If You Like planes, trains and automobiles
Based on real preference data from thousands of voters, here's what fans of planes, trains and automobiles also love. Use these connections to discover your next favorite.
138 connections found
#184xUncle Buck
1989
#274xTrading Places
1983
#370xCaddyshack
1980
#450xE.T. the Extra-Terrestrial
1982
#548xYoung Frankenstein
1974
#646xBig
1988
#742xAirplane!
1980
#842xBill & Ted's Excellent Adventure
1989
#941xWayne's World
1992
#1040xMeet the Parents
2000
#1137xGhostbusters II
1989
#1236xRocky
1976
#1332xThe Goonies
1985
#1432xMrs. Doubtfire
1993
#1532xSpaceballs
1987
#1631xStand by Me
1986
#1730xWho Framed Roger Rabbit
1988
#1830xWilly Wonka & the Chocolate Factory
1971
#1930xJaws
1975
#2028xZoolander
2001
#2127xSchool of Rock
2003
#2227xGremlins
1984
#2325xThe Lion King
1994
#2425xNapoleon Dynamite
2004
#2524xAnchorman: The Legend of Ron Burgundy
2004raiders of the lost ark
#2724xGhostbusters
1984
#2823xOffice Space
1999
#2921xGroundhog Day
1993
#3021xThe Addams Family
1991
#3121xTotal Recall
1990
#3221xRain Man
1988
#3320xDie Hard
1988
#3419xTaxi Driver
1976
#3519xAliens
1986
#3619xIndiana Jones and the Last Crusade
1989
#3719xBeetlejuice
1988
#3819xBack to the Future Part II
1989
#3918xPsycho
1960
#4018xFerris Bueller's Day Off
1986
#4118xHome Alone
1990Terminator
1984
#4318xMonty Python and the Holy Grail
1975
#4416xBraveheart
1995
#4516xThe Bourne Identity
2002
#4616xTerminator 2: Judgment Day
1991
#4716xIndiana Jones and the Temple of Doom
1984
#4816xSuperbad
2007Star Wars: Episode VI - Return of the Jedi
1983
#5015xHot Fuzz
2007
#5115xBack to the Future Part III
1990
#5215xDead Poets Society
1989
#5315xFull Metal Jacket
1987
#5415xThe Princess Bride
1987
#5515xFargo
1996
#5615xOcean's Eleven
2001
#5714xAlien
1979
#5814xFinding Nemo
2003
#5914xThe Sixth Sense
1999Goodfellas
1990
#6114xToy Story
1995
#6214xBeing John Malkovich
1999
#6313xCast Away
2000
#6413xScarface
1983
#6513xMinority Report
2002
#6613xThe Breakfast Club
1985
#6713xShaun of the Dead
2004
#6813xJurassic Park
1993
#6913xBlade Runner
1982
#7013x2001: A Space Odyssey
1968
#7113xBack to the Future
1985
#7212xLéon: The Professional
1994
#7312xThe Big Lebowski
1998
#7412xSaving Private Ryan
1998Star Wars: Episode V - The Empire Strikes Back
1980
#7612xThe Green Mile
1999
#7712xEdward Scissorhands
1990
#7812xThe Butterfly Effect
2004
#7911xThe Fifth Element
1997
#8011xMen in Black
1997
#8111xMad Max: Fury Road
2015
#8211xThe Shining
1980
#8311xThe Hangover
2009
#8411xThe Nightmare Before Christmas
1993
#8511xSin City
2005
#8611xThe Silence of the Lambs
1991
#8711xKill Bill: Vol. 1
2003
#8811xWALL·E
2008
#8910xGood Will Hunting
1998
#9010xLittle Miss Sunshine
2006
#9110xThe Departed
2006
#9210xDeadpool
2016
#9310xZombieland
2009
#9410xDistrict 9
2009
#9510xGuardians of the Galaxy Vol. 2
2017
#969.8xGladiator
2000
#979.7xThe Incredibles
2004
#989.6xThe Godfather
1972
#999.6xShrek
2001
#1009.4xNo Country for Old Men
2007
#1019.3xI Am Legend
2007
#1029.3xSnatch
2001
#1039.2xAmerican Psycho
2000
#1049.1xMonsters, Inc.
2001
#1059.1xCatch Me If You Can
2003
#1068.9xUp
2009
#1078.9xThe Truman Show
1998
#1088.9xGone Girl
2014
#1098.8xForrest Gump
1994
#1108.7xReservoir Dogs
1992
#1118.6xTrainspotting
1996
#1128.4xSe7en
1995
#1138.4xThe Martian
2015
#1148.4xThe Shawshank Redemption
1994
#1158.4xAmerican History X
1998
#1167.4xThe Avengers
2012
#1177.3xThe Matrix
1999
#1187.3xThe Wolf of Wall Street
2013
#1197.3xThe Dark Knight Rises
2012
#1207.2xBatman Begins
2005
#1217.1xEternal Sunshine of the Spotless Mind
2004
#1227.1xAvatar
2009
#1237.1xDonnie Darko
2001
#1247.0xThe Lord of the Rings: The Fellowship of the Ring
2001
#1257.0xDjango Unchained
2012
#1267.0xInglourious Basterds
2009
#1277.0xIron Man
2008
#1286.9xThe Lord of the Rings: The Return of the King
2003
#1296.8xGuardians of the Galaxy
2014
#1306.8xThe Lord of the Rings: The Two Towers
2002
#1316.4xThe Dark Knight
2008
#1326.1xPulp Fiction
1994
#1336.1xV for Vendetta
2006
#1346.0xShutter Island
2010
#1355.8xThe Prestige
2006
#1365.7xInterstellar
2014
#1375.4xFight Club
1999
#1384.6xInception
2010How does this work?
These recommendations are based on real voting data, not algorithms. When thousands of people vote on their favorites, patterns emerge — people who love planes, trains and automobiles consistently tend to also love certain other things. The "strength" score shows how much more likely fans of planes, trains and automobiles are to enjoy each recommendation compared to the average person.
Unlike algorithmic recommendations, these connections come from actual human preferences. A high strength score means the connection is genuine — not just because two items share a category, but because the same people genuinely love both.