SAGAUSDT · recorded history

One-sided tape: buyers on SAGAUSDT

Taker buy ratio over the last 15 minutes has run at 0.62 or more: a persistently buyer-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: 43.2% · 111 of 257 minutes
Other minutes: 60.8% · 23,202 of 38,187 minutes

Price touched −10% or lower

When this held: 12.1% · 31 of 257 minutes
Other minutes: 23.6% · 9,005 of 38,187 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 257 of 264 matches with a full 24 hours after them. The 7 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 8.5 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	263	262	257	249	235
Too recent	1	2	7	15	29
+0.1% or more	231 (87.8%)	255 (97.3%)	255 (99.2%)	249 (100.0%)	235 (100.0%)
+0.2% or more	208 (79.1%)	244 (93.1%)	252 (98.1%)	249 (100.0%)	235 (100.0%)
+0.5% or more	153 (58.2%)	205 (78.2%)	239 (93.0%)	249 (100.0%)	235 (100.0%)
+1% or more	89 (33.8%)	153 (58.4%)	220 (85.6%)	248 (99.6%)	235 (100.0%)
+2% or more	31 (11.8%)	97 (37.0%)	184 (71.6%)	240 (96.4%)	235 (100.0%)
+5% or more	7 (2.7%)	32 (12.2%)	111 (43.2%)	178 (71.5%)	235 (100.0%)
+10% or more	4 (1.5%)	12 (4.6%)	71 (27.6%)	128 (51.4%)	195 (83.0%)
+15% or more	2 (0.8%)	9 (3.4%)	62 (24.1%)	127 (51.0%)	192 (81.7%)
+20% or more	2 (0.8%)	5 (1.9%)	58 (22.6%)	127 (51.0%)	192 (81.7%)
+30% or more	2 (0.8%)	5 (1.9%)	37 (14.4%)	109 (43.8%)	171 (72.8%)
+50% or more	1 (0.4%)	2 (0.8%)	7 (2.7%)	36 (14.5%)	109 (46.4%)
+100% or more	0 (0.0%)	1 (0.4%)	2 (0.8%)	8 (3.2%)	50 (21.3%)
+200% or more	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	17 (7.2%)
−0.1% or lower	242 (92.0%)	253 (96.6%)	254 (98.8%)	248 (99.6%)	235 (100.0%)
−0.2% or lower	220 (83.7%)	245 (93.5%)	251 (97.7%)	245 (98.4%)	234 (99.6%)
−0.5% or lower	152 (57.8%)	205 (78.2%)	228 (88.7%)	228 (91.6%)	223 (94.9%)
−1% or lower	88 (33.5%)	161 (61.5%)	208 (80.9%)	213 (85.5%)	212 (90.2%)
−2% or lower	36 (13.7%)	94 (35.9%)	170 (66.1%)	191 (76.7%)	195 (83.0%)
−5% or lower	7 (2.7%)	23 (8.8%)	73 (28.4%)	113 (45.4%)	144 (61.3%)
−10% or lower	1 (0.4%)	4 (1.5%)	31 (12.1%)	66 (26.5%)	127 (54.0%)
−15% or lower	0 (0.0%)	0 (0.0%)	9 (3.5%)	42 (16.9%)	71 (30.2%)
−20% or lower	0 (0.0%)	0 (0.0%)	8 (3.1%)	14 (5.6%)	7 (3.0%)
−30% or lower	0 (0.0%)	0 (0.0%)	3 (1.2%)	7 (2.8%)	6 (2.6%)
−50% or lower	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	1 (0.4%)

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. 257 with a complete 24 hours.

Drawdown · 24hThe worst price moved against within 24 hours of each match: the deepest point, never the close. 257 with a complete 24 hours.

Price 30 minutes laterForward 30-minute returns across 261 matches: close to an even split, which is what a coin flip looks like. 3 too recent.

How to read a distribution

Matches per UTC day

1 Sep16 matches
2 Sep16 matches
3 Sep16 matches
4 Sep16 matches
5 Sep17 matches
6 Sep18 matches
7 Sep16 matches
8 Sep16 matches
9 Sep18 matches
10 Sep8 matches
11 Sep7 matches
12 Sep13 matches
13 Sep10 matches
14 Sep11 matches
15 Sep4 matches
16 Sep2 matches
17 Sep8 matches
18 Sep7 matches
19 Sep8 matches
20 Sep1 match
21 Sep1 match
22 Sep3 matches
23 Sep3 matches
24 Sep3 matches
25 Sep1 match
26 Sep4 matches
27 Sep6 matches
28 Sep2 matches
29 Sep6 matches
30 Sep7 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#3782ccf9)

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: 3782ccf932e5af2e4fcf3b2ddef4327c837c6f21cdf5e21e4516d10e689d9880
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",
        "gte",
        0.62
      ],
      [
        "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","gte",0.62],["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: buyers 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