime >=70) )# Label Greatnessdf_clean <- df_clean %>%mutate(is_great = imdb_rating >=7.2| meta_score >=70)# Identify Your Collectionmy_collection <-c("It's a Wonderful Life", "Christmas in Connecticut", "The Bishop's Wife","The Lemon Drop Kid", "White Christmas", "Auntie Mame", "Trading Places","Scrooged", "Die Hard", "Home Alone", "Edward Scissorhands", "Home Alone 2: Lost in New York", "The Muppet Christmas Carol", "The Santa Clause", "While You Were Sleeping", "Catch Me If You Can","Elf", "Love Actually", "Four Christmases")df_clean <- df_clean %>%mutate(is_owned = title %in% my_collection)
📈 Visualizing the Trend
This scatter plot showcases the density of films over time. The Gold Diamonds represent your personal collection. Notice how the “gray cloud” of films has grown exponentially denser in recent decades, making quality films harder to discover.
🌊 The Shift in Distribution
The “Ridgeline” plot below shows the “Density of Quality.” Notice how the distribution shape changes: early decades show narrow, quality-focused peaks, while recent decades show massive volume with lower average quality.
📊 The Signal-to-Noise Problem
This dual chart reveals the core insight: while the frequency of great films has remained relatively stable, the percentage of quality films has plummeted as production volume exploded.
🏁 Summary of Findings
Based on the filtered data, here are the key takeaways from the analysis:
Decade-by-Decade Breakdown
Decade
Total Produced
Great Films
Classics/Year
% Quality
Status
1940
24
11
1.1
45.8
High Signal
1950
11
4
0.4
36.4
High Signal
1960
10
8
0.8
80.0
High Signal
1970
10
5
0.5
50.0
High Signal
1980
12
5
0.5
41.7
High Signal
1990
32
7
0.7
21.9
High Signal
2000
65
6
0.6
9.2
Moderate
2010
355
12
1.2
3.4
Moderate
2020
261
11
1.1
4.2
Moderate
Key Insights
The Volume Explosion: The 2010s produced 14.8x more films than the 1940s (355 vs. 24), while great films only increased 1.1x (12 vs. 11).
The Percentage Collapse: In the 1940s, 45.8% of holiday films were “great.” By the 2010s, this dropped to 3.4%—a 92.6% decline in hit rate.
Stable Frequency, Buried Quality: Modern decades maintain similar absolute numbers of quality films, but finding them now requires sifting through 14.8x more content.
The Discoverability Crisis: Your personal collection (18.5% above average) represents successful curation—a skill that’s become exponentially more valuable in the streaming era.
🏆 Top 20 Holiday Films of All Time
Based on IMDb ratings, here are the highest-rated holiday films in the dataset (filtered by our 70-minute methodology):
The 20 Greatest Holiday Films (Feature Length)
Rank
Title
Year
IMDb Rating
Meta Score
Runtime
1
ABC Stage 67: A Christmas Memory
1966
9.0
NA
51
2
It’s a Wonderful Life
1946
8.6
89
130
3
A Kylie Christmas: Live from the Royal Albert Hall
2015
8.6
NA
120
4
Anne of Green Gables
1985
8.5
NA
199
5
Jingle Vingle
2022
8.5
NA
96
6
Christmas Eve on Sesame Street
1978
8.4
NA
60
7
The Original Christmas Classics
1965
8.4
NA
NA
8
How the Grinch Stole Christmas!
1966
8.3
NA
26
9
A Charlie Brown Christmas
1965
8.3
NA
25
10
The Apartment
1960
8.3
94
125
11
Holiday Hideaway
2022
8.3
NA
96
12
Die Hard
1988
8.2
72
132
13
Klaus
2019
8.2
65
96
14
A Christmas Carol
1951
8.1
NA
86
15
Rudolph the Red-Nosed Reindeer
1964
8.0
NA
47
16
The Shop Around the Corner
1940
8.0
96
99
17
Miracle on 34th Street
1947
7.9
88
96
18
The Nightmare Before Christmas
1993
7.9
82
76
19
Edward Scissorhands
1990
7.9
74
105
20
The Muppet Christmas Carol
1992
7.8
64
85
Era Breakdown: 11 films from the classic era (pre-1980) vs. 9 from the modern era (1980+).
Observation: The presence of 9 modern films in the top 20 confirms that quality hasn’t disappeared—it’s simply become harder to find among the exponentially larger pool of releases.
💰 Box Office Performance Analysis
Does critical acclaim translate to commercial success? Let’s examine the relationship between quality and box office gross.
Data Limitation: Unfortunately, box office gross data is not available in the current dataset. This analysis requires additional data to be populated.
To enable this analysis, the dataset would need a ‘gross’ column with actual box office revenue figures (e.g., from Box Office Mojo or The Numbers).
🎭 Actor Analysis: The Holiday Movie Stars
Who are the most prolific holiday movie actors, and does quantity equal quality?
Most Prolific Holiday Movie Actors
Actors with Most Holiday Films
Actor
# Films
Avg Rating
Best Film Rating
Lacey Chabert
12
6.28
7.0
Stephen Huszar
10
6.01
7.0
Alicia Witt
8
6.15
6.4
Andrew W. Walker
8
6.65
7.6
Candace Cameron Bure
8
6.51
7.0
Corey Sevier
8
6.26
7.1
Merritt Patterson
8
6.42
6.9
Ashley Williams
7
6.29
6.8
Cindy Busby
7
5.91
6.9
Jesse Hutch
7
6.06
6.6
Jessica Lowndes
7
5.96
6.7
Rachel Boston
7
6.04
6.7
Robin Dunne
7
6.14
6.8
Teryl Rothery
7
6.41
7.1
Ashley Newbrough
6
5.90
6.7
Insight: These actors represent the “holiday movie specialists”—stars who have built careers around the genre, particularly in the Hallmark/Lifetime era of high-volume production.
Highest-Rated Holiday Movie Actors (Minimum 3 Films)
Actors with Highest Average Ratings
Actor
# Films
Avg Rating
Best Film Rating
James Stewart
3
7.80
8.6
Arthur Rankin Jr.
4
7.40
7.7
Paul Frees
3
7.30
7.7
Bing Crosby
4
7.28
7.6
Tyler Hynes
4
7.05
7.5
Shirley MacLaine
3
7.00
8.3
Lucas Bryant
3
6.93
7.0
Steve Bacic
3
6.93
7.5
Warren Christie
3
6.93
7.3
Spring Byington
3
6.90
7.1
Amy Groening
3
6.83
6.9
Alison Sweeney
4
6.80
7.0
Autumn Reeser
3
6.80
7.1
Kimberley Sustad
5
6.80
7.2
Kristoffer Polaha
4
6.80
7.2
Insight: Classic-era actors dominate this list, suggesting that quality was more consistent when fewer holiday films were being produced.
Interactive Actor Search
Use the search box below to find all holiday films by any actor in the dataset:
How to use: Type an actor’s name in the “Actor” search box above to filter the table. You can also search by film title, year, or sort by any column.
Actor Quality vs. Quantity
Insight: Actors appearing in multiple holiday films average 6.16 vs. dataset average of 6.08. This suggests that specialization in holiday films doesn’t necessarily predict quality—consistent with our broader finding about volume versus excellence.
🎬 Your Collection Analysis
Your Personal Collection
Title
Year
IMDb Rating
Meta Score
Christmas in Connecticut
1945
7.3
64
It’s a Wonderful Life
1946
8.6
89
The Bishop’s Wife
1947
7.6
73
The Lemon Drop Kid
1951
7.0
NA
White Christmas
1954
7.6
56
Die Hard
1988
8.2
72
Scrooged
1988
6.9
38
Home Alone
1990
7.7
63
Edward Scissorhands
1990
7.9
74
Home Alone 2: Lost in New York
1992
6.9
46
The Muppet Christmas Carol
1992
7.8
64
Christmas in Connecticut
1992
4.8
NA
The Santa Clause
1994
6.6
57
Love Actually
2003
7.6
55
Elf
2003
7.1
66
Four Christmases
2008
5.7
41
Collection Average: 7.21 vs. Dataset Average: 6.08
Your collection’s average rating is 18.5% higher than the overall dataset average.
Hit Rate Context: The decades your collection spans averaged a 31% quality rate—meaning you successfully avoided 69% of the “noise” in those eras.
Curation Success: Your collection demonstrates effective quality filtering across multiple decades, from the golden age through the modern streaming era. This validates both the timeless appeal of classic films and the existence of quality modern entries—when properly curated.
💡 Conclusions
The data reveals a paradox: quality hasn’t disappeared, but it has become invisible.
The Core Finding
While modern decades produce great films at roughly the same absolute rate as earlier eras, the signal-to-noise ratio has collapsed catastrophically:
1940s: 11 great films out of 24 total (45.8% hit rate)
2010s: 12 great films out of 355 total (3.4% hit rate)
This represents a 92.6% decline in the probability that a random holiday film will be worth watching.
The Discoverability Problem
The streaming era hasn’t killed quality—it has buried it. Production volume increased 14.8x while great film output remained relatively flat. The modern viewer faces a curation challenge that didn’t exist in earlier eras:
1940s: You could reasonably watch every holiday release in a season
2010s: Achieving the same requires watching 36 films per year
The Real Shift
The fundamental change isn’t in Hollywood’s ability to produce quality holiday films—it’s in the economic incentive to produce volume. Streaming platforms prioritize content libraries over individual film quality, resulting in a “spray and pray” approach where greatness becomes accidental rather than intentional.
Your Advantage
Your personal collection, with its 18.5% quality premium, demonstrates that: 1. Great holiday films continue to exist across all eras 2. Successful curation requires active effort, not passive discovery 3. The skill of quality discernment is exponentially more valuable in the modern content landscape
The takeaway: Modern holiday classics do exist—but finding them requires cutting through unprecedented noise. This analysis validates both nostalgia for the “signal-rich” past and optimism about quality content in the present, while acknowledging the very real challenge of discoverability in the streaming age.
