The Admiral

Summary: When the young republic of The Netherlands is attacked by England, France, and Germany, and the country is on the brink of civil war, only one man can lead the country's strongest weapon, the Dutch fleet: Michiel de Ruyter.

Release Date: January 29, 2015

Genres: Action, Drama, Biography

Director: Roel Reiné

Writers: Lars Boom

, Alex van Galen

Runtime: 2 h 31 min

MPAA: 14A

Production: Farmhouse Film & TV, Ciné Cri De Coeur, AVROTROS, Grid-vfx, Rebel Entertainment

Distributor: Alameda Entertainment

Country: Netherlands

Language: Dutch

Movie budget: $ 8,000,000

Box office:

Budget:$8MWorldwide:$6.4M

Adaptation/remake:

based on true story, based on real person

14%

The Rotten Tomatoes audience rated this 14% higher than the critics.

67%81%

No Metacritic ratings imported yet.

28%0%

28% of the Stars & Main Cast are Female.

0% of the Stars & Main Cast are "diverse."

White100%

N/A

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CONTENT BREAKDOWN

Methodology

RottenTomatoes:

67%81%

Douban:

IMDb:

Kinopoisk:

Moviemeter:

OFDb:

Methodology

Cast

Stars:

Supporting cast:

Other Cast, Production

Other cast:

Production:

Representation

Star

Supporting

Other

Production

Race	White	Black	Mixed / Other	Total	Visuals	Info
Ethnic	2	1	1	4		This is the most reliable data source for accurate ethnic breakdowns of famous people. Often the information is crowdsourced by users and they cite all their sources (family trees, obituaries, census archives, etc.) on the bottom of the page. The only issue is converting their ambiguous and inconsistent verdicts into quantifiable variables. Source: https://ethnicelebs.com/
Kairos	2	1		3		A third party facial recognition software company we used to maintain objectivity. Upload images to the facial recognition demo page to check the veracity of our data set. Or use their API and do a bulk peer review if you'd like. Source: https://www.kairos.com/demos
Surname	3			3		A third party free program that uses US Census data to create an algorithm that analyzes surnames and guesses what ethnicity the person is. Obviously there are issues with this data set such as African Americans who have the last names of their ancestors' slave owner. However, when no other data set is available, this can give a rough estimate and expand the data pool for the less important cast members with no IMDb or TMDb image. Please consider downloading their source code via GitHub to verify the accuracy of our data set, and to peer review our conclusions. Source: https://pypi.org/project/ethnicolr/
Bettaface	1			1		A third party facial recognition software company we used to maintain objectivity. Upload images to the facial recognition demo page to check the veracity of our data set. Or use their API and do a bulk peer review if you'd like. Source: https://www.betafaceapi.com/demo_old.html
Familysearch	1			1
Total	9	2	1	12
Cast Percentages	75%	16.67%	8.33%	100%	{"name":"Cast Percentages","series":[{"name":"White","y":75,"color":"#2b908f","sliced":true,"selected":true},{"name":"Black","y":16.67,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":8.33,"color":"#55BF3B","sliced":true,"selected":true}],"prefix":""}
U.S. Population (2020) Percentage	57.84%	12.4%	9.32%		{"name":"U.S. Population (2020)","series":[{"name":"White","y":57.84,"color":"#2b908f"},{"name":"Arab","y":0.54,"color":"#DF5353"},{"name":"Asian","y":6,"color":"#90ee7e"},{"name":"Black","y":12.4,"color":"#f45b5b"},{"name":"Indian","y":1.35,"color":"#7798BF"},{"name":"Indigenous","y":1.12,"color":"#aaeeee"},{"name":"Latino","y":18.73,"color":"#eeaaee"},{"name":"Mixed \/ Other","y":9.32,"color":"#55BF3B"},{"name":"Jewish","y":2.02,"color":"#ff0066"}],"prefix":""}	Source: US Census (Note: Racial and ethnic categories overlap so the sum will not equal 100%.)
U.S. Population (2020) Representation	+17.16	+4.27	-0.99		{"name":"U.S. Population (2020)","series":[["White",57.84],["Black",12.4],["Mixed \/ Other",9.32]],"cast":[{"name":"White","y":75,"color":"#2b908f"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Mixed \/ Other","y":8.33,"color":"#55BF3B"}]}
U.S. Buying Power (2023) Percentage	72.69%	8.02%	1.54%		{"name":"U.S. Buying Power (2023)","series":[{"name":"White","y":13897000000000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1333100000000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1533100000000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":136400000000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1924000000000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":295300000000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: Selig Center, University of Georgia
U.S. Buying Power (2023) Representation	+2.31	+8.65	+6.79		{"name":"U.S. Buying Power (2023)","series":[["White",72.69],["Black",8.02],["Mixed \/ Other",1.54]],"cast":[{"name":"White","y":75,"color":"#2b908f"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Mixed \/ Other","y":8.33,"color":"#55BF3B"}]}
U.S. Average Individual Income (2018) Percentage	65.34%	9.43%	7.28%		{"name":"U.S. Average Individual Income (2018)","series":[{"name":"White","y":11825174998483,"color":"#2b908f","sliced":true,"selected":true},{"name":"Arab","y":0,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":1360705388565,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Black","y":1706765993728,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indian","y":0,"color":"#7798BF","sliced":true,"selected":true},{"name":"Indigenous","y":164296821776,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Latino","y":1721419354421,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":1318328353188,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Jewish","y":0,"color":"#ff0066","sliced":true,"selected":true}],"prefix":"$"}	Source: IPUMS-CPS, University of Minnesota
U.S. Average Individual Income (2018) Representation	+9.66	+7.24	+1.05		{"name":"U.S. Average Individual Income (2018)","series":[["White",65.34],["Black",9.43],["Mixed \/ Other",7.28]],"cast":[{"name":"White","y":75,"color":"#2b908f"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Mixed \/ Other","y":8.33,"color":"#55BF3B"}]}
World population (2019) Percentage	14.24%	14.47%	1.92%		{"name":"World population (2019) ","series":[{"name":"Mixed \/ Other","y":14688882870,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Latino","y":42991259469,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Indigenous","y":10971786583,"color":"#aaeeee","sliced":true,"selected":true},{"name":"White","y":108889096410,"color":"#2b908f","sliced":true,"selected":true},{"name":"Black","y":110601821551,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Asian","y":238860161621,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Arab","y":67406299429,"color":"#DF5353","sliced":true,"selected":true},{"name":"Indian","y":167470202093,"color":"#7798BF","sliced":true,"selected":true},{"name":"Jewish","y":2568698093,"color":"#ff0066","sliced":true,"selected":true}],"prefix":""}	NOTE: ZR is the first organization to ever create a global buying power divided by race. Essentially we just took data from CIA.gov FactBook, UN Population Estimates, and The World Bank's Population Estimates / Purchasing Power Parity Per Capita.
World population (2019) Representation	+60.76	+2.2	+6.41		{"name":"World population (2019) ","series":[["White",14.24],["Black",14.47],["Mixed \/ Other",1.92]],"cast":[{"name":"White","y":75,"color":"#2b908f"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Mixed \/ Other","y":8.33,"color":"#55BF3B"}]}
World Buying Power Percentage	36.48%	6.38%	1.81%		{"name":"World Buying Power","series":[{"name":"White","y":3010602822170000,"color":"#2b908f","sliced":true,"selected":true},{"name":"Latino","y":771525888400000,"color":"#eeaaee","sliced":true,"selected":true},{"name":"Jewish","y":91700962050000,"color":"#ff0066","sliced":true,"selected":true},{"name":"Black","y":526264226360000,"color":"#f45b5b","sliced":true,"selected":true},{"name":"Indigenous","y":174285727610000,"color":"#aaeeee","sliced":true,"selected":true},{"name":"Mixed \/ Other","y":148984454560000,"color":"#55BF3B","sliced":true,"selected":true},{"name":"Arab","y":526400066100000,"color":"#DF5353","sliced":true,"selected":true},{"name":"Asian","y":2431392083750000,"color":"#90ee7e","sliced":true,"selected":true},{"name":"Indian","y":572687873900000,"color":"#7798BF","sliced":true,"selected":true}],"prefix":"$"}	NOTE: ZR is the first organization to ever create a global buying power divided by race. Essentially we just took data from CIA.gov FactBook, UN Population Estimates, and The World Bank's Population Estimates / Purchasing Power Parity Per Capita.
World Buying Power Representation	+38.52	+10.29	+6.52		{"name":"World Buying Power","series":[["White",36.48],["Black",6.38],["Mixed \/ Other",1.81]],"cast":[{"name":"White","y":75,"color":"#2b908f"},{"name":"Black","y":16.67,"color":"#f45b5b"},{"name":"Mixed \/ Other","y":8.33,"color":"#55BF3B"}]}
Notes			The "Mixed / Other" categories overlap, and the 2 or more category was not an option until the 2000 Census. So for the combined column, all data will be taken from the "Other" column except for 2000, 2010, & 2020. For those, the average between the "2 or More Races" and "Some Other Race" will be used.

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The Admiral

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