综合php项目，中卫组合默契度如何量化？

wen PHP项目 2026-11-14 2

中卫组合默契度量化方案（PHP 项目）

在足球数据分析中，中后卫组合的"默契度"是难以直接测量的隐性指标，下面给出一个可落地的 PHP 量化方案，核心思路是用可观测数据间接刻画默契，并输出 0–100 的默契分。

量化维度设计

默契度不能靠单一指标，建议从 4 个维度加权：

维度	含义	可观测代理指标
协同稳定性	两人同时出场且配合不出错的频率	同场时长占比、共同出场时失球率
空间互补性	覆盖区域是否互补而非重叠	防守热区重叠度、拦截/解围区域分布
行为同步性	防守动作的时序协同	同场时被反击次数、造越位成功率、协防补位次数
结果有效性	组合带来的实际防守产出	同场零封率、对方 xG 抑制、对抗成功率

数据模型（MySQL 表设计）

-- 球员基础
CREATE TABLE players (
  id INT PRIMARY KEY,
  name VARCHAR(50),
  position VARCHAR(10)  -- 'CB'
);
-- 比赛出场记录（每场每球员一条）
CREATE TABLE appearances (
  id INT PRIMARY KEY,
  match_id INT,
  player_id INT,
  minutes INT,
  position VARCHAR(10),
  goals_conceded INT,      -- 该球员在场时丢球
  xg_conceded DECIMAL(5,2),-- 该球员在场时对方 xG
  interceptions INT,
  clearances INT,
  tackles_won INT,
  duels_won INT,
  offside_traps_success INT,
  zone_grid VARCHAR(500)   -- 防守热区网格 JSON，如 {"A1":12,"B2":8}
);
-- 比赛元数据
CREATE TABLE matches (
  id INT PRIMARY KEY,
  team_id INT,
  opponent_id INT,
  match_date DATE,
  goals_conceded_total INT,
  clean_sheet TINYINT
);

核心算法（PHP 实现）

找出"中卫组合"并统计同场数据

function getPairStats(PDO $pdo, int $cbA, int $cbB): array
{
    // 找出两人同时出场（均为中卫且时间重叠）的比赛
    $sql = "
        SELECT a.match_id, m.clean_sheet, m.goals_conceded_total,
               LEAST(a.minutes, b.minutes) AS shared_minutes,
               a.xg_conceded AS xg_a, b.xg_conceded AS xg_b,
               a.interceptions AS int_a, b.interceptions AS int_b,
               a.clearances AS clr_a, b.clearances AS clr_b,
               a.duels_won AS dw_a, b.duels_won AS dw_b,
               a.zone_grid AS zone_a, b.zone_grid AS zone_b,
               a.offside_traps_success AS trap_a,
               b.offside_traps_success AS trap_b
        FROM appearances a
        JOIN appearances b ON a.match_id = b.match_id
        JOIN matches m ON m.id = a.match_id
        WHERE a.player_id = :a AND b.player_id = :b
          AND a.position = 'CB' AND b.position = 'CB'
          AND a.minutes > 0 AND b.minutes > 0
    ";
    $stmt = $pdo->prepare($sql);
    $stmt->execute([':a' => $cbA, ':b' => $cbB]);
    return $stmt->fetchAll(PDO::FETCH_ASSOC);
}

四个子分数计算

function computeScores(array $rows): array
{
    if (count($rows) === 0) {
        return ['stability'=>0,'complement'=>0,'sync'=>0,'outcome'=>0];
    }
    $n = count($rows);
    $sharedTotal = 0; $zeroSheet = 0;
    $goalsPer90 = []; $xgPer90 = [];
    $overlapSum = 0; $trapRate = []; $duelRate = [];
    foreach ($rows as $r) {
        $sharedTotal += $r['shared_minutes'];
        if ($r['clean_sheet']) $zeroSheet++;
        // 结果有效性：每 90 分钟丢球 & 对方 xG
        if ($r['shared_minutes'] > 0) {
            $goalsPer90[] = $r['goals_conceded_total'] * 90 / $r['shared_minutes'];
            $xgPer90[]    = (($r['xg_a'] + $r['xg_b']) / 2) * 90 / $r['shared_minutes'];
        }
        // 空间互补性：热区重叠度（Jaccard 相似度的补值）
        $za = json_decode($r['zone_a'], true) ?: [];
        $zb = json_decode($r['zone_b'], true) ?: [];
        $overlapSum += 1 - jaccard(array_keys($za), array_keys($zb));
        // 行为同步性：造越位成功率（两人合计）
        $trapOps = max(1, $r['trap_a'] + $r['trap_b']);
        $trapRate[] = $r['trap_a'] + $r['trap_b']; 
        // 对抗成功率
        $duelOps = max(1, $r['dw_a'] + $r['dw_b']);
        $duelRate[] = ($r['dw_a'] + $r['dw_b']) / $duelOps;
    }
    // 1) 协同稳定性：同场场次越多 + 零封率越高越稳
    $stability = min(1, $n / 15) * 0.5 + ($zeroSheet / $n) * 0.5;
    // 2) 空间互补性：重叠度越低（互补）越好
    $complement = 1 - ($overlapSum / $n);
    // 3) 行为同步性：造越位 + 对抗，归一化
    $syncRaw = array_sum($trapRate) / $n;                // 平均每场造越位数
    $sync = min(1, $syncRaw / 4) * 0.5
          + (array_sum($duelRate) / $n) * 0.5;
    // 4) 结果有效性：丢球越少、xG 抑制越强越好
    $avgG90 = array_sum($goalsPer90) / $n;
    $avgXg90 = array_sum($xgPer90) / $n;
    $outcome = max(0, 1 - ($avgG90 / 2)) * 0.5
             + max(0, 1 - ($avgXg90 / 2.5)) * 0.5;
    return [
        'stability'  => round($stability, 4),
        'complement' => round($complement, 4),
        'sync'       => round($sync, 4),
        'outcome'    => round($outcome, 4),
    ];
}
function jaccard(array $a, array $b): float
{
    $a = array_unique($a); $b = array_unique($b);
    $inter = count(array_intersect($a, $b));
    $union = count(array_unique(array_merge($a, $b)));
    return $union === 0 ? 0 : $inter / $union;
}

加权汇总为 0–100 默契分

function compatibilityScore(array $s): float
{
    // 权重可调：结果与稳定性优先
    $w = [
        'stability'  => 0.30,
        'complement' => 0.20,
        'sync'       => 0.25,
        'outcome'    => 0.25,
    ];
    $score = 0;
    foreach ($w as $k => $weight) {
        $score += $s[$k] * $weight;
    }
    return round($score * 100, 2);
}

调用示例

$rows  = getPairStats($pdo, 101, 102);   // 两名中卫
$sub   = computeScores($rows);
$final = compatibilityScore($sub);
echo "默契度总分：{$final}\n";
print_r($sub);
// 输出示例：
// 默契度总分：78.4
// ['stability'=>0.80,'complement'=>0.72,'sync'=>0.65,'outcome'=>0.85]