/**
 * Correlation engine.
 *
 * Pearson correlation between two stat streams. Caller feeds in pairs of
 * arrays (same player or same team) and we return the coefficient plus
 * the implied SGP adjustment for value flagging.
 */

function pearson(xs, ys) {
  if (!Array.isArray(xs) || !Array.isArray(ys) || xs.length !== ys.length || xs.length < 3) return null;
  let sx = 0, sy = 0;
  for (let i = 0; i < xs.length; i++) { sx += xs[i]; sy += ys[i]; }
  const mx = sx / xs.length, my = sy / ys.length;
  let num = 0, dx = 0, dy = 0;
  for (let i = 0; i < xs.length; i++) {
    const a = xs[i] - mx;
    const b = ys[i] - my;
    num += a * b; dx += a * a; dy += b * b;
  }
  const den = Math.sqrt(dx * dy);
  if (den === 0) return 0;
  return num / den;
}

/**
 * Compare measured correlation to the book's implicit SGP adjustment.
 * `bookAdjustment` is the multiplier the book applies to the joint price
 * vs the independent-events price. >1 means the book over-prices the
 * correlation; <1 means under-priced (VALUE).
 */
function flagValue(measuredR, bookAdjustment) {
  if (measuredR == null || bookAdjustment == null) return null;
  if (bookAdjustment < 1 && measuredR > 0.15) return 'VALUE';
  if (bookAdjustment > 1.2 && measuredR < 0.1) return 'OVERPRICED';
  return null;
}

module.exports = { pearson, flagValue };