Rows of scouting data are useless until you summarize them. Two kinds of numbers do almost all the work: measures of center (where a team's typical performance sits) and measures of spread (how much it bounces around).
Measures of Center#
Mean (average): Add every value and divide by the count. For game pieces [4, 5, 6], the mean is (4+5+6)/3 = 5. In a sheet, =AVERAGE(C2:C50). The mean uses every data point, which makes it informative but also easy to skew.
Median: Sort the values and take the middle one. For [4, 5, 6] the median is 5. With an even count like [4, 5, 6, 9], average the two middle values: (5+6)/2 = 5.5. In a sheet, =MEDIAN(C2:C50).
Why the Median Resists Outliers#
An outlier is a value far from the rest. Watch what one bad match does. Say a team scores [5, 6, 5, 6, 0] — that 0 was a dead battery, not their real ability.
- Mean =
(5+6+5+6+0)/5 = 4.4 - Median = sort to
[0, 5, 5, 6, 6], middle value = 5
The single 0 dragged the mean down more than half a point; the median barely moved. The median is resistant because it only cares about the middle value's position, not how extreme the flukes are. The mean is not — every value pulls on it. When a team's data is skewed by a breakdown or a no-show, the median tells the more honest story. When their matches are fairly even, the mean captures more.
Measures of Spread#
Two teams can share an average and play nothing alike. Spread is how you measure consistency — and at FRC, a partner you can count on often beats a partner who might explode.
- Range = max minus min (
=MAX(...)-MIN(...)). Easy, but one outlier blows it up. - Standard deviation measures how far values typically fall from the mean. Small means tightly clustered and reliable; large means boom-or-bust. In a sheet,
=STDEV(C2:C50).
A Worked Example#
Two teams, five matches each, both averaging 6 game pieces:
- Team A:
[6, 6, 5, 7, 6]— mean 6, range 2, low standard deviation. Rock-solid. - Team B:
[1, 11, 2, 10, 6]— mean 6, range 10, high standard deviation. A coin flip.
On average alone they look identical. Spread reveals Team A is a dependable second pick and Team B is a gamble you only take if you need a ceiling that high. In an elimination bracket where one dead match ends your day, that difference decides who you call.
So always report center and spread together. An average without spread is half the story — and the half that gets alliances knocked out early.
the part worth keeping
Key takeaways
- The mean uses every value but is pulled by outliers; the median is the middle value and resists them.
- Use the median when data is skewed or has extreme values (like a dead-battery zero); use the mean when data is fairly even.
- Range (max minus min) is quick but fragile; standard deviation measures typical distance from the mean and captures consistency.
- Two teams can share an average while differing wildly in spread, so always report center and spread together.
- In spreadsheets: =AVERAGE, =MEDIAN, =MAX-MIN for range, and =STDEV for standard deviation.
Scouting & StrategyData Foundations: Spreadsheets and Statisticslesson 2 of 3
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Sources and corrections
This lesson is AI-assisted: drafted from primary sources, then reviewed and edited by hand. Errors still get through. When one is reported we fix it and write down what changed, in public, in the corrections log.
sources and further reading
- khanacademy.orgSummarizing quantitative data (Khan Academy)
- khanacademy.orgRange, variance & standard deviation as measures of dispersion (Khan Academy)
- support.google.comMEDIAN function (Google Docs Editors Help)
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answer sheet
Lesson quiz
All 3 right completes the lesson. Miss one and only that question comes back, anything you already answered correctly stays banked.
0 of 3 answered
01A team scores [5, 6, 5, 6, 0], where the 0 came from a dead battery. Which statement is true?
02Two teams both average 6 game pieces. Team A scores [6,6,5,7,6] and Team B scores [1,11,2,10,6]. What does the spread tell you?
03Which measure of center is described as 'resistant' because outliers barely affect it?
Answer every question to submit.
All 32 lessons in Scouting & Strategyopenclose
01 / prerequisites
02 / scouting-fundamentals
03 / building-a-scouting-system
04 / data-analysis-tba-statbotics
05 / strategy-picklists-and-match-play
06 / worked-examples-and-mini-projects
- Not read yet:Project 1: Configure a QRScout Form for REEFSCAPE
- Not read yet:Project 2: Compute OPR by Hand, Then in a Spreadsheet
- Not read yet:Project 3: Pull Live Data with the TBA and Statbotics APIs
- Not read yet:Project 4: Build an EPA-Component Robot Ranking Sheet
- Not read yet:Project 5: Assemble a One-Page Pre-Match Prep Sheet
07 / common-mistakes-and-troubleshooting
08 / advanced-techniques-and-case-studies