datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
epl-inplay-quad-fatigue-sub-error-collapse-v0.1EPL In-Play Quad Fatigue Substitution Error Collapse v0.1
What this dataset is
You test whether a model can detect late-game defensive collapse.
Each row represents a defending team state in minute 65 to 95.
Core quad coupling
Sprint intensityMinutes since last substitutionDefensive duel successError rate
The label asks
Will this team concede a goal in the next 120 seconds
Why this matters
Late goals decide matches.
Defensive collapse is usually a coupling failure between fatigue and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/epl-inplay-quad-fatigue-sub-error-collapse-v0.1.football-latent-cross-coupling-pressing-fatigue-breakdown-v0.1
What this repo does
This dataset detects hidden instability in high-press football systems before visible breakdown occurs.
It identifies when pressing intensity and fatigue are interacting in a way that will lead to structural collapse.
Core structure
This dataset models:
latent instability under sustained pressing
fatigue accumulation
transition exposure
cross-coupled breakdown risk
Prediction target
Binary:
1 → pressing system likely to break down due to… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/football-latent-cross-coupling-pressing-fatigue-breakdown-v0.1.nba-player-load-fatigue-coherence-risk-v0.1What this repo is for
Detect fatigue risk before late-game drop.
Focus
travel and schedule density
rest days and back-to-backs
minutes trend
intensity bursts
late game efficiency
soreness markers
Why it matters
Fatigue shows up late.
Dense schedule plus rising minutes is the warning.
clinical-quad-epro-compliance-diary-fatigue-backfill-endpoint-reliability-loss-v0.1Clinical Quad ePRO Compliance Diary Fatigue Backfill Endpoint Reliability Loss v0.1
Each row is a site monthly snapshot.
Core quad
ePRO complianceDiary fatigueBackfill entriesEndpoint reliability loss
Target
label_primary_fail_next_90d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
This dataset identifies a measurable coupling pattern associated with systemic instability.
The sample demonstrates… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-epro-compliance-diary-fatigue-backfill-endpoint-reliability-loss-v0.1.smart-material-coherence-drift-functional-fatigue-detection-v0.1Goal
Detect when a smart material starts losing function.
Core idea
Smart materials fail when stimulus and response stop coupling.
This dataset tests whether a model can detect that drift early.
Domains
shape memory alloys
self-healing polymers
electrochromic materials
Inputs
Healthy baseline signals plus evolving drift signals.
Required outputs
coherence_drift_rate
fatigue_onset_cycle
decoherence_type
functional_variance_growth
failure_probability
recommended_monitoring_action
Decoherence… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/smart-material-coherence-drift-functional-fatigue-detection-v0.1.