Movielogr

Home

movie poster

Rating: 8 stars

Seen 2 times

Seen on: 12/09/2011, 06/05/2011

View on: IMDb | TMDb

X-Men: First Class (2011)

Directed by Matthew Vaughn

Action

Most recently watched by jakeneff, noahphex, sensoria, noahphex, jenerator, noahphex, sensoria

Overview

Before Charles Xavier and Erik Lensherr took the names Professor X and Magneto, they were two young men discovering their powers for the first time. Before they were arch-enemies, they were closest of friends, working together with other mutants (some familiar, some new), to stop the greatest threat the world has ever known.

Rated PG-13 | Length 132 minutes

Actors

Lucas Till | Jason Flemyng | Don Creech | Ludger Pistor | Rade Serbedzija | James Remar | Tony Curran | Nicholas Hoult | Kevin Bacon | James McAvoy | Ray Wise | Hugh Jackman | James Faulkner | Rose Byrne | Rebecca Romijn | Michael Ironside | Glenn Morshower | Matt Craven | Corey Johnson | Michael Fassbender | Oliver Platt | Wilfried Hochholdinger | Demetri Goritsas | John F. Kennedy | January Jones | Randall Batinkoff | Zoë Kravitz | Jason Beghe | Edi Gathegi | Olek Krupa | Sasha Pieterse | Jennifer Lawrence | Brendan Fehr | Morgan Lily | Bill Milner | Annabelle Wallis | Peter Stark | Gene Farber | Michael Medeiros | Katrine De Candole | Gregory Cox | Arthur Darbinyan | Sean Brown | Laurence Belcher | Caleb Landry Jones | David Joseph Martinez | Josh Cohen | Álex González | Andrei Zayats | Beth Goddard | Jarid Faubel | Greg Kolpakchi | Neil Fingleton | Venya Manzyuk | Georg Nikoloff | Juan Herrera | Carlos Peres | Johnny Otto | David Agranov | Éva Magyar | Greg Savage | David Crow | Kieran Patrick Campbell | Yuri Naumkin | Leonard Redlich | Marios | Josh Ramsay

Viewing Notes

There were lots of plot holes and in general, I felt it tried to do too much, but it was still a damn good movie.

The New X-Men was my first teenage comic book love. I bought Issue #111 off a comic book rack in a convenience store while at summer camp and was immediately hooked on the combo of Claremont and Byrne.

First Class reminded me a lot of those stories, even though it’s set in the ‘60s. I quite enjoyed the pseudo-retro style, especially on Sebastian Shaw. Bacon really nailed this character! It was great to see him in such a cool role.

Most of the casting was a surprise to me since I try to avoid reviews and pre-release news about movies. I was kinda shocked to see Jennifer Lawrence in the role of Mystique. I thought she acquitted herself nicely. It’s great to see her getting work after her excellent turn in Winter’s Bone. I’m guessing The Hunger Games will put her over the top.

Aside from Bacon, the one who steals the show here is Michael Fassbender as Magneto. He brings a lot of humanity and conflict to his character.

Jason Flemyng as Azazel was practically unrecognizable under all the makeup. I actually had to look him up on IMDB to reconnect the name to the face.

Going back to the comics of my youth, it was great to see some of the characters from that era, since that’s when I first got introduced to the likes of Moira McTaggart, Banshee, Havok and The Hellfire Club (which, if I recall correctly, is based on a real sex club that operated in NYC back in the ‘70s and/or ‘80s).

Here’s hoping we get more films in the series that do as good a job or better in exploring this universe.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0015
Controller Execution Time ( Members / Movie Detail )  0.0232
Total Execution Time  0.0248
  GET DATA  
No GET data exists
  MEMORY USAGE  
550,896 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sensoria/movie_detail/7058
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.0066 seconds)  (Hide)
0.0003   SELECT 1
FROM `ml_sessions`
WHERE `id` = '69f0807bf0058dfc0da224447554ee406e35c857'
AND `ip_address` = '216.73.216.111' 
0.0002   SELECT GET_LOCK('2b036dadad10baee50c3b78271e1a767', 300) AS ci_session_lock 
0.0003   SELECT `data`
FROM `ml_sessions`
WHERE `id` = '69f0807bf0058dfc0da224447554ee406e35c857'
AND `ip_address` = '216.73.216.111' 
0.0003   SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'sensoria'
 LIMIT 1 
0.0004   SELECT `MV`.`title_id`, `MT`.`tmdb_id`
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movies` `MV` ON `MV`.`title_id` = `MT`.`title_id`
WHERE `MV`.`movie_id` = 7058
AND `MV`.`user_id` = 1
 LIMIT 1 
0.0003   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 
0.0002   SET SESSION group_concat_max_len = 12288 
0.0021   SELECT `MV`.`title_id`, `MV`.`movie_id`, COUNT(DISTINCT MV.title_id) AS mv_count, `title`, `prefix`, `year`, `imdb_link`, `MT`.`imdb_id`, `MT`.`tmdb_id`, `overview`, `certification`, `runtime`, `genre_id_01`, `genre_id_02`, `genre_id_03`, MAX(MP.filename) AS filename, `G1`.`genre_name` AS `genre_name_01`, `G2`.`genre_name` AS `genre_name_02`, `G3`.`genre_name` AS `genre_name_03`, `date_viewed`, `notes`, `MV`.`format_id`, `FMT`.`format_name`, `MV`.`source_id`, `SRC`.`source_name`, `MV`.`device_id`, `DVC`.`device_name`, `MV`.`rating_id`, `STR`.`star_rating`, `rewatch`, GROUP_CONCAT(DISTINCT(DR.director_name) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS directors, GROUP_CONCAT(DISTINCT(DR.tmdb_director_id) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS director_ids, GROUP_CONCAT(DISTINCT(ACT.actor_name) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actors, GROUP_CONCAT(DISTINCT(ACT.tmdb_actor_id) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actor_ids
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movies` `MV` ON `MV`.`title_id` = `MT`.`title_id`
LEFT JOIN `ml_movie_posters` `MP` ON `MV`.`title_id` = `MP`.`title_id`
LEFT JOIN `ml_lookup_genres` `G1` ON `MV`.`genre_id_01` = `G1`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G2` ON `MV`.`genre_id_02` = `G2`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G3` ON `MV`.`genre_id_03` = `G3`.`genre_id`
LEFT JOIN `ml_lookup_formats` `FMT` ON `MV`.`format_id` = `FMT`.`format_id`
LEFT JOIN `ml_lookup_sources` `SRC` ON `MV`.`source_id` = `SRC`.`source_id`
LEFT JOIN `ml_lookup_devices` `DVC` ON `MV`.`device_id` = `DVC`.`device_id`
LEFT JOIN `ml_movie_ratings_ten_star` `STR` ON `MV`.`rating_id` = `STR`.`rating_id`
LEFT JOIN `ml_junction_movies_directors` `JMD` ON `MT`.`title_id` = `JMD`.`title_id`
LEFT JOIN `ml_directors_new` `DR` ON `JMD`.`tmdb_director_id` = `DR`.`tmdb_director_id`
LEFT JOIN `ml_junction_movies_actors` `JMA` ON `MT`.`title_id` = `JMA`.`title_id`
LEFT JOIN `ml_actors_new` `ACT` ON `JMA`.`tmdb_actor_id` = `ACT`.`tmdb_actor_id`
WHERE `MV`.`movie_id` = 7058
AND `MV`.`user_id` = 1
ORDER BY `date_viewed` DESC 
0.0002   SET SESSION group_concat_max_len = 1024 
0.0003   SELECT `event_title`, `JME`.`event_id`
FROM `ml_junction_movies_events` `JME`
LEFT JOIN `ml_movie_events` `EV` ON `JME`.`event_id` = `EV`.`event_id`
WHERE `JME`.`movie_id` = 7058 
0.0002   SELECT `tag`, `JMT`.`tag_id`
FROM `ml_junction_movies_tags` `JMT`
LEFT JOIN `ml_tags` `MT` ON `JMT`.`tag_id` = `MT`.`tag_id`
WHERE `JMT`.`movie_id` = 7058 
0.0002   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 
0.0003   SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7058
 LIMIT 1 
0.0002   SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '18'
 LIMIT 1 
0.0004   SELECT `MV2`.`date_viewed`, `MV2`.`movie_id`
FROM `ml_movies` `MV`
LEFT JOIN `ml_movies` `MV2` ON `MV`.`title_id` = `MV2`.`title_id` AND `MV`.`user_id` = `MV2`.`user_id`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7058
GROUP BY `MV2`.`movie_id`
ORDER BY `MV2`.`date_viewed` DESC 
0.0003   SELECT `comment_id`, `comment`, `commenter_id`, `timestamp`, `username`, `email_address`
FROM `ml_comments` `MC`
JOIN `ml_users` `MU` ON `MU`.`user_id` = `MC`.`commenter_id`
WHERE `movie_id` = 7058 
0.0004   SELECT `username`, `date_viewed`, `MV`.`movie_id`
FROM `ml_users` `MU`
JOIN `ml_movies` `MV` ON `MV`.`user_id` = `MU`.`user_id`
JOIN `ml_movie_titles` `MT` ON `MT`.`title_id` = `MV`.`title_id`
WHERE `MT`.`title_id` = 3271
ORDER BY `date_viewed` DESC
 LIMIT 10 
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)