The Science

Evidence Medium — The curve shape and per-muscle recovery windows are well studied; several dose magnitudes are practitioner estimates.

Tracks recovery muscle by muscle on a non-linear (exponential) curve, so each session trains what's fresh and spares what's still repairing — heavier, higher-RIR, and eccentric work all extend the window.

Honest note. The curve shape and per-muscle recovery windows come from this literature; a few secondary-mover credits and the running→set-equivalent doses are practitioner estimates, labeled low-confidence in the calibration notes. A separate low-confidence assumption sets how much of a run's dose lands immediately — its freshness-at-t=0 amplitude: no source calibrates that against our freshness scale, so it stays a monotonic heuristic pending your own recovery data.

Evidence Low — The check-in instrument is validated; how much a low score should trim volume and load is mostly practitioner heuristic.

A 30-second daily check-in — sleep, energy, soreness, time — sets a readiness score that adjusts the day's volume, load and RIR out loud, rather than silently under- or over-reaching.

Honest note. The instrument itself — subjective wellness over objective monitoring, and the choice to autoregulate out loud — is directly evidence-based and validated. The deload dose-response on top of it (how much a lower score trims volume, load and RIR) is a practitioner heuristic, not a calibrated dose-response: our own backing review rates those magnitudes Medium down to Low, and the load-factor mapping is its single largest evidence gap. The per-user baselining that would keep a chronically harsh or lenient self-scorer honest — the report's main anti-gaming safeguard — is not yet built.

Evidence Medium — Gain rates trace to real longitudinal datasets; the calibration wrapped around them is lower-confidence.

When you set a target lift and a date, it charts an honest trajectory from evidence-based weekly gain rates by training age and lift — easing off when you're ahead, adding work when you're behind, and refusing to promise a number that isn't reachable in the time.

Honest note. The expected rates of gain come from these datasets. The limits that keep a projection realistic, and the adjustments for lifts the datasets do not measure directly, are VidarFit calibration assembled from that evidence and flagged lower-confidence — considered judgements, not physiological thresholds.

Evidence Medium — Deterministic arithmetic on your own logs; the one primary source here mainly backs the caveat, not population comparisons.

For eligible barbell lifts, divides an estimated one-rep max (from a set of 10 reps or fewer) by your most recent logged bodyweight — shown alongside, never instead of, the underlying lift estimate.

Honest note. The ×BW value is deterministic arithmetic, not a body-composition or health score. Simple ratio scaling can still favor lighter athletes and does not make different exercises, sexes, ages, or techniques directly comparable — so no Beginner/Advanced/Elite population tier cutoffs are applied. Your own trend over time is the honest comparison.

Evidence Medium — The %1RM–reps relationship is peer-reviewed; the base reps×RIR chart is practitioner-validated, not peer-reviewed.

Uses a rep-range and reps-left rule for eligible weighted muscle-building progression. Load estimates still help choose starting weights and serve other workout types; estimated one-rep max remains a separate progress measure.

Honest note. The max-reps-at-%1RM relationship and the 1RM-prediction equations are peer-reviewed. The base reps×RIR→%1RM lookup derives from the RTS/Tuchscherer coaching chart, which is practitioner-validated, not peer-reviewed — we disclose that openly and the primary literature calibrates its shape. The overhead-press (vertical-press) load table carries no OHP-specific reps-to-failure data: it is extrapolated as a flat offset from the bench table — a LOW-MED-confidence magnitude — and for high-stakes vertical-press prescriptions we fall back to the bench table. The displayed deadlift one-rep max also carries a small upward correction: a practitioner-applied, display-only adjustment (LOW confidence, never fed into your prescribed loads) tied to LeSuer's finding that the standard equations underestimate deadlift 1RM by roughly ten percent — so that one figure is not itself a peer-reviewed prediction.

Evidence Medium — Intensity distribution and injury-aware progression are strongly evidenced; pace and heart-rate zones start from textbook and age-estimate priors.

Prescribes easy / threshold / interval paces and personalized heart-rate zones, and builds a run plan labeled by your goal race distance and date, using a mostly-easy intensity distribution and injury-aware progression limits.

Honest note. The intensity-distribution and injury-progression evidence is strong. The pace-zone boundaries follow Daniels' system (a textbook, cited directly) as coaching-consensus starting zones — per-athlete pace calibration is planned, not yet built. Heart-rate zones start from an age-estimated HRmax (Tanaka) as a low-confidence prior that sharpens as you log real runs; the zone seams sit at the LT1 ≈ 70% and LT2 ≈ 88% HRmax thresholds and scale by heart-rate reserve, following the endurance-training literature below, while talk-test / RPE stays the primary signal because heart rate lags and drifts. The goal race distance labels the plan today; distance-specific periodization is still to come.

Evidence Low — Mixed, graded at its weaker half: the protein anchor is well-evidenced, but the calorie and rate-of-change magnitudes rest on narrative recommendations rather than dose-finding trials.

Sets protein, calorie and macro targets from your bodyweight, goal and a safe rate of change — enough protein to build or protect muscle, an energy target sized to the trajectory, not a fixed guess.

Honest note. Protein plateaus and deficit protein needs are directly evidence-based. The rate-of-gain targets are a deliberately conservative baseline (about 0.25–0.5% bodyweight/week for novice/intermediate, slower for advanced — Iraki 2019; gaining faster mainly adds fat, Helms 2023 / Garthe 2013), labeled lower-confidence because they trace to narrative recommendations, not dose-finding trials; the compliance→expected-progress multiplier is a modeled layer on top. A goal weight and date, when set, nudge that pace within the same safe range — never past it — and the calorie number stays an initial estimate that recalibrates from your logged weigh-ins. When you're cutting and have a body-fat figure, protein is set from your estimated lean mass (a composition-adjusted target aimed at protecting muscle — depending on your body fat it can land above or below the bodyweight-based number); note the underlying protein range was studied in already-lean athletes (Helms 2014), and a tape/scale body-fat figure carries a few points of error (RFM/Navy ~3.5 points, Woolcott & Bergman 2018), so an entered or estimated value is treated the same — as an estimate.