Movielogr

movie poster

Rating: 7.5 stars

Seen 1 time

Seen on: 03/26/2011

View on: IMDb | TMDb

Mystery Team (2009)

Directed by Dan Eckman

Comedy

Most recently watched by sensoria, noahphex, suspectk

Overview

A group of former Encyclopedia Brown-style child-detectives struggle to solve an adult mystery.

Rated R | Length 97 minutes

Actors

Matt Walsh | Donald Glover | D.C. Pierson | Dominic Dierkes | Aubrey Plaza | Dan Eckman | Meggie McFadden | Gregory Burke | Tom Shillue | Ron Simons | Glenn Kalison | Kevin Brown | Kay Cannon | Ben Schwartz | Bobby Moynihan | Ellie Kemper | Robbie Sublett | John Lutz | Peter Saati | Will Hines | Kristopher Kling | Nick Packard | Daphne Ciccarelle | Jon Daly

Viewing Notes

I know nothing about any of the talent surrounding this film, or where it came from. I also knew nothing about the movie itself except that a lot of people loved it when it first came out.

It is hilariously wrong! Donald Glover is excellent and the combination of youthful innocence with really raunchy shit happening is excellent.

I highly recommend watching this on Netflix Instant Watch while it’s around. Completely worth it. I plan on rewatching it because I was fading in and out at the end as it was really late.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0030
Controller Execution Time ( Members / Movie Detail )  0.0447
Total Execution Time  0.0478
  GET DATA  
No GET data exists
  MEMORY USAGE  
531,040 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sensoria/movie_detail/2297
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 16 (0.0070 seconds)  (Hide)
0.0003  
SELECT GET_LOCK('8a87e92c99aaee51cd0557c90678c6f6', 300) AS ci_session_lock ?>
0.0004  
SELECT `data`
FROM `ml_sessions`
WHERE `id` = '416a252f6b862d2d67445c69383290dcfc403f60'
AND `ip_address` = '216.73.216.6' ?>
0.0007  
SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'sensoria'
 LIMIT 1 ?>
0.0005  
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` = 2297
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 ?>
0.0020  
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` = 2297
AND `MV`.`user_id` = 1
ORDER BY `date_viewed` DESC ?>
0.0003  
SET SESSION group_concat_max_len = 1024 ?>
0.0004  
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` = 2297 ?>
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` = 2297 ?>
0.0002  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 ?>
0.0002  
SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 2297
 LIMIT 1 ?>
0.0003  
SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '17'
 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` = 2297
GROUP BY `MV2`.`movie_id`
ORDER BY `MV2`.`date_viewed` DESC ?>
0.0002  
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` = 2297 ?>
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` = 2098
ORDER BY `date_viewed` DESC
 LIMIT 10 ?>
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)