alexei.dolgolyov
68f3229c35
- Add SuspensionFreezeDetector via the IAnomalyDetector seam: a suspension gap with the favourite unchanged and a negligible (< threshold) price move — the mirror of the flip. Score = how completely the line froze. Reuses MatchWinEvidence so UI + evaluator handle it unchanged. 6 tests. - Add AnomalyKind.SuspensionFreeze + localized card/detail label, SuspensionFreezeThreshold option, and fan it into DetectAnomaliesUseCase.
108 lines
4.6 KiB
C#
108 lines
4.6 KiB
C#
using Marathon.Domain.Entities;
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using Marathon.Domain.Enums;
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using Marathon.Domain.ValueObjects;
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namespace Marathon.Domain.AnomalyDetection;
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/// <summary>
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/// Detects a "suspension freeze": the market was suspended (a gap larger than
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/// <c>suspensionGapSeconds</c> between adjacent live snapshots) but resumed with
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/// essentially the same line — the favourite is unchanged and the largest normalised
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/// implied-probability move is below <c>freezeThreshold</c>.
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/// </summary>
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/// <remarks>
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/// <para>
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/// This is the mirror image of <see cref="AnomalyDetector"/> (SuspensionFlip): the flip
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/// fires on a large favourite-changing move across a suspension; the freeze fires when
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/// the bookmaker paused but did <i>not</i> move — a tell that they were uncertain or
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/// gathering information rather than repricing.
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/// </para>
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/// <para>
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/// Score = how completely the line froze: <c>1 − (maxMove / freezeThreshold)</c>, so a
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/// perfectly unchanged line scores ~1.0 and one near the threshold scores near 0. The
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/// shared <see cref="MatchWinEvidence"/> shape (pre ≈ post) conveys the freeze directly,
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/// and the outcome evaluator grades the unchanged favourite like any other anomaly.
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/// </para>
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/// </remarks>
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public sealed class SuspensionFreezeDetector : IAnomalyDetector
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{
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private readonly int _suspensionGapSeconds;
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private readonly decimal _freezeThreshold;
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private readonly int _minSnapshotCount;
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/// <param name="suspensionGapSeconds">Minimum adjacent-snapshot gap (seconds) classed as a suspension.</param>
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/// <param name="freezeThreshold">Maximum normalised probability move to count as frozen; in (0, 1).</param>
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/// <param name="minSnapshotCount">Minimum live snapshots before detection runs (>= 2).</param>
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public SuspensionFreezeDetector(int suspensionGapSeconds, decimal freezeThreshold, int minSnapshotCount)
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{
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if (suspensionGapSeconds <= 0)
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throw new ArgumentOutOfRangeException(nameof(suspensionGapSeconds), suspensionGapSeconds, "Must be positive.");
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if (freezeThreshold is <= 0m or >= 1m)
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throw new ArgumentOutOfRangeException(nameof(freezeThreshold), freezeThreshold, "Must be in (0, 1).");
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if (minSnapshotCount < 2)
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throw new ArgumentOutOfRangeException(nameof(minSnapshotCount), minSnapshotCount, "Must be at least 2.");
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_suspensionGapSeconds = suspensionGapSeconds;
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_freezeThreshold = freezeThreshold;
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_minSnapshotCount = minSnapshotCount;
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}
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/// <inheritdoc />
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public IReadOnlyList<Anomaly> Detect(EventId eventId, IReadOnlyList<OddsSnapshot> snapshots)
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{
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ArgumentNullException.ThrowIfNull(eventId);
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ArgumentNullException.ThrowIfNull(snapshots);
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var live = snapshots
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.Where(s => s.Source == OddsSource.Live)
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.OrderBy(s => s.CapturedAt)
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.ToList();
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if (live.Count < _minSnapshotCount)
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return Array.Empty<Anomaly>();
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var suspensionGap = TimeSpan.FromSeconds(_suspensionGapSeconds);
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var anomalies = new List<Anomaly>();
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for (int i = 0; i < live.Count - 1; i++)
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{
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var pre = live[i];
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var post = live[i + 1];
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if (post.CapturedAt - pre.CapturedAt <= suspensionGap)
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continue;
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var preProbs = MatchWinEvidence.Extract(pre);
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var postProbs = MatchWinEvidence.Extract(post);
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if (preProbs is null || postProbs is null)
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continue;
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decimal maxMove = Math.Max(
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Math.Abs(postProbs.P1 - preProbs.P1),
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Math.Abs(postProbs.P2 - preProbs.P2));
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if (preProbs.PDraw.HasValue && postProbs.PDraw.HasValue)
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maxMove = Math.Max(maxMove, Math.Abs(postProbs.PDraw.Value - preProbs.PDraw.Value));
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var favouriteUnchanged =
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MatchWinEvidence.Favourite(preProbs) == MatchWinEvidence.Favourite(postProbs);
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// Strictly below the threshold so the score stays in (0, 1].
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if (!favouriteUnchanged || maxMove >= _freezeThreshold)
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continue;
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var score = 1m - (maxMove / _freezeThreshold);
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var gapSeconds = (int)(post.CapturedAt - pre.CapturedAt).TotalSeconds;
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var evidenceJson = MatchWinEvidence.BuildJson(gapSeconds, pre, preProbs, post, postProbs);
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anomalies.Add(new Anomaly(
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Id: Guid.NewGuid(),
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EventId: eventId,
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DetectedAt: MoscowTime.Now,
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Kind: AnomalyKind.SuspensionFreeze,
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Score: score,
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EvidenceJson: evidenceJson));
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}
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return anomalies.AsReadOnly();
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}
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}
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