Read the numbers properly.

Short, honest lessons on sports statistics — sample size, rate stats, park factors, regression to the mean — and on how betting markets work. No locks, no hype, no guru act. The same principles our own research runs on.

Track 1

Reading the Numbers

Statistical literacy for sports: what a number can tell you, and what it can't.

Rate Stats vs Counting Stats

4 min

A counting stat rewards opportunity. A rate stat measures quality. Confusing the two is the most common mistake in sports analysis, and it is why the league leader in a category is often not the best player in it.

What Sample Size Does to a Batting Average

6 min

A .300 average over 40 at-bats is consistent with a true talent anywhere from .158 to .442. Small samples do not produce small errors — they produce wide ranges that get reported as single numbers.

Why Per-Game Averages Mislead

5 min

An average collapses a distribution into one number and throws away the shape. Two players averaging 18 points can have completely different floors, ceilings, and consistency — and the average cannot tell them apart.

Regression to the Mean

5 min

Extreme performances tend to be followed by less extreme ones — not because anything changed, but because extremes are partly luck, and luck does not repeat. This is the most useful idea in sports analysis and the most consistently misread.

Base Rates: The Number You Forgot to Ask For

5 min

Before asking whether something is impressive, ask how often it happens anyway. Most sports claims that sound remarkable are describing an ordinary base rate in dramatic language.

Correlation, Causation, and Sports Narratives

5 min

Teams that run the ball a lot tend to win. That does not mean running the ball causes winning — teams run because they are already ahead. Most sports narratives are causation claims resting on correlation evidence.

Hot Streaks and Survivorship

6 min

If you search 500 players for a ten-game streak, you will find several — even if every player is a coin flip. The streak is real; the search that found it is what makes it meaningless.

Why Projections Have Ranges

5 min

A projection is a distribution reported as a number. The single figure is the middle of a range, and for most players that range is wide enough that the point estimate is the least interesting part of it.

Which Stats Stabilize First

5 min

Not all statistics become trustworthy at the same rate. Some are meaningful within weeks; others need more than a season. Knowing which is which tells you what you are allowed to conclude in May.

Expected Stats vs What Happened

5 min

Expected statistics estimate what should have resulted from the quality of what a player did, ignoring where the ball happened to land. The gap between expected and actual is usually luck, and usually closes.

Comparing Players Across Eras

5 min

Raw statistics are not comparable across decades, because the conditions producing them changed. Era adjustment compares a player to his own league instead of to a fixed number.

What a Ranking Actually Encodes

5 min

Every ranking is a set of weighting choices wearing the appearance of an objective list. Two credible systems can disagree sharply and both be defensible — the disagreement is usually about what to value, not about the facts.

Track 2

Context & Matchups

The same stat line means different things in different parks, paces, and schedules.

Track 3

Fantasy Analytics

Roles, usage, and schedule — what actually drives fantasy production.

Track 4

Betting 101

The mechanics every bettor should know before placing a dollar.

Track 5

Reading the Market

Prices move for reasons. Learn to read them.

Track 6

Strategy & Discipline

The habits that separate a rough week from a wiped-out bankroll.

Track 7

Play Smart

Keeping it what it should be — a hobby you control.

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