ESPORTSUSDT · historical base rate

One-sided tape: buyers on ESPORTSUSDT

Taker buy ratio over the last 15 minutes has run at 0.62 or more: a persistently buyer-heavy tape.

What has happened on ESPORTSUSDT when it held

Historically, when One-sided tape: buyers on ESPORTSUSDT held (165 occurrences in the scanned window, 159 with a computable 24h horizon), the market reached +5% within 24h in 79 of 159 (49.7) and drew down 10%+ in 68 of 159 (42.8). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

Outcome distribution

WHAT FOLLOWED - ALL 165 MATCHES, FROM THE PER-SCAN SUMMARY

6 OF 165 (3.6%) REACHED ≥ +5% WITHIN 1H

METRIC MFE_1H · CHIPS RE-READ THE SUMMARY, NEVER RE-QUERY

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 165 = MATCHES WITH A COMPLETE 1H HORIZON

OCCURRENCES PER DAY · UTC · SUM 165 - ALL 165, NOT THE PAGE

About 5.3 a day, on 24 of 31 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 165 PRESENT · 0 ABSENT

Forward 30-minute returns across 165 matches: 61% of them finished down.

Upside reached · 24hThe most price moved up within 24h of each occurrence: a high-water mark, never a close. 159 with a complete 24h.

Drawdown · 24hThe worst price moved against within 24h of each occurrence: the deepest point, never the close. 159 with a complete 24h.

Versus baseline

Historically, when any eligible ESPORTSUSDT minute in the window (baseline) held (40,204 occurrences in the scanned window, 38,767 with a computable 24h horizon), the market reached +5% within 24h in 26,204 of 38,767 (67.6) and drew down 10%+ in 20,452 of 38,767 (52.8). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

The full record

The same setup counted over every recorded day on ESPORTSUSDT (2026-05-15 to 2026-08-01), growing daily.

Historically, when One-sided tape: buyers on ESPORTSUSDT over the full record held (266 occurrences in the scanned window, 260 with a computable 24h horizon), the market reached +5% within 24h in 151 of 260 (58.1) and drew down 10%+ in 107 of 260 (41.2). Maximum favorable (MFE) and maximum adverse (MAE) excursions, both computed forward.

WHAT FOLLOWED - ALL 266 MATCHES, FROM THE PER-SCAN SUMMARY

27 OF 266 (10.2%) REACHED ≥ +5% WITHIN 1H

METRIC MFE_1H · CHIPS RE-READ THE SUMMARY, NEVER RE-QUERY

🔒 COMPUTED FORWARD, NEVER A FILTER · DENOMINATOR 266 = MATCHES WITH A COMPLETE 1H HORIZON

OCCURRENCES PER DAY · UTC · SUM 266 - ALL 266, NOT THE PAGE

About 3.4 a day, on 48 of 79 days: spread through the record rather than one event.

FWD_RET_30M DISTRIBUTION · 265 PRESENT · 1 ABSENT

Forward 30-minute returns across 265 matches: 59% of them finished down.

Reproducibility key (q#2b764998)

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: ce3b6253b51706f7a4c0e4a553e0dd67fcf76395dd1a8717eccda70dad520d60
query hash: 2b764998b773af1359d9f3a30edb751c143fb9c605a1dd0cc7d83a01dcfaabf7
scanned window: 2026-07-02T00:00:00.000Z to 2026-08-01T00:00:00.000Z (UTC)

Same key, same bytes. This receipt reruns; it does not retell. When the record grows, the dataset revision changes and says so.

Re-run this over the API or MCP

This is the exact research_query.v2 definition behind the receipt. Send it to the key-authed research API (or the MCP research tool) and diff the bytes: a cached rerun is free.

{
  "schema_version": "research_query.v2",
  "normalization_version": "archive_normalization.v1",
  "feature_version": "feature_defs.v1",
  "target": "record_occurrences",
  "where": {
    "all": [
      [
        "feature.taker_buy_ratio_15m",
        "gte",
        0.62
      ],
      [
        "identity.symbol",
        "eq",
        "esportsusdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-07-02T00:00:00.000Z",
          "2026-08-01T00:00:00.000Z"
        ]
      ]
    ]
  },
  "sort": [
    "times.anchor_time",
    "desc"
  ],
  "page": {
    "limit": 50,
    "cursor": null
  }
}

curl -s https://app.edgedepth.com/api/v1/research/query \
  -H 'authorization: Bearer $EDGEDEPTH_API_KEY' \
  -H 'content-type: application/json' \
  -d '{"schema_version":"research_query.v2","normalization_version":"archive_normalization.v1","feature_version":"feature_defs.v1","target":"record_occurrences","where":{"all":[["feature.taker_buy_ratio_15m","gte",0.62],["identity.symbol","eq","esportsusdt"],["times.anchor_time","between",["2026-07-02T00:00:00.000Z","2026-08-01T00:00:00.000Z"]]]},"sort":["times.anchor_time","desc"],"page":{"limit":50,"cursor":null}}'

How to read this

Counts ship with denominators: occurrences across the eligible symbol-buckets scanned. A rate is over the occurrences with a computable horizon (present), never the total.
Absent is absent. When a feature was not warm at a minute, that bucket leaves the denominator and is reported; it is never coerced to zero.
This selects a setup, never its outcome. The grammar forbids filtering on what followed (OUTCOME_IN_PREDICATE), so the distribution below is over every occurrence, not a survivorship-picked subset.

Occurrences are observed examples in a selected archive, not a guarantee. Outcomes are computed forward from each anchor and are descriptive, never a filter and never a prediction. Nothing here is trading advice.

Everything measured on ESPORTSUSDT right now: the ESPORTSUSDT research page