Movielogr

Home

movie poster

Rating: 2.5 stars

Tags

Netflix Watch Instantly

Seen 1 time

Seen on: 02/27/2010

View on: IMDb | TMDb

Bag Boy (2007)

Directed by Mort Nathan

Comedy

Most recently watched by noahphex

Overview

A teenager enters the competitive world of grocery store bagging.

Rated PG-13 | Length 94 minutes

Actors

Dennis Farina | Larry Miller | Brooke Shields | Richard Kind | Bruce Altman | Robert Hoffman | Zen Gesner | Paul Campbell | Terence Goodman | Wesley Jonathan | Lisa Darr | Marika Dominczyk | Nick Lashaway | Rob Moran | Josh Dean | Carlos Lacámara

Viewing Notes

Who ever thought someone would make a movie about competitive grocery bagging? Wait, isn’t there a scene in Employee of the Month with Dax Shepard and Dane Cook doing this exact same thing that came out a year earlier? I think so.

Anyways, Bag Boy tries too hard to actually have a serious edge to it with the lead kid Paul Campbell (who later goes on to be in Battlestar Galactica) trying to make a connection with his dream girl Barbi (Marika Dominczyk). Because of the long stretches of non-wacky comedy where the film maker is trying to make this into a teen rom-com it suffers and gets a little tedious.

National Lampoon movies tend to always have one or two B-listers or old TV stars showing up in them and this time it’s Dennis Farina as the grocery story owner who used to train some of the best baggers in the country. You also have Brooke Shields as the horny MILF who constantly hits on the check-out guys. There’s a weird sub-plot that has no bearing in the film at all, about the black checkout guy who is trying to become a rap star and when he gets no props from the record company because he’s not hard or hasn’t been arrested or shot, he goes around to a white neighborhood trying to get people to fear him. I have no clue what it’s doing in this movie because it has nothing to do with either of the two main story lines.  It’s also only mildly amusing.

All in all Bag Boy doesn’t go far enough in its sexiness, its humor or in it’s story. One thing you kind of hope for with a National Lampoon movie is lots of naked breasts and ridiculous humor but we don’t really get that here and it’s shame. Let’s keep the romantic comedies elsewhere.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0020
Controller Execution Time ( Members / Movie Detail )  0.0863
Total Execution Time  0.0883
  GET DATA  
No GET data exists
  MEMORY USAGE  
539,800 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/noahphex/movie_detail/4085
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.0062 seconds)  (Hide)
0.0004   SELECT 1
FROM `ml_sessions`
WHERE `id` = 'b39b68308e920e4dfee3338b0b9dc0e1359ba885'
AND `ip_address` = '216.73.216.111' 
0.0002   SELECT GET_LOCK('09042f5549012cb98d8b383c9765796f', 300) AS ci_session_lock 
0.0003   SELECT `data`
FROM `ml_sessions`
WHERE `id` = 'b39b68308e920e4dfee3338b0b9dc0e1359ba885'
AND `ip_address` = '216.73.216.111' 
0.0004   SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'noahphex'
 LIMIT 1 
0.0003   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` = 4085
AND `MV`.`user_id` = 8
 LIMIT 1 
0.0004   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 8
 LIMIT 1 
0.0002   SET SESSION group_concat_max_len = 12288 
0.0017   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_five_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` = 4085
AND `MV`.`user_id` = 8
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` = 4085 
0.0003   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` = 4085 
0.0002   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 8
 LIMIT 1 
0.0002   SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 8
AND `MV`.`movie_id` = 4085
 LIMIT 1 
0.0002   SELECT `star_rating`
FROM `ml_movie_ratings_five_star` `MR`
WHERE `MR`.`rating_id` = '12'
 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` = 8
AND `MV`.`movie_id` = 4085
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` = 4085 
0.0003   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` = 2591
ORDER BY `date_viewed` DESC
 LIMIT 10 
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)