Question
What does my class history reveal about routine, workout intensity, station use, and recorded calories?
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Personal analytics · Power BI · R · Tableau
My Orangetheory Stats
A personal workout-data project that turns two years of class logs into a guided Power BI story and a transparent calorie-burn estimator.
Project brief
Data
361 self-tracked classes from Aug. 2022–Jul. 2024, joined across general, rower, and treadmill logs.
Method
Data validation in Google Sheets, merging and regression in R, and interactive visual storytelling in Power BI and Tableau.
Explore the Power BI story
Six dashboard views, organized around a single question: what drives a stronger class?
Dashboard 01
A personal record of 361 classes.
The opening dashboard brings attendance, class mix, studios, time of day, and weekly and monthly routine into one frame. It establishes the context before moving into performance measures.
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Dashboard 02
Sustained effort is more revealing than a peak.
Calories rise most clearly with splat points and average heart rate. Steps add a moderate relationship, while maximum heart rate alone is less informative - a useful distinction between sustained and momentary effort.
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Dashboard 03
Zone time makes workout intensity visible.
The zone view compares 2G, 3G, and Strength classes and translates the five heart-rate bands into a readable intensity profile. Green and orange-zone time provide the clearest sustained-work context.
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Dashboard 04
Consistency, not a single score.
I met the 12-splat-point goal in 337 of 361 classes. This view compares classes that met the goal with those that did not, connecting heart-rate-zone composition to calorie and heart-rate outcomes.
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Dashboards 05–06
Workout structure matters as much as distance.
The final views pair station-level summaries with distance comparisons. Rower distance rises with calories and splat points, while more treadmill distance does not automatically mean a higher-intensity class.
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Key takeaways
Intensity over distance
Splat points and average heart rate were more closely associated with calories than maximum heart rate or distance alone.
A consistent routine
Morning 2G classes made up the largest share of the history, with Brentwood and Century City accounting for most visits.
Station context matters
Rower participation changed averages only slightly; interval structure and sustained effort better explain the differences.
From analysis to interaction
A personal calorie-burn estimate, made inspectable.
I translated an R regression model into a Tableau calculator with five inputs: splat points, class type, average heart rate, rower distance, and steps. The model explains 75.7% of the variation in recorded calories across 245 complete historical records.
This is a personal, in-sample estimate - not a medical tool or a general calorie prescription.
Try the calculator
Open interactive calculator ↗Reflection
Personal data becomes useful when it supports a clearer next question.
Consistent tracking made it possible to move from a class log to analysis, visualization, and an interactive model - while keeping the scope and limits of the data visible.