Aging Curves: When Hitters and Pitchers Peak and Decline
What baseball aging curves show about when hitters and pitchers peak and decline, why survivorship bias makes the raw averages lie, and how to use the curves without over-trusting them.
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BABIP Explained: Luck, Skill and What Regresses
BABIP is the share of balls put in play that fall for hits. Learn the formula, the league norm near .290 to .300, why some hitters keep high marks, and how to tell luck from skill.
Batting Average, On-Base Percentage and Slugging Explained
How batting average, on-base percentage and slugging percentage are calculated, what each one captures and misses, and how league averages have moved from 1900 to the 2020s, with worked examples.
Catcher Framing Explained
Framing is how a catcher receives pitches near the edge of the zone to win more called strikes. How the skill works, how analysts measure it with tracking data, what it is worth and where the numbers mislead.
Defensive Metrics Explained: Outs Above Average, Defensive Runs Saved and UZR
How Outs Above Average, Defensive Runs Saved and Ultimate Zone Rating each measure fielding, why they disagree about the same player, and how much data you need before trusting any of them.
ERA and ERA+ Explained
How earned run average is calculated, why a 3.00 ERA means different things in different years and parks, and how ERA+ rescales a pitcher's ERA against the league so eras can be compared.
Exit Velocity, Launch Angle and Barrels Explained
How Statcast measures batted balls, what exit velocity, launch angle, hard-hit rate and barrels mean, how they fit together, what they leave out, and how home runs rose across the launch-angle era.
Expected Statistics: xBA, xSLG and xwOBA Explained
Expected batting average, expected slugging and expected wOBA estimate what a hitter should have produced from the quality of his contact. Learn how they are built, how to read the gap and where they fall short.
Fielding Percentage, Range Factor and Why Older Fielding Stats Mislead
The formulas for fielding percentage and range factor, worked with real shortstop seasons from the historical record, and the reasons both can rank defenders in the wrong order.
FIP, xFIP and SIERA: Estimating a Pitcher's Skill from What He Controls
What FIP, xFIP and SIERA measure, how to calculate FIP by hand with a worked example, why defense-independent pitching began with Voros McCracken, and when each metric helps or misleads.
How to Read a Player's Statistics Page: Every Column Explained
A plain-English glossary of the columns and abbreviations on a baseball player page, with the formulas, worked examples from real seasons and the traps to avoid when you read a stat line.
Isolated Power and the Power Metrics Explained
How to calculate isolated power (ISO), how it differs from slugging, how home run rate and Statcast barrels measure power, and what each number misses, with league and career figures from the historical record.
Lineup Construction and the Math of the Batting Order
How much does the batting order matter? This guide does the arithmetic on plate appearances by slot, compares the traditional lineup with the analytic one and shows why the choice of nine hitters matters more than their order.
OPS and OPS+ Explained: What They Measure and What They Miss
How OPS adds on-base and slugging percentage, how OPS+ adjusts it for ballpark and league so that 100 is average, with worked examples and an honest list of what neither number captures.
Park Factors Explained: Why Coors Field Is Not Fenway Park
How park factors are calculated, why one season is noisy and three are better, what the BPF and PPF fields in the historical record mean, and how to use them to compare players fairly across ballparks.
Platoon Splits and the Handedness Advantage
Why batters usually do better against pitchers who throw with the opposite hand, how big the gap is, why one season of splits misleads, and how managers and fantasy players use the idea.
Pythagorean Expectation: Estimating a Team's Record from Runs Scored and Allowed
Bill James's Pythagorean formula turns runs scored and allowed into an expected win total. Learn the math, the 1.83 exponent, worked examples from real seasons, and how to use it on a standings table.
Run Expectancy and the 24 Base-Out States
Run expectancy gives every moment of an inning a value in runs. This explainer builds the 24 base-out states, shows how a table is made, and uses worked examples to test the sacrifice bunt and the stolen base.
Sample Size and Regression to the Mean in Baseball Statistics
Why a hot month proves little, how many plate appearances it takes for strikeout rate, walk rate and batting average to mean something, and how to regress a number toward the mean, with real historical data.
Spin Rate, Spin Axis and Pitch Movement Explained
What spin rate, spin axis and spin efficiency measure, how a spinning baseball moves, and how radar and camera systems capture it, with a worked example of how much a pitch drops without spin.
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