← All Connections

If You Like KaBlam!(1996)

TV

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

132 connections found

132 connections
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3
170x
91 voters
5
142x
95 voters
7
133x
68 voters
13
116x
103 voters
14
115x
118 voters
17
106x
87 voters
18
105x
66 voters
19
102x
65 voters
21
98x
165 voters
22
97x
103 voters
23
95x
54 voters
24
91x
145 voters
26
89x
135 voters
28
86x
114 voters
29
84x
132 voters
30
84x
55 voters
31
77x
108 voters
33
76x
52 voters
34
69x
53 voters
35
64x
56 voters
36
62x
86 voters
38
59x
145 voters
39
59x
107 voters
41
59x
61 voters
44
57x
75 voters
45
57x
69 voters
46
56x
54 voters
52
51x
59 voters
54
48x
61 voters
55
45x
96 voters
56
44x
82 voters
58
43x
51 voters
59
42x
122 voters
60
42x
68 voters
61
41x
55 voters
62
39x
75 voters
63
39x
101 voters
64
37x
74 voters
66
37x
104 voters
67
37x
102 voters
68
32x
57 voters
69
31x
57 voters
70
29x
50 voters
71
27x
81 voters
72
27x
78 voters
76
22x
61 voters
78
18x
79 voters
80
16x
53 voters
83
13x
78 voters
84
12x
78 voters
85
11x
79 voters
86
10x
133 voters
87
9.3x
60 voters
88
9.0x
53 voters
91
7.8x
64 voters
92
7.1x
86 voters
93
6.8x
114 voters
95
6.3x
55 voters
96
6.2x
76 voters
97
5.9x
99 voters
98
4.7x
78 voters
99
4.4x
86 voters
100
4.2x
56 voters
102
3.2x
59 voters
103
3.0x
50 voters
104
3.0x
56 voters
106
2.0x
76 voters
107
0.1x
7 voters
109
0.1x
6 voters
111
0.0x
5 voters
112
0.0x
4 voters
113
0.0x
4 voters
114
0.0x
3 voters
115
0.0x
8 voters
116
0.0x
4 voters
118
0.0x
3 voters
120
0.0x
3 voters
121
0.0x
9 voters
122
0.0x
8 voters
125
0.0x
5 voters
127
0.0x
4 voters
128
0.0x
4 voters
129
0.0x
3 voters
130
0.0x
3 voters
132
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 KaBlam! consistently tend to also love certain other things. The "strength" score shows how much more likely fans of KaBlam! 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.