[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_26":27,"_28":29,"_30":12,"_31":12,"_32":12,"_33":12,"_34":12,"_35":12,"_36":37},"routes/canvas.shared.$sharedTextdocId",{"_9":10,"_11":12},"sharedTextdoc",{"_13":14,"_15":-7,"_16":17,"_18":19,"_20":21,"_22":23,"_24":12,"_25":12},"isAuthenticated",false,"sharedTextdocId","68a4cb3c95fc8191ba225c33634907dd","versionInt","title","Garmin 5k Vs Vo2 Max — Scatter","type","code/react","content","import React, { useMemo, useState } from \"react\";\nimport {\n ResponsiveContainer,\n ScatterChart,\n Scatter,\n XAxis,\n YAxis,\n CartesianGrid,\n Tooltip,\n Legend,\n ReferenceArea,\n} from \"recharts\";\n\n// Helper to format seconds -> m:ss\nfunction fmtTime(sec: number): string {\n const m = Math.floor(sec / 60);\n const s = Math.round(sec % 60);\n return `${m}:${s.toString().padStart(2, \"0\")}`;\n}\n\n// Raw points pulled from the Reddit thread the user pasted.\n// Fields: label (user/short note), timeSec (5k time), vo2 (Garmin running VO2max), age, sex, flags\nconst RAW: Array<{\n label: string;\n timeSec: number;\n vo2: number;\n age?: number;\n sex?: \"M\" | \"F\";\n flags?: Array<\"ambiguous\" | \"estimate\" | \"range-avg\">;\n}> = [\n { label: \"OP_29M\", timeSec: 27 * 60 + 18, vo2: 41, age: 29, sex: \"M\" },\n { label: \"LibraryTime11011011_40M\", timeSec: 18 * 60 + 49, vo2: 58, age: 40, sex: \"M\" },\n { label: \"justlookbelow_56M\", timeSec: 18 * 60 + 49, vo2: 58, age: 56, sex: \"M\" },\n { label: \"John_the_cyclist_65M\", timeSec: 20 * 60 + 59, vo2: 54, age: 65, sex: \"M\", flags: [\"ambiguous\"] }, // possibly cycling\n { label: \"Away-Evening-6547_51M\", timeSec: 22 * 60 + 45, vo2: 51, age: 51, sex: \"M\" },\n { label: \"easternhorizon_32M\", timeSec: 24 * 60 + 46, vo2: 41, age: 32, sex: \"M\" },\n { label: \"DeSlacheable_39F\", timeSec: 28 * 60 + 34, vo2: 27, age: 39, sex: \"F\" },\n { label: \"LeperMessiah11_40M\", timeSec: 25 * 60 + 43, vo2: 49, age: 40, sex: \"M\" },\n { label: \"Conscious_Olive_8361_34M\", timeSec: 25 * 60 + 49, vo2: 50, age: 34, sex: \"M\" },\n { label: \"tajpr_41M\", timeSec: 24 * 60 + 51, vo2: 49, age: 41, sex: \"M\" },\n { label: \"Tyler_Durden69420\", timeSec: 17 * 60 + 6, vo2: 63, flags: [\"range-avg\"] }, // 62–64\n { label: \"glr123_36M\", timeSec: 18 * 60 + 0, vo2: 64.5, age: 36, sex: \"M\", flags: [\"range-avg\"] }, // 64/65\n { label: \"SeparateBus5141_44M\", timeSec: 22 * 60 + 21, vo2: 54, age: 44, sex: \"M\" },\n { label: \"Sadpanda0_35M\", timeSec: 22 * 60 + 13, vo2: 54, age: 35, sex: \"M\" },\n { label: \"yung_emppu_33M\", timeSec: 22 * 60 + 55, vo2: 47, age: 33, sex: \"M\" },\n { label: \"hurtta59_37\", timeSec: 15 * 60 + 32, vo2: 70, age: 37 },\n { label: \"neintineinproblems_47M\", timeSec: 25 * 60 + 43, vo2: 48, age: 47, sex: \"M\" },\n { label: \"brianzors_33M\", timeSec: 21 * 60 + 19, vo2: 54, age: 33, sex: \"M\" },\n { label: \"EPICxNITRI_26M\", timeSec: 22 * 60 + 50, vo2: 54, age: 26, sex: \"M\" },\n { label: \"Hubbabz_36M\", timeSec: 26 * 60 + 0, vo2: 52, age: 36, sex: \"M\" },\n { label: \"tomogian_35M\", timeSec: 22 * 60 + 22, vo2: 49, age: 35, sex: \"M\" },\n { label: \"finalj22_41M\", timeSec: 21 * 60 + 56, vo2: 56, age: 41, sex: \"M\" },\n { label: \"dizy777_47M\", timeSec: 22 * 60 + 11, vo2: 58, age: 47, sex: \"M\" },\n { label: \"rightboobenthusiast_38M\", timeSec: 27 * 60 + 45, vo2: 39, age: 38, sex: \"M\" },\n { label: \"sfo2_42M\", timeSec: 19 * 60 + 0, vo2: 52, age: 42, sex: \"M\" },\n { label: \"silly_billy1303_22M\", timeSec: 18 * 60 + 45, vo2: 59, age: 22, sex: \"M\" },\n { label: \"Old-Ad3767_50M\", timeSec: 22 * 60 + 21, vo2: 52, age: 50, sex: \"M\" },\n { label: \"Spiffman-Space_44M\", timeSec: 18 * 60 + 39, vo2: 60, age: 44, sex: \"M\" },\n { label: \"I_Have_Hairy_Teeth_41M\", timeSec: 19 * 60 + 45, vo2: 57.5, age: 41, sex: \"M\", flags: [\"range-avg\"] }, // 56–59\n { label: \"run_swim_nobike_42F\", timeSec: 23 * 60 + 22, vo2: 47, age: 42, sex: \"F\" },\n { label: \"x7leafcloverx_40M\", timeSec: 29 * 60 + 20, vo2: 48, age: 40, sex: \"M\" },\n { label: \"Hampshire_Coast_62M\", timeSec: 20 * 60 + 23, vo2: 59, age: 62, sex: \"M\" },\n { label: \"Togata_29M\", timeSec: 21 * 60 + 24, vo2: 42, age: 29, sex: \"M\" },\n { label: \"Calthyr_FR965_35M\", timeSec: 20 * 60 + 11, vo2: 56, age: 35, sex: \"M\" },\n { label: \"GregryC1260_54M\", timeSec: 21 * 60 + 41, vo2: 55, age: 54, sex: \"M\", flags: [\"estimate\"] },\n { label: \"Ok-Home-8059_46M\", timeSec: 20 * 60 + 14, vo2: 55, age: 46, sex: \"M\" },\n { label: \"lucain0_36\", timeSec: 19 * 60 + 13, vo2: 55, age: 36 },\n { label: \"femn703_56M\", timeSec: 30 * 60 + 13, vo2: 40, age: 56, sex: \"M\" },\n { label: \"turtlejai_35M\", timeSec: 32 * 60 + 18, vo2: 41, age: 35, sex: \"M\" },\n { label: \"skatchawan_50M\", timeSec: 26 * 60 + 30, vo2: 45, age: 50, sex: \"M\" },\n { label: \"TrainingMight2622_24F\", timeSec: 21 * 60 + 20, vo2: 63, age: 24, sex: \"F\" },\n { label: \"iseebirdsfly\", timeSec: 23 * 60 + 50, vo2: 43 },\n];\n\nfunction pearson(x: number[], y: number[]) {\n const n = x.length;\n const mx = x.reduce((a, b) => a + b, 0) / n;\n const my = y.reduce((a, b) => a + b, 0) / n;\n let num = 0,\n dx = 0,\n dy = 0;\n for (let i = 0; i < n; i++) {\n const vx = x[i] - mx;\n const vy = y[i] - my;\n num += vx * vy;\n dx += vx * vx;\n dy += vy * vy;\n }\n return num / Math.sqrt(dx * dy);\n}\n\nexport default function Garmin5kVo2Scatter() {\n const [showAmbiguous, setShowAmbiguous] = useState(true);\n const [showEstimates, setShowEstimates] = useState(true);\n\n const data = useMemo(() => {\n return RAW.filter((d) => {\n const flags = new Set(d.flags ?? []);\n if (!showAmbiguous && flags.has(\"ambiguous\")) return false;\n if (!showEstimates && (flags.has(\"estimate\") || flags.has(\"range-avg\"))) return false;\n return true;\n }).map((d) => ({ ...d, timeLabel: fmtTime(d.timeSec) }));\n }, [showAmbiguous, showEstimates]);\n\n const xMin = Math.min(...data.map((d) => d.vo2)) - 1;\n const xMax = Math.max(...data.map((d) => d.vo2)) + 1;\n const yMin = Math.min(...data.map((d) => d.timeSec)) - 15;\n const yMax = Math.max(...data.map((d) => d.timeSec)) + 15;\n\n const r = useMemo(() => pearson(data.map((d) => d.vo2), data.map((d) => d.timeSec)), [data]);\n\n return (\n

5K Time vs VO₂ Max (Reddit sample)

\n Each point is a user report from the pasted thread. Hover for details. Lower is better on the Y-axis.\n

\n \n setShowAmbiguous(e.target.checked)}\n />\n Include ambiguous (e.g., possible cycling)\n \n \n setShowEstimates(e.target.checked)}\n />\n Include estimates / ranges\n \n

\n\n

\n n = {data.length}\n \n Pearson r (VO₂ vs Time) = {r.toFixed(3)} (expect negative correlation)\n \n

\n\n

\n \n \n \n \n \n {\n if (name === \"timeSec\") return [fmtTime(value as number), \"5K time\"];\n return [value, name];\n }}\n labelFormatter={() => \"\"}\n contentStyle={{ borderRadius: 12 }}\n />\n \n\n \n {/* We rely on default point rendering. */}\n \n\n {/* Optional shaded area where data is sparse (slow times & very high VO2 should be rare) */}\n \n \n \n

\n\n

Notes & assumptions

Times were converted to total seconds for plotting; the Y-axis shows m:ss.
Entries marked ambiguous may not be comparable (e.g., a cyclist username reporting a run).
Where a VO₂ max range was given (e.g., 56–59) we used the mid-point and flagged it as range-avg.
One historical time had an estimated VO₂; it is flagged estimate.
This is anecdotal, self-reported data; Garmin VO₂ estimates vary by device/algorithm and training status.

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