There Are No Turkeys in the Objective Top Seven Movies From 1992 to 1998

Shall we call it “The Drive for Twenty Five”? If so, this installment of our journey to the Objective Top Twenty Five Movies of the last Twenty Five years begs the question which of these Cinematic Seven will survive to Twenty Five.

Shall we call it “The Drive for Twenty Five”? If so, this installment of our journey to the Objective Top Twenty Five Movies of the last Twenty Five years begs the question which of these Cinematic Seven will survive to Twenty Five. By adding 1998 to the Objective Database more discrete groupings of data are statistically viable. As future years are added the number of groupings will grow resulting in many changes to this list. From the initial Top Six list that was published just two weeks ago, only three movies remain in the Top Seven. I think we can expect this kind of volatility with each year we add. How many of these movies will be in the Top Twenty Five at the end? Fewer than we’d expect, I’m sure.

Here’s our significant seven:

7. Scent of a Woman (IMDB 8.0, Certified Fresh 88%, CinemaScore A, Major Academy Award Win)

This movie is a favorite of mine. It produced Al Pacino’s only Academy Award win after being shut out for his seven previous nominations.

6. Good Will Hunting (IMDB 8.3, Certified Fresh 97%, CinemaScore A. Major  Academy Award Win)

One of my followers wondered why his favorite movie didn’t make the list. Good Will Hunting is a good illustration of what it takes. It requires high ratings from all feedback groups, movie watchers, movie critics, opening night moviegoers, and peer movie artists.

5. The Shawshank Redemption (IMDB 9.3, Certified Fresh 91%, CinemaScore A, Major Academy Award Nomination)

Another one of the original Top Six. The Achilles Heel for this movie from an objective rating standpoint is its failure to win a major Academy Award despite three major nominations.

4. The Usual Suspects (IMDB 8.6, Certified Fresh 88%, No CinemaScore rating, Major Academy Award Win)

Because this is an objective ranking rather than subjective, Kevin Spacey movies are still considered. In the long run, I wonder how much the absence of a CinemaScore rating will hurt this movie and, if so, should it.

3. The Lion King (IMDB 8.5, Certified Fresh 83%, CinemaScore A+, Minor Academy Award Win)

A few weeks before the release of this picture, Elton John was given a private screening of the movie. He noticed the love song he wrote wasn’t in the film and successfully lobbied to have it put back in. That song, Can You Feel the Love Tonight, won Elton John an Academy Award for Best Original Song.

2. Saving Private Ryan (IMDB 8.6, Certified Fresh 92%, CinemaScore A, Major Academy Award Win)

The only movie from the just added 1998 year to make the list. It is also the only movie on the list to be the top grossing movie for the year it was released.

1. Schindler’s List (IMDB 8.9, Certified Fresh 96%, CinemaScore A+, Major Academy Award Win)

According to the Objective “Really Like” algorithm, a 76.98% “really like” probability is the highest score that can be achieved with the algorithm. So far, Schindler’s List is the only movie with that perfect score.

***

Disney animated movies rule Thanksgiving weekend. According to Box Office Mojo, Disney owns 9 of the 10 highest grossing Thanksgiving movies of all time. Coco, which opened in theaters yesterday, is this year’s entrant into their tradition of Thanksgiving dominance. Early IMDB ratings give it a 9.1 average rating to go along with its 96% Certified Fresh Rotten Tomatoes rating. This morning CinemaScore gave it an A+ rating.

Also, two more Oscar hopefuls go into limited release this weekend. Darkest Hour is the perfect bookend to Dunkirk. It follows Winston Churchill’s response to the events at Dunkirk. Gary Oldman’s portrayal of Churchill has him on everyone’s short list for Best Actor. Also worth considering is a festival favorite, Call Me By Your Name, which was nominated this week for an Independent Spirit Award for Best Picture.

Happy Thanksgiving to you and your families.

Author: Mad Movie Man

I love good movies. In my prior life I worked with predictive models. I've combined my love of movies with my prior experience to create a simple Bayesian probability model to help select movies that you will probably "really like".

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