NBA / Player profiles

NBA variability and its league baseline

Published shrunk points, rebounds, and assists CVs compared with their same-snapshot league mean raw CV priors.

Derived analysis30 published rows11 fieldsSource as of 2026-04-12

Published measurements

Choose a measurement

MeasurementPopulationOrder

Only the published extremes are available as player rows, not the complete eligible population. All rows are shown without a pooled ranking, median, or percentile.

30 matching rows; 30 contain shrunk cv range.

CSV includes 30 matching rows, all fields, and source context; missing measurements stay blank. Published source dates and row provenance are included when available; structured provenance uses JSON cells.

NBA variability and its league baseline: all published measurement fields
Entity	Shrunk CV range	Highest shrunk stat CV	Lowest shrunk stat CV	Points shrunk CV	Rebounds shrunk CV	Assists shrunk CV	Qualifying games	Points: shrunk CV minus prior	Rebounds: shrunk CV minus prior	Assists: shrunk CV minus prior	Source shrink weight
Luka DoncicPublished low-CV subset	0.1176	0.3975	0.2799	0.2799	0.3569	0.3975	184	-0.2443	-0.1992	-0.385	90.2%
Nikola JokicPublished low-CV subset	0.0969	0.4072	0.3103	0.3103	0.3194	0.4072	210	-0.2139	-0.2367	-0.3753	91.3%
Domantas SabonisPublished low-CV subset	0.1581	0.471	0.3129	0.3297	0.3129	0.471	170	-0.1945	-0.2432	-0.3115	89.5%
Giannis AntetokounmpoPublished low-CV subset	0.2566	0.5232	0.2666	0.2666	0.3333	0.5232	173	-0.2576	-0.2228	-0.2593	89.6%
Shai Gilgeous-AlexanderPublished low-CV subset	0.2348	0.4722	0.2374	0.2374	0.4722	0.4253	218	-0.2868	-0.0839	-0.3572	91.6%
Cade CunninghamPublished low-CV subset	0.1601	0.4675	0.3074	0.3074	0.4675	0.3756	192	-0.2168	-0.0886	-0.4069	90.6%
LeBron JamesPublished low-CV subset	0.1526	0.452	0.2994	0.2994	0.452	0.4055	201	-0.2248	-0.1041	-0.377	91%
Jayson TatumPublished low-CV subset	0.1984	0.4914	0.293	0.293	0.387	0.4914	162	-0.2312	-0.1691	-0.2911	89%
Paolo BancheroPublished low-CV subset	0.1199	0.4515	0.3316	0.3316	0.3909	0.4515	190	-0.1926	-0.1652	-0.331	90.5%
Alperen SengunPublished low-CV subset	0.1575	0.4768	0.3193	0.3193	0.3856	0.4768	208	-0.2049	-0.1705	-0.3057	91.2%
Kawhi LeonardPublished low-CV subset	0.1652	0.4889	0.3237	0.3237	0.3881	0.4889	164	-0.2005	-0.168	-0.2936	89.1%
Scottie BarnesPublished low-CV subset	0.1191	0.4436	0.3245	0.3245	0.4367	0.4436	196	-0.1997	-0.1194	-0.3389	90.7%

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01 / Interpretation

What this measures

A positive signed gap means the published shrunk stat CV exceeds its same-snapshot prior; a negative gap means it is below. Gaps are dimensionless CV units, not percentage points. Shrinkage attenuates each gap toward that prior. Published four-decimal CVs and priors make calculated gaps approximate; the source weight is rounded to three decimals. The within-player range does not identify a universally most unstable role.

02 / Calculation

For each stat, raw CV = sample standard deviation (ddof=1) / mean of qualifying per-36 game rates. Source shrinkage: shrunk CV = w * raw player CV + (1 - w) * same-snapshot league mean raw CV, with w = games / (games + K) and source K = 20 games. The published weight is the raw-player-CV share of the blend, not a confidence score. The prior is the unweighted mean of qualifying players' raw CVs, not a pooled game CV. Signed gap = published shrunk CV - published raw league mean CV prior. CV range = max(three published shrunk CVs) - min(three published shrunk CVs).

Use the table to inspect available fields and the source JSON to trace the formula inputs. CSV percentage values are stored as fractions.

03 / Population & limits

30 published players from the two selected CV extremes; 579 players meeting the published floor; seasons 2023-24, 2024-25, 2025-26; at least 15 qualifying games; at least 10 minutes per qualifying game; source as of 2026-04-12.

Only selected extremes are shown. Raw per-player standard deviations and per-stat valid counts are unavailable; the games column counts appearances meeting the minutes floor. The league reference includes each selected player and is not an independent comparison sample. CV rises mechanically when a stat mean is low. Cross-stat gaps are not standardized. These historical values do not measure skill, forecast uncertainty, or causal effects.

04 / Source & method references

Published source JSON NIST coefficient of variation Published NBA consistency producer

References explain ingredients and prior methods. They do not validate this derived analysis or establish its originality.