SAGAUSDT · recorded history

One-sided tape: sellers on SAGAUSDT

Taker buy ratio over the last 15 minutes has run at 0.38 or less: a persistently seller-heavy tape.

Read it in context

Read SAGAUSDT itself
Inspect SAGAUSDT now or at a past minute
Its recorded moves
SAGAUSDT market events and replays
Test it on SAGAUSDT, then plan it
A tested result leads to Plan a trade, which measures what trading it would have paid after costs.
Edit this test in Workbench

What happened in the next 24 hours?

Both moves were less common than on minutes without it.

Other minutes are the same markets and dates without this condition. Each percentage is the share of measured minutes that reached that move from the starting price.

Price touched +5% or higher

When this held: 48.0% · 132 of 275 minutes
Other minutes: 60.9% · 23,000 of 37,796 minutes

Price touched −10% or lower

When this held: 10.9% · 30 of 275 minutes
Other minutes: 23.6% · 8,935 of 37,796 minutes

Price can touch both levels within the same 24 hours.

This counts how often price touched a level, not what trading it would have paid.

Sample and counting

Rates use the 275 of 285 matches with a full 24 hours after them. The 10 newer ones are left out, not counted as zero.

Every condition is measured over the same 24 hours, whatever the length of its own reading. Other windows and move sizes shows shorter and longer windows.

When it happened

About 9.2 a day, on 30 of 31 days: spread through the record rather than one event.

Other windows and move sizes

Matches that reached each move within each window. Counts first; the measured row is what each rate is over.
Move	1 hour	4 hours	24 hours	72 hours	7 days
Measured	285	283	275	260	241
Too recent	0	2	10	25	44
+0.1% or more	266 (93.3%)	276 (97.5%)	274 (99.6%)	259 (99.6%)	241 (100.0%)
+0.2% or more	246 (86.3%)	265 (93.6%)	268 (97.5%)	259 (99.6%)	241 (100.0%)
+0.5% or more	184 (64.6%)	237 (83.7%)	255 (92.7%)	258 (99.2%)	241 (100.0%)
+1% or more	100 (35.1%)	176 (62.2%)	234 (85.1%)	258 (99.2%)	241 (100.0%)
+2% or more	56 (19.6%)	99 (35.0%)	194 (70.5%)	248 (95.4%)	241 (100.0%)
+5% or more	16 (5.6%)	39 (13.8%)	132 (48.0%)	189 (72.7%)	241 (100.0%)
+10% or more	8 (2.8%)	20 (7.1%)	87 (31.6%)	139 (53.5%)	197 (81.7%)
+15% or more	4 (1.4%)	15 (5.3%)	76 (27.6%)	139 (53.5%)	193 (80.1%)
+20% or more	4 (1.4%)	8 (2.8%)	67 (24.4%)	135 (51.9%)	193 (80.1%)
+30% or more	2 (0.7%)	6 (2.1%)	46 (16.7%)	118 (45.4%)	173 (71.8%)
+50% or more	0 (0.0%)	1 (0.4%)	9 (3.3%)	48 (18.5%)	112 (46.5%)
+100% or more	0 (0.0%)	1 (0.4%)	4 (1.5%)	17 (6.5%)	63 (26.1%)
+200% or more	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	18 (7.5%)
−0.1% or lower	257 (90.2%)	270 (95.4%)	270 (98.2%)	257 (98.8%)	240 (99.6%)
−0.2% or lower	230 (80.7%)	262 (92.6%)	265 (96.4%)	252 (96.9%)	236 (97.9%)
−0.5% or lower	178 (62.5%)	239 (84.5%)	256 (93.1%)	244 (93.8%)	233 (96.7%)
−1% or lower	94 (33.0%)	172 (60.8%)	223 (81.1%)	230 (88.5%)	223 (92.5%)
−2% or lower	38 (13.3%)	95 (33.6%)	175 (63.6%)	197 (75.8%)	203 (84.2%)
−5% or lower	4 (1.4%)	20 (7.1%)	79 (28.7%)	129 (49.6%)	155 (64.3%)
−10% or lower	1 (0.4%)	5 (1.8%)	30 (10.9%)	74 (28.5%)	131 (54.4%)
−15% or lower	0 (0.0%)	2 (0.7%)	8 (2.9%)	52 (20.0%)	80 (33.2%)
−20% or lower	0 (0.0%)	0 (0.0%)	6 (2.2%)	21 (8.1%)	16 (6.6%)
−30% or lower	0 (0.0%)	0 (0.0%)	4 (1.5%)	10 (3.8%)	13 (5.4%)

Each window counts only matches old enough for it, so a longer window can show fewer.

Distributions and daily counts

Upside reached · 24hThe most price moved up within 24 hours of each match: a high-water mark, never a close. 275 with a complete 24 hours.

Drawdown · 24hThe worst price moved against within 24 hours of each match: the deepest point, never the close. 275 with a complete 24 hours.

Price 30 minutes laterForward 30-minute returns across 285 matches: close to an even split, which is what a coin flip looks like. 0 too recent.

How to read a distribution

Matches per UTC day

1 Sep19 matches
2 Sep18 matches
3 Sep15 matches
4 Sep16 matches
5 Sep18 matches
6 Sep16 matches
7 Sep16 matches
8 Sep15 matches
9 Sep16 matches
10 Sep2 matches
11 Sep4 matches
12 Sep13 matches
13 Sep12 matches
14 Sep8 matches
15 Sep5 matches
16 Sep3 matches
17 Sep11 matches
18 Sep9 matches
19 Sep7 matches
20 Sep2 matches
21 Sep6 matches
22 Sep6 matches
23 Sep4 matches
24 Sep4 matches
25 Sep4 matches
26 Sep3 matches
27 Sep8 matches
28 Sep4 matches
29 Sep11 matches
30 Sep10 matches
1 Oct0 matches

How this is counted

Each rate counts only matches with the full window after them.
A minute where a reading was missing is left out and reported, not read as zero.
The condition picks the setup, never the outcome: a definition that filters on what followed is rejected (OUTCOME_IN_PREDICATE). Every match is measured, winners and losers alike.
"Other minutes" is every other eligible minute in the same market and window. It is a reference, not a control group.
"Reached +5%" uses the highest price inside the window (maximum favourable excursion, MFE); "fell to −10%" uses the lowest (maximum adverse excursion, MAE). Neither is the close.
Checked 43,201 eligible market-minutes (eligible_symbol_buckets) on SAGAUSDT, 2026-09-01 00:00 to 2026-10-01 00:00 UTC.

What are MFE and MAE?

Reproducibility key (q#c0577ac6)

The key that re-runs this exact count. Same key, same bytes; when the record grows, the dataset revision changes.

grammar: research_query.v2
normalization: archive_normalization.v1
feature library: feature_defs.v1
dataset revision: c764b05a2cce2a39e38b40d35fcb2488ecc1bfda3dfbabbbd252d4ba3f3a9680
query hash: c0577ac6e776774353c468a8b7daf7721aefd803f230aee30dbdd28198b3df9e
scanned window: 2026-09-01T00:00:00.000Z to 2026-10-01T00:00:00.000Z (UTC)

Re-run over the API

The exact search definition behind this count. Send it to the key-authed research API (or the MCP research tool) and compare 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",
        "lte",
        0.38
      ],
      [
        "identity.symbol",
        "eq",
        "sagausdt"
      ],
      [
        "times.anchor_time",
        "between",
        [
          "2026-09-01T00:00:00.000Z",
          "2026-10-01T00:00:00.000Z"
        ]
      ]
    ]
  },
  "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","lte",0.38],["identity.symbol","eq","sagausdt"],["times.anchor_time","between",["2026-09-01T00:00:00.000Z","2026-10-01T00:00:00.000Z"]]]},"sort":["times.anchor_time","desc"],"page":{"limit":50,"cursor":null}}'

One-sided tape: sellers on SAGAUSDT

Read it in context

Read SAGAUSDT itself

Its recorded moves

Test it on SAGAUSDT, then plan it

What happened in the next 24 hours?

Price touched +5% or higher

Price touched −10% or lower