I watch a lot of movies, a fact that my wife, and occasionally my children, like to remind of. Unlike the average, non-geeky, movie fan, though, I am constantly analyzing the process I go through to determine which movies I watch. I don’t like to watch mediocre, or worse, movies. I’ve pretty much eliminated bad movies from my selections. But, every now and then a movie I “like” rather than “really like” will get past my screen.
Over the next three weeks I’ll outline the steps I’m taking this year to improve my “really like” movie odds. Starting this week with New Movies, I’ll lay out a focused strategy for three different types of movie selection decisions.
The most challenging “really like” movie decision I make is which movies that I’ve never seen before are likely to be “really like” movies. There is only a 39.3% chance that watching a movie I’ve never seen before will result in a “really like” experience. My goal is to improve those odds by the end of the year.
The first step I’ve taken is to separate movies I’ve seen before from movies I’ve never seen in establishing my “really like” probabilities. As a frame of reference, there is a 79.5% chance that I will “really like” a movie I’ve seen before. By setting my probabilities for movies I’ve never seen off of the 39.3% probability I have created a tighter screen for those movies. This should result in me watching fewer never-before-seen movies then I’ve typically watched in previous years. Of the 20 movies I’ve watched so far this year, only two were never-before-seen movies.
The challenge in selecting never-before-seen movies is that, because I’ve watched close to 2,000 movies over the last 15 years, I’ve already watched the “cream of the crop” from those 15 years.. From 2006 to 2015, there were 331 movies that I rated as “really like” movies, that is 33 movies a year, or less than 3 a month. Last year I watched 109 movies that I had never seen before. So, except for the 33 new movies that came out last year that, statistically, might be “really like” movies, I watched 76 movies that didn’t have a great chance of being “really like” movies.
Logically, the probability of selecting a “really like” movie that I’ve never seen before should be highest for new releases. I just haven’t seen that many of them. I’ve only seen 6 movies that were released in the last six months and I “really liked” 5 of them. If, on average, there are 33 “really like” movies released each year, then, statistically, there should be a dozen “really like” movies released in the last six months that I haven’t seen yet. I just have to discover them. Here is my list of the top ten new movie prospects that I haven’t seen yet.
|My Top Ten New Movie Prospects|
|New Movies = < Release Date + 6 Months|
|Movie Title||Release Date||Last Data Update||“Really Like” Probability|
|Beatles, The: Eight Days a Week||9/16/2016||2/4/2017||78.7%|
|Before the Flood||10/30/2016||2/4/2017||51.7%|
|Fantastic Beasts and Where to Find Them||11/18/2016||2/4/2017||51.7%|
Based on my own experience, I believe you can identify most of the new movies that will be “really like” movies within 6 months of their release, which is how I’ve defined “new” for this list. I’m going to test this theory this year.
In case you are interested, here is the ratings data driving the probabilities.
|My Top Ten New Movie Prospects|
|Movie Site Ratings Breakdown|
|Movie Title||# of Ratings All Sites||Age 45+ IMDB||Rotten Tomatoes **||Criticker||Movielens||Netflix|
|Hacksaw Ridge||9,543||8.2||CF 86%||8.3||8.3||8.6|
|Doctor Strange||16,844||7.7||CF 90%||8.2||8.3||7.8|
|Hidden Figures||7,258||8.2||CF 92%||7.7||7.3||8.2|
|Beatles, The: Eight Days a Week||1,689||8.2||CF 95%||8.0||7.3||8.0|
|Before the Flood||1,073||7.8||F 70%||7.6||8.2||7.8|
|Fantastic Beasts and Where to Find Them||14,307||7.5||CF 73%||7.3||6.9||7.6|
|Deepwater Horizon||40,866||7.1||CF 83%||7.8||7.6||7.6|
|*All Ratings Except Rotten Tomatoes Calibrated to a 10.0 Scale|
|** CF = Certified Fresh, F = Fresh|
Two movies, Hacksaw Ridge and Arrival, are already probably “really like” movies and should be selected to watch when available. The # of Ratings All Sites is a key column. The ratings for Movielens and Netflix need ratings volume before they can credibly reach their true level. Until, there is a credible amount of data the rating you get is closer to what an average movie would get. A movie like Fences, at 4,418 ratings, hasn’t reached the critical mass needed to migrate to the higher ratings I would expect that movie to reach. Deep Water Horizon, on the other hand, with 40,866 ratings, has reached a fairly credible level and may not improve upon its current probability.
I’m replacing my monthly forecast on the sidebar of this website with the top ten new movie prospects exhibit displayed above. I think it is a better reflection of the movies that have the best chance of being “really like” movies. Feel free to share any comments you might have.