Standard · Methodology

How benchmarks work

Every Benchmark chip a parent or coach sees on PlayerFocus is sourced from peer-reviewed or institutional reference data. Here's exactly how a single test result becomes a percentile — and what we do when no published norm exists.

From a stopwatch number to a percentile

When a coach records a 10m sprint of 1.95 seconds for a U12 boy, the resolver does a 4-dimensional lookup against our reference table:

(test_slug, sport_type, sex, age_band)
   = (sprint_10m, soccer, male, U12)

That returns a single normative row — five points (p10, p25, p50, p75, p90) anchored to a cited source. We linearly interpolate the athlete's value between those bands, clamp outliers at the 5th / 95th percentile (we don't claim a 99th percentile from only five sample points), and return a number alongside its provenance. The chip shows the percentile AND the source label AND the population N — never the percentile alone.

The source ladder

When multiple sources cover the same cohort, the resolver picks in this order:

  1. 01

    PlayerFocus Internal Cohort Data

    Aggregated anonymized test results from PlayerFocus academies. Becomes the primary source for a (test, sport, sex, age) cohort once N ≥ 50 athletes recorded — flipping above any published source in the resolver ladder.

    Covers: (promoted automatically as data accumulates)

  2. 02

    Tomkinson et al. 2017

    Tomkinson GR, Carver KD, Atkinson F, et al. European normative values for physical fitness in children and adolescents aged 9–17 years: results from 2 779 165 Eurofit performances representing 30 countries. Br J Sports Med 2018;52:1445-1456.

    Reference link →

    Covers: 20m sprint, 30m sprint (extrapolated), 40m sprint (extrapolated), Vertical jump, Beep test (PACER)

  3. 03

    FITNESSGRAM Healthy Fitness Zone (Cooper Institute)

    Cooper Institute. FITNESSGRAM/ACTIVITYGRAM Reference Guide, 5th edition. Healthy Fitness Zone (HFZ) thresholds for U.S. youth.

    Reference link →

    Covers: Beep test (PACER), Cooper 12-min run

  4. 04

    Castro-Piñero et al. 2010

    Castro-Piñero J, Ortega FB, Artero EG, et al. Assessing muscular strength in youth: usefulness of standing long jump as a general index of muscular fitness. J Strength Cond Res 2010;24(7):1810-1817. European youth dataset (N=2,778) used for 10m sprint phase data.

    Covers: 10m sprint

  5. 05

    Bangsbo, Iaia & Krustrup 2008

    Bangsbo J, Iaia FM, Krustrup P. The Yo-Yo Intermittent Recovery Test: a useful tool for evaluation of physical performance in intermittent sports. Sports Medicine 2008;38(1):37-51. Combined with Castagna et al. 2010 (Med Sci Sports Exerc) for youth soccer calibration.

    Covers: Yo-Yo IR1

  6. 06

    Pauole et al. 2000

    Pauole K, Madole K, Garhammer J, Lacourse M, Rozenek R. Reliability and validity of the T-test as a measure of agility, leg power, and leg speed in college-aged men and women. J Strength Cond Res 2000;14(4):443-450. The canonical T-test reference paper.

    Covers: T-test

  7. 07

    IAAF / World Athletics Youth Performance Tables

    World Athletics (formerly IAAF). Youth Performance Tables — open-access aggregate from member national federations.

    Reference link →

    Covers: 60m sprint

  8. 08

    NSCA Youth Position Statement (Faigenbaum 2016)

    Faigenbaum AD, Lloyd RS, Oliver JM. National Strength and Conditioning Association Position Statement on Long-Term Athletic Development. J Strength Cond Res 2016;30(6):1491-1509.

    Covers: 5-10-5 shuttle, Standing broad jump

PlayerFocus Internal Cohort Data sits at the top of the ladder because a same-sport, same-age peer cohort is a more relevant comparison than a global European average. Once a (test, sport, sex, age) cohort has accumulated 50+ recorded athletes in the platform, the nightly recompute promotes our internal data above the published source for that cell. The chip's source label changes from "Tomkinson 2017" to "PlayerFocus Internal · N=52" with no UI change required.

What we don't do

  • We don't invent percentiles. When no source covers an athlete's cohort, the chip says "No reference data for this cohort" and shows the measured value without a comparison.
  • We don't hide the source. Every chip displays the source label and population N. Parents can sniff fake numbers; citation builds trust.
  • We don't mix datasets silently. Each cohort cell uses one source. Multi-source weighting introduces math that can't be audited from the outside.
  • We don't hold values out of the timeline because a percentile didn't resolve. The result still shows; only the comparison is omitted.

Coverage today

This matrix is generated from our live reference table — it reflects exactly which youth cohorts the resolver can answer right now. Cells marked "—" have no published norm seeded yet; for those, the PlayerFocus Internal cohort will become the primary source as data accumulates.

TestU8U10U12U14U16U18U21
10m SprintM+FM+FM+FM+FM+F
20m SprintM+FM+FM+FM+FM+F
30m Sprintunisexunisexunisexunisexunisex
40m Sprintunisexunisexunisex
5-10-5 ShuttleM+FM+FM+FM only
60m Sprintunisexunisexunisexunisex
Beep Test (PACER)M+FM+FM+FM+FM+F
Cooper 12-min RunM+FM+FM+FM+FM+F
Standing Broad JumpM+FM+FM+FM+FM+F
T-TestM+FM+FM+FM+F
Vertical JumpM+FM+FM+FM+FM+F
Yo-Yo IR1M+FM+FM+FM+FM+F

97 reference rows · 7 sources · last refreshed May 12, 2026

Why some chips don't appear

If your athlete's Benchmark chip is missing for a particular test, one of these is true:

  1. No published youth norm covers their cohort. Most peer-reviewed youth datasets stop at U18; U8 and U21 athletes hit this regularly.
  2. The published norm is sex-segregated and only one sex is seeded. A few cohorts (e.g., 5-10-5 shuttle at U18) only have male reference data in the literature we've cited.
  3. Their record is missing an age or sex. The resolver needs both to do a comparison. Coach can update on the player profile.
  4. The test is new to the catalog and no source has been seeded yet. This is what PlayerFocus Internal solves automatically as data accrues.

Audit + verification

Every reference row in our table carries a verification flag. Rows land as "sourced, pending audit" until our team cross-checks the percentile bands against the original publication. Verified rows are flagged in the in-app ops surface; unverified rows still resolve normally for full transparency.

Questions about the methodology, or want to suggest a source we've missed? hello@playerfocus.ca

Part of the PlayerFocus Standard — our public reference for how we build and measure youth athletic development.