datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
football-charts-results-goal-timing
Football Charts — Match Results and Goal Timing
Football Charts publishes results, fixtures, league tables and the minute of
every goal for 93 leagues in 42 countries, including the lower divisions and
women's competitions most sources skip. Free JSON API and MCP server; the
results and goal-timing dataset is CC BY 4.0 with a DOI
(10.5281/zenodo.22295583).
Most public football datasets cover the big five European leagues and stop at
the final score. This one reaches Serie C, 3.… See the full description on the dataset page: https://huggingface.co/datasets/Damir81/football-charts-results-goal-timing.goat
🐐 GOAT
Generalized Occupational Aptitude Test (GOAT) is a dataset based on questions from Russian government exams that is required for every person graduated from school.
Currently, the dataset cover questions from Literature, Sociology and Russian language subjects.
All questions are divided by expected output format:
Single choice. In such tasks, there is a set of possible answers from which you need to choose the right one. The answer to such tasks is one digit, which is the… See the full description on the dataset page: https://huggingface.co/datasets/deepvk/goat.PORturkish-plu-goal-inferenceHomepage: https://github.com/GGLAB-KU/turkish-plu
premier-league-first-goal-impact-2025-26
What Is the First Goal Worth? — 2025/26 Premier League
Match-level data behind a 5DollarFootballAPI study of how the first confirmed goal changed
Bet365's normalized in-play win probabilities during the 2025/26 Premier League season.
Across 347 usable matches, the median within-match increase in the scoring team's normalized
win probability was 23.1 percentage points (bootstrap 95% CI: 22.4–24.2). The median
first goal after minute 75 moved the probability by 62.2 points… See the full description on the dataset page: https://huggingface.co/datasets/5dollarfootballapi/premier-league-first-goal-impact-2025-26.goal-contribution-efficiency-top-5-leagues
⚽ Football Player Performance Analysis (2019-2020)
📋 Project Overview
This project explores player performance data across the Top 5 European Leagues (England, France, Germany, Italy, and Spain) during the 2019-2020 season. Using a dataset of 2,661 players and 22 columns, we analyze the relationship between actual scoring output and expected metrics.
❓ Research Question
"Do top-tier goal contributors consistently exceed their expected metrics (xG and xA), or… See the full description on the dataset page: https://huggingface.co/datasets/rotemknat/goal-contribution-efficiency-top-5-leagues.epl-inplay-quad-pre-goal-collapse-window-v0.1EPL In-Play Quad Pre-Goal Collapse Window v0.1
What this dataset is
You test whether a model can detect an in-play collapse window before a goal.
Each row represents a live match-state snapshot.
The label asks
Will a goal occur in the next 120 seconds
Core quad coupling
Press intensityDefensive line heightTurnover zonexG per possession
Why this matters
Most football models explain goals after the fact.
This dataset tests pre-goal instability detection.
Intended use
You feed a row.
You output a… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/epl-inplay-quad-pre-goal-collapse-window-v0.1.complete-goal-35f45b
complete-goal-35f45b
Synthetic products test data: 51 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/yuiyamada/complete-goal-35f45b.cristiano-ronaldo-all-club-goals-stats
Context
This dataset contains all the stats of all club goals of Cristiano Ronaldo dos Santos Aveiro.
About Cristiano Ronaldo
Cristiano Ronaldo dos Santos Aveiro is a Portuguese professional footballer who plays as a forward for Premier League club Manchester United and captains the Portugal national team.
Current team: Portugal national football team (#7 / Forward) Trending
Born: February 5, 1985 (age 37 years), Hospital Dr. Nélio Mendonça, Funchal, Portugal
Height:… See the full description on the dataset page: https://huggingface.co/datasets/azminetoushikwasi/cristiano-ronaldo-all-club-goals-stats.goatai-tool-selection-goal-coherence-risk-v0.1What this repo is for
Detect when an AI system selects the wrong tool.
Core failure modes:
uses tools when not needed
avoids tools when needed
picks a tool that cannot solve the task
picks a tool that increases risk
This matters most for agentic systems.
ai-goal-drift-long-horizon-coherence-risk-v0.1What this repo is for
Detect when systems slowly drift away from original goals across long task chains.
Focus:
long-horizon agent behavior
proxy goal takeover
step-by-step objective mutation
hidden optimization drift
This dataset targets one of the hardest alignment failures: gradual goal shift over time.
counterfactual-goal-value-stability-v0.1
What this dataset tests
Whether goals and values remain stableunder counterfactual pressure.
Plans may change.
Priorities must not silently invert.
Why this exists
Counterfactual reasoning often triggers:
goal substitution
safety downgrades
consent bypass
policy flips
This dataset detects those drifts.
Data format
Each example includes:
base goal
base values
counterfactual condition
proposed plan
implied tradeoffs
The task is to label… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/counterfactual-goal-value-stability-v0.1.ai-goal-misgeneralization-drift-detection-v0.1What this dataset is
Detects early goal drift when an agent leaves its training setting
Names the drift type, how strong it is, and what to do next
Inputs
setting
env_shift_event
training_objective
deployment_task
internal_goal_signal_t0
internal_goal_signal_t1
behavior_t0
behavior_t1
Required output
Return JSON only
drift_type_labelOne… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-goal-misgeneralization-drift-detection-v0.1.RealMadrid_Goals_Prediction
Real Madrid Goals Prediction
This dataset contains statistics of Real Madrid Matches, It helps you predict the number of goals that Real Madrid scores in the next Matchs
Overview
Rows: 41 (match records)
Columns / Features:
Date – Date of the match
Home – 1 if Real Madrid played at home, 0 if away
Opponent – Opponent team
RM_Form_Last5 - Real Madrid's Form in the last 5 matches
RM_AvgGoals_Last5 – Average goals scored by Real Madrid in the last 5 matches… See the full description on the dataset page: https://huggingface.co/datasets/shapdl/RealMadrid_Goals_Prediction.goatdata-testclinical_goal_substitution_detector_v0.1Clinical Goal Substitution Detector
Detect when a clinical goal is replaced by a secondary convenience goal.
Output JSON
substitution
sub_type
correct_action
Runpython scorer.py --predictions predictions.jsonl --test_csv data/test.csv
ai-temporal-5node-pressure-buf-lag-cpl-alignment-goal-drift-v0.1
What this repo does
This dataset tests whether a model can detect an alignment cascade forming over time by reading a short ordered window of signals and predicting whether goal drift lock-in occurs by the final step.
Core quad
pressurebufferlagcoupling
Prediction target
label_cascade_state
Row structure
One row represents one short time window (t0 to t3) for an AI system under alignment pressure. It includes time-series values for optimization… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-temporal-5node-pressure-buf-lag-cpl-alignment-goal-drift-v0.1.robotics-goal-persistence-under-disturbance-v0.1What this dataset tests
Goal remains stable when the world shifts
Replanning happens instead of goal drift
Safety interrupts persistence when needed
Why this exists
Robots often fail under disturbance
they abandon goals
they substitute easier goals
they keep pushing unsafely
This set labels those outcomes
Data format
primary_goal
disturbance_event
chosen_action_after
rationale_after
Task
Emit one persistence label
Give one short reason
Disturbance pressures… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/robotics-goal-persistence-under-disturbance-v0.1.turkish-plu-goal-inference
Data
Find the train, validation, and test splits for the goal inference task.
Goal inference data follows the format of the SWAG dataset, as can be seen in the example below:
video-id,fold-ind,startphrase,sent1,sent2,gold-source,ending0,ending1,ending2,ending3,label
xxx,259773,xxx,xxx,Modemi koyacağın yere karar ver.,xxx,Modem Kurmak,Anten Ayarlamak,VPN Kurmak,VPN Kullanmak,0
GoalPrefBench
GoalPref-Bench: Goal-Preference Alignment Benchmark
GoalPref-Bench evaluates how AI systems handle conflicts between users' long-term goals and immediate preferences. The benchmark tests whether models prioritize helping users achieve their stated objectives or instead accommodate conflicting preferences that undermine those goals.
Overview
This benchmark addresses a core question in AI alignment — when a user's immediate preference conflicts with their long-term goal… See the full description on the dataset page: https://huggingface.co/datasets/neurips26-sycophancy/GoalPrefBench.goal_substitution_detector_v01Goal Substitution Detector v0.1
This is an evaluation dataset that detects when a model silently replaces a user’s stated goal with a simpler, easier, or more convenient one.
It targets a common failure mode in agentic and planning systems where outputs remain plausible but no longer serve the original user intent.
This is not training data.
What it tests
Goal preservation across multiple steps
Resistance to convenience and effort pressure
Explicit handling of proposed goal changes
Detection… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/goal_substitution_detector_v01.ai-environment-goal-coherence-baseline-mapping-v0.1What this dataset is
Benchmarks whether an agent keeps the same goal when the environment shifts
Establishes a baseline coherence manifold before drift detection work
Input fields
env_features
training_objective
deployment_context
internal_goal_signal
policy_behavior_summary
Required model output format
Return JSON with these fields
baseline_coherence_score0 to 1higher means the goal signal and behavior still match the objective
goal_representation_stability0 to 1higher means the… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-environment-goal-coherence-baseline-mapping-v0.1.goat_standardizedfitness-goal-datasetai-goal-failure-horizon-and-realignment-routing-v0.1What this dataset is
Predicts how soon goal drift becomes a hard failure
Names the realignment window before collapse
Forces an intervention choice with triggers and monitoring
Inputs
setting
env_shift_event
observed_drift_markers
goal_representation_summary
behavioral_deviation_summary
system_constraints
intervention_options
Gold fields in the CSV
failure_mode
estimated_failure_horizon_steps
realignment_window_steps
gold_intervention_choice
realignment_trigger_conditions… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-goal-failure-horizon-and-realignment-routing-v0.1.SMART-Goals-Validation
Dataset Description
Synthitic dataset generated using Google AI Studio.
for training LLMs for specific data and following the same pattern.
splits into ( SMART-Goal-Examples --> 2013, TaskList-Examples --> 2500)
ricknmortyUniversity_athletic_performance_and_goal_orientation_dataset_2021-2024