S

Backtest results

An honest replay of the direction model on past data. For every coin and day in our history, we run the model and check what price actually did 1, 3, or 7 days later— only on days the model hadn't learned from. Pick a coin group and horizon to see where it has real edge and which stress / pulse conditions give the most reliable calls.

All clusters·7-day horizon
Predictions
71,926
All-calls accuracy
57.6%
41,447 / 71,926
Meaningful-only accuracy
57.1%
34,902 / 61,071CI [56.857.5]
Edge over baseline
+0.5pp
baseline 56.7%
Computed
2026-06-14
probabilities calibrated

Meaningful = predictions where the model's probability was at least ±3% away from 50/50 — i.e., the model actually picked a side. The all-calls number includes every prediction, even near-coinflip ones.

Accuracy by Stress band

Each row groups predictions by the pair's stress score on that day. Look for bands where meaningful accuracy is well above 50% — those are the regimes where the model actually has an edge.

Stress bandCallsAll-calls accMeaningful accEdge
0.00-0.252,536(2,208 meaningful)55.3%54.3%+0.5pp
0.25-0.5055,725(47,819 meaningful)57.0%56.8%+0.6pp
0.50-0.7512,055(9,639 meaningful)59.8%58.2%+0.2pp
0.75-1.011,610(1,405 meaningful)66.0%66.5%-0.1pp

Accuracy by Pulse band

Same idea, grouped by the pulse score (how fast positioning, funding and volatility are shifting versus normal). Pulse tends to lead the move — does the model trust fast-moving setups more?

Pulse bandCallsAll-calls accMeaningful accEdge
0.00-0.254,397(3,630 meaningful)59.3%58.3%+0.7pp
0.25-0.5033,127(27,994 meaningful)56.8%56.3%+0.6pp
0.50-0.7530,125(25,723 meaningful)57.8%57.4%+0.4pp
0.75-1.014,277(3,724 meaningful)60.6%60.6%+0.2pp

Stress × Pulse accuracy heatmap

Each cell is the model's hit rate when stress (rows) and pulse (cols) landed in those bands together, with the number of calls (n) underneath. Green = real skill (beat the base rate); gray = the hit rate is just the base rate, not skill. Hover any cell for the baseline and confidence interval.

Pulse →
Stress ↓0.00-0.250.25-0.500.50-0.750.75-1.01
0.00-0.25
57%
n=527
53%
n=1,447
54%
n=234
n=0
0.25-0.50
59%
n=2,809
56%
n=23,146
57%
n=19,686
59%
n=2,178
0.50-0.75
56%
n=278
58%
n=3,091
57%
n=5,006
62%
n=1,264
0.75-1.01
75%
n=16
62%
n=310
68%
n=797
67%
n=282

Cross-sectional model — “will it beat the median coin today?”

Trained on relative strength versus the same-day median of all coins, so the market's overall drift is removed from the label by construction — the baseline is exactly 50%, and anything above it is pure per-coin skill. Honest walk-forward numbers, meaningful calls only.

1-day
54.9%
edge +4.9pp · 22,295 calls · CI [54.255.5]
3-day
54.6%
edge +4.6pp · 21,133 calls · CI [53.955.3]
7-day
55.1%
edge +5.1pp · 15,467 calls · CI [54.355.9]

Breakout model — “will it break ±1.5σ within N days?”

Predicts whether a coin will touch a volatility-scaled barrier (±1.5× its own daily volatility) within the window. Globally it only matches the base rate — so the product shows it only for pairs in the conditions below, where the backtest shows real edge over the event base rate.

1-day · overall
69.2%
base 69.2% · edge -0.0pp
3-day · overall
69.5%
base 68.3% · edge +1.2pp
7-day · overall
89.0%
base 88.9% · edge +0.1pp
#11d · stress 0.75-1.01 · pulse 0.75-1.01acc 72.8% vs base 60.4% · n=323+12.4pp
#21d · stress 0.75-1.01 · pulse 0.50-0.75acc 69.6% vs base 61.7% · n=954+7.9pp
#33d · stress 0.75-1.01 · pulse 0.50-0.75acc 70.1% vs base 63.8% · n=970+6.3pp
#43d · stress 0.75-1.01 · pulse 0.25-0.50acc 60.9% vs base 55.3% · n=371+5.7pp
#51d · stress 0.50-0.75 · pulse 0.75-1.01acc 65.7% vs base 60.7% · n=1,562+5.1pp
#67d · stress 0.75-1.01 · pulse 0.50-0.75acc 80.8% vs base 77.3% · n=902+3.5pp

Predictions that worked — the model's lean matched what price did

Concrete examples where the model called ▲ up and price went up, or called ▼ down and price went down — within the chosen horizon. Ordered by realized move size, so the impressive calls float to the top. Pure 50/50 picks are excluded (|p − 50%| ≥ 3%).

1-day
19,569 meaningful
3-day
33,553 meaningful
7-day
55,972 meaningful
14-day
81,839 meaningful
25-day
68,096 meaningful
total predictions in window correct · wrong
DatePairLeanRealized
2026-04-06RAVEUSDT54%+3143.21%
2026-04-05RAVEUSDT55%+2271.33%
2026-01-24BULLAUSDT59%+938.27%
2026-04-04RAVEUSDT55%+770.81%
2026-04-29LABUSDT53%+580.13%
2026-04-30LABUSDT55%+546.06%
2026-04-03RAVEUSDT54%+526.61%
2026-06-04BEATUSDT55%+487.91%
2026-06-04ESPORTSUSDT57%+451.90%
2026-06-03BEATUSDT58%+434.50%
2026-04-06BLESSUSDT54%+417.38%
2026-01-13FHEUSDT54%+415.23%
2026-04-03SIRENUSDT54%+400.69%
2026-06-05BEATUSDT55%+388.93%
2026-01-12FHEUSDT55%+355.10%
2026-02-19POWERUSDT55%+354.62%
2026-04-27SKYAIUSDT54%+336.94%
2026-06-02VELVETUSDT54%+333.75%
2026-06-02BEATUSDT60%+333.43%
2026-03-28DUSDT55%+299.05%
2026-05-24PORTALUSDT56%+295.01%
2026-01-23BULLAUSDT57%+294.97%
2026-04-28LABUSDT54%+290.68%
2026-06-01BEATUSDT56%+269.12%
2026-05-25LABUSDT55%+265.24%
2026-04-08AKEUSDT55%+259.77%
2026-04-09ORDIUSDT56%+252.02%
2026-04-07BLESSUSDT54%+251.25%
2026-05-26LABUSDT53%+245.96%
2026-06-01VELVETUSDT56%+244.97%
2026-05-27LABUSDT53%+243.59%
2026-01-10FHEUSDT55%+240.39%
2026-04-18BSBUSDT54%+237.20%
2026-01-31SIRENUSDT53%+229.93%
2025-12-30BROCCOLI714USDT55%+221.98%
2026-04-25UBUSDT55%+218.53%
2026-02-05PIPPINUSDT53%+215.36%
2026-04-24BUSDT55%+213.17%
2026-01-22BULLAUSDT56%+211.23%
2026-05-26PORTALUSDT55%+210.49%
2026-05-24ALLOUSDT54%+208.87%
2026-05-14EDENUSDT56%+208.76%
2026-06-05ESPORTSUSDT56%+208.12%
2026-05-15EDENUSDT56%+204.93%
2026-03-27AIOTUSDT56%+201.37%
2026-04-10ORDIUSDT56%+192.54%
2025-12-04FHEUSDT54%+192.12%
2026-04-22AIOTUSDT55%+188.42%
2026-03-19BRUSDT54%+187.75%
2026-04-23AIOTUSDT56%+187.52%
up downLean = trained model's calibrated probability at that sample's date · Realized = what actually happened over the next 7 days. Click a pair name to open its current dashboard.