| Title: | Simulation Framework for Sports Physiology and Analytics |
| Version: | 0.3.0 |
| Description: | Provides a rule-based simulation environment for modeling real-world athlete performance, dynamic training sessions, hierarchical variance, and missing telemetry data. |
| License: | MIT + file LICENSE |
| Depends: | R (≥ 4.1.0) |
| Suggests: | dplyr, ggplot2, glmnet, here, knitr, lme4, lmerTest, mice, quarto, ranger, rmarkdown, testthat (≥ 3.0.0) |
| VignetteBuilder: | quarto |
| Encoding: | UTF-8 |
| Config/roxygen2/version: | 8.1.0 |
| NeedsCompilation: | no |
| Packaged: | 2026-09-28 10:43:41 UTC; ma_ab |
| Author: | Mohammad Abbas [aut, cre] |
| Maintainer: | Mohammad Abbas <ma.abbas3107@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2026-09-28 11:00:02 UTC |
Comprehensive Sports Features Dataset (With Missing Values)
Description
Comprehensive Sports Features Dataset (With Missing Values)
Usage
data(sports_features_missing)
Format
A tibble or data frame with 42 variables describing athlete sessions and performance metrics:
- session_id
Unique alphanumeric identifier for each training session.
- athlete_id
Unique alphanumeric identifier for each athlete.
- datetime
Timestamp of when the training session occurred.
- activity_type
Type of exercise performed (e.g., running, cycling, swimming).
- region
Geographical area where the session took place.
- distance_km
Total distance covered during the session in kilometers.
- weather_type
Weather condition during the session (e.g., sunny, rainy, cloudy).
- temperature_c
Ambient outdoor temperature in degrees Celsius.
- personal_status
Pre-activity physical or mental status reported by the athlete.
- is_group_activity
Logical indicator (TRUE/FALSE) if the session was done with a group.
- gender
Categorical gender of the athlete.
- age
Age of the athlete in years.
- base_fitness
Baseline fitness score of the athlete.
- base_speed
Baseline average speed capability of the athlete.
- base_stamina
Baseline stamina level of the athlete.
- base_weight
Baseline body weight of the athlete in kilograms.
- resting_heart_rate
Baseline resting heart rate in beats per minute (bpm).
- device_type
Type of tracking device used during the session.
- speed_kmh
Average speed maintained throughout the session in km/h.
- duration_min
Total duration of the training session in minutes.
- heart_rate_avg
Average heart rate monitored during the session in bpm.
- calories_burned
Estimated total energy expenditure in kilocalories (kcal).
- exhaustion_level
Subjective exhaustion level reported after the session.
- hydration_status
Hydration level (%) recorded during or after the session.
- fatigue_score
Calculated post-activity fatigue accumulation score.
- aerobic_contribution_pct
Estimated percentage contribution of the aerobic energy system to total session workload.
- anaerobic_contribution_pct
Estimated percentage contribution of the anaerobic energy system to total session workload.
- energy_system
Categorical classification of session effort (Aerobic dominant, Mixed, or Anaerobic dominant).
- vo2_session_ml_kg_min
Estimated oxygen consumption rate during the session in mL/kg/min.
- vo2max_est_ml_kg_min
Estimated maximal oxygen uptake potential of the athlete in mL/kg/min.
- vo2_utilisation
Normalises aerobic demand relative to VO2max; quantifies session intensity as a fraction of physiological capacity.
- efficiency_index
Captures cardiovascular economy by relating oxygen uptake to heart rate; used to assess aerobic efficiency and readiness.
- hr_reserve
Represents net cardiovascular elevation above resting state; proxy for internal load and autonomic strain.
- aerobic_efficiency
Indicates aerobic contribution per unit heart rate; evaluates aerobic system utilisation and metabolic economy.
- fatigue_per_km
Normalises fatigue accumulation by distance; models workload-adjusted fatigue dynamics.
- athlete_mean_fatigue
Chronic fatigue baseline; separates stable athlete-level fatigue differences from session-level variation.
- fatigue_deviation
Within-athlete centred fatigue; isolates session-specific deviations from an athlete's personal fatigue norm.
- athlete_mean_distance
Chronic volume baseline; captures habitual training load differences between athletes.
- distance_centered
Within-athlete centred distance; models session-specific deviations from typical training volume.
- pace_min_km
Represents external speed demand; used to model performance intensity and pacing strategy.
- calories_per_km
Normalises metabolic cost by distance; quantifies energetic efficiency and workload economy.
- calories_per_min
Represents metabolic burn rate; models internal metabolic intensity independent of distance.
Details
A variant of the core sports analytics dataset containing structured missingness (NA values) across performance tracking columns to demonstrate imputation workflows.
Source
Synthesized sports features analytics framework.