PAIesque vs Paintball Notificator
Side-by-side comparison of two open source alternatives
PAIesque
PAIesque helps athletes and fitness enthusiasts monitor their training through a simple three-step logic: 1. Measure training impulse (TRIMP) — The faster and longer your heart beats, the higher your daily score. 2. Analyze patterns over time — Track how your TRIMP accumulates and distributes 3. Monitor your body's response — Compare how your body reacts to training load PAIesque is different from commercial fitness apps (e.g. Garmin, Whoop, Polar). Every metric comes from published, peer-reviewed research with transparent methods that can be calculated from heart rate data alone. The app only includes metrics we can verify and reproduce from first principles — no proprietary black boxes, no undisclosed algorithms. And, all your data stays on your device. 1. TRIMP: • Banister TRIMP — The original exponential model with sex-specific coefficients (a=0.64/0.86, b=1.92/1.67) [Banister, 1991; Morton et al., 1990] • iTRIMP — Individualized TRIMP with customizable b coefficient (1.5-4.0) [Stagno et al., 2007; Akubat et al., 2012] • LT-TRIMP — Lactate Threshold-based model with β coefficient (0.04-0.11) and smooth transition at LT [Cheng et al., 1992; Mader et al., 1976; Gaesser and Poole, 1986] • PAI-esque — PAI-inspired metric using EWMA (not the official commercial algorithm) [Nes et al., 2017; Kieffer et al., 2021] 2. Patterns over time: • Intensity zones — Time and TRIMP spent in low/moderate/high zones (polarized training model) [Seiler and Tønnessen, 2009; Stöggl and Sperlich, 2014] • EWMA — Exponentially Weighted Moving Average for rolling loads (more sensitive than simple averages) • ACWR — Acute:Chronic Workload Ratio for injury risk monitoring (0.8-1.3 = sweet spot) [Murray et al., 2017; Griffin et al., 2021; Gabbett, 2016] • Polarized Training Score — 0-100 measure of how closely your distribution matches your targets 3. Body's response: • Resting Heart Rate (RHR) — Calculated from your defined sleep window (adaptive percentile: 5th-15th) • Heart Rate Variability (HRV) — Daily RMSSD averages during sleep [Task Force, 1996; Plews et al., 2013; Buchheit, 2014] • EWMA trends — Exponentially weighted moving averages for both RHR and HRV (acute and chronic windows) • Combined interpretation — RHR ↓ + HRV ↑ = positive adaptation; RHR ↑ + HRV ↓ = possible fatigue Data Management: • CSV export/import • Complete backup/restore (db) • All data stays on your device — no accounts, no cloud uploads, no tracking Creative Use Cases: • Coach analyzing athletes — Import athlete exports, analyze charts, provide feedback • Research analysis — Export CSV files for custom analysis in R, Python, or spreadsheets • Switch between athletes — Use "Delete All Data" + CSV import to analyze multiple individuals Requirements: • Google Health Connect installed on your device • Heart rate (and HRV) data in Health Connect from your wearable device (Gadgetbridge, Garmin, Polar, Samsung, etc.) • Android 8.0 (API 26) or higher Note on PAI: Our PAI-esque implementation is NOT the official commercial PAI® algorithm (which is proprietary). It uses EWMA and scaled TRIMP values to provide a similar intensity-weighted weekly score. The 100 PAI target remains the evidence-based health outcome from the HUNT Study research.
Paintball Notificator
Simple app to let you know when all teams are ready.
| Feature | PAIesque | Paintball Notificator |
|---|---|---|
| License | MIT | GPL-3.0-only |
| Install sources | F-Droid | F-DroidGitHub |
| Categories | ProductivityFitnessMessaging | ProductivityFitnessMessaging |
| Features | Ad-FreeOpen SourceNo Tracking | Ad-FreeOpen SourceNo Tracking |
| Platforms | Android | Android |
| Website | ||
| Source code |