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If You Like Power(2014)

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Based on real preference data from thousands of voters, here's what fans of Power also love. Use these connections to discover your next favorite.

44 connections found

Other versions:Power 2014 2017 Powerman 5000 2015 2017 2022 Powerwolf

44 connections

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1

Power Book IV: Force(2022)

215x

50 voters

2

80x

68 voters

3

Queen of the South(2016)

61x

64 voters

4

47x

96 voters

5

45x

51 voters

6

Animal Kingdom(2016)

42x

53 voters

7

Ray Donovan(2013)

24x

79 voters

8

20x

78 voters

9

14x

53 voters

10

11x

66 voters

11

Sons of Anarchy(2008)

9.5x

103 voters

12

9.0x

111 voters

13

The Blacklist(2013)

8.3x

97 voters

14

Boardwalk Empire(2010)

6.9x

51 voters

15

Peaky Blinders(2014)

6.6x

75 voters

16

How to Get Away with Murder(2014)

6.6x

71 voters

17

6.5x

86 voters

18

6.3x

83 voters

19

5.6x

107 voters

20

The Sopranos(2000)

5.4x

51 voters

21

5.3x

72 voters

22

Prison Break(2005)

5.3x

98 voters

23

Person of Interest(2011)

5.3x

55 voters

24

Shameless(2011)

4.7x

72 voters

25

White Collar(2009)

4.7x

66 voters

26

3.7x

57 voters

27

Orange Is the New Black(2013)

3.2x

69 voters

28

Better Call Saul(2015)

3.1x

75 voters

29

Mr. Robot(2015)

2.9x

66 voters

30

House of Cards(2013)

2.9x

69 voters

31

2.9x

96 voters

32

Grey's Anatomy(2005)

2.9x

50 voters

33

True Detective(2014)

2.7x

61 voters

34

Breaking Bad(2008)

2.3x

152 voters

35

2.2x

52 voters

36

Westworld(2016)

2.1x

50 voters

37

The Walking Dead(2010)

1.8x

60 voters

38

Game of Thrones(2011)

1.7x

131 voters

39

Stranger Things(2016)

1.6x

70 voters

40

All in the Family(1971)

0.0x

3 voters

41

Wolfblood(2012)

0.0x

4 voters

42

0.0x

4 voters

43

0.0x

4 voters

44

16 and Pregnant(2009)

0.0x

3 voters

How 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 Power consistently tend to also love certain other things. The "strength" score shows how much more likely fans of Power 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.

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