Code Coverage |
||||||||||
Lines |
Functions and Methods |
Classes and Traits |
||||||||
Total | |
0.00% |
0 / 20 |
|
0.00% |
0 / 1 |
CRAP | |
0.00% |
0 / 1 |
BradleyTerry | |
0.00% |
0 / 20 |
|
0.00% |
0 / 1 |
56 | |
0.00% |
0 / 1 |
rating | |
0.00% |
0 / 20 |
|
0.00% |
0 / 1 |
56 |
1 | <?php |
2 | /** |
3 | * Jingga |
4 | * |
5 | * PHP Version 8.1 |
6 | * |
7 | * @package phpOMS\Algorithm\Rating |
8 | * @copyright Dennis Eichhorn |
9 | * @license OMS License 2.0 |
10 | * @version 1.0.0 |
11 | * @link https://jingga.app |
12 | */ |
13 | declare(strict_types=1); |
14 | |
15 | namespace phpOMS\Algorithm\Rating; |
16 | |
17 | /** |
18 | * Calculate rating strength using the Bradley Terry model |
19 | * |
20 | * @package phpOMS\Algorithm\Rating |
21 | * @license OMS License 2.0 |
22 | * @link https://jingga.app |
23 | * @see https://en.wikipedia.org/wiki/Bradley%E2%80%93Terry_model |
24 | * @since 1.0.0 |
25 | */ |
26 | final class BradleyTerry |
27 | { |
28 | /** |
29 | * Rate the strongest to the weakest team based on historic performances (wins/losses) |
30 | * |
31 | * The following example contains match results (matrix) of teams A-D facing each other (each point is a victory). |
32 | * @example rating( |
33 | * [ |
34 | * 'A' => ['A' => 0, 'B' => 2, 'C' => 0, 'D' => 1], |
35 | * 'B' => ['A' => 3, 'B' => 0, 'C' => 5, 'D' => 0], |
36 | * 'C' => ['A' => 0, 'B' => 3, 'C' => 0, 'D' => 1], |
37 | * 'D' => ['A' => 4, 'B' => 0, 'C' => 3, 'D' => 0], |
38 | * ], |
39 | * 10 |
40 | * ) // [0.640, 1.043, 0.660, 2.270] -> D is strongest |
41 | * |
42 | * @param array[] $history Historic results |
43 | * @param int $iterations Iterations for estimation |
44 | * |
45 | * @return float[] Array of "strength" scores (highest = strongest) |
46 | * |
47 | * @since 1.0.0 |
48 | */ |
49 | public function rating(array $history, int $iterations = 20) : array |
50 | { |
51 | $keys = \array_keys($history); |
52 | $pOld = []; |
53 | foreach ($keys as $key) { |
54 | $pOld[$key] = 1; |
55 | } |
56 | |
57 | $p = $pOld; |
58 | for ($i = 0; $i < $iterations; ++$i) { |
59 | foreach ($history as $idx => $row) { |
60 | $W = \array_sum($row); |
61 | |
62 | $d = 0; |
63 | foreach ($history as $idx2 => $_) { |
64 | if ($idx === $idx2) { |
65 | continue; |
66 | } |
67 | |
68 | $d += ($history[$idx][$idx2] + $history[$idx2][$idx]) |
69 | / ($pOld[$idx] + $pOld[$idx2]); |
70 | } |
71 | |
72 | $p[$idx] = $W / $d; |
73 | } |
74 | |
75 | $norm = \array_sum($p); |
76 | foreach ($p as $idx => $_) { |
77 | $p[$idx] /= $norm; |
78 | } |
79 | |
80 | $pOld = $p; |
81 | } |
82 | |
83 | return $p; |
84 | } |
85 | } |