It's been three weeks, twenty-four posts, and more than 16,000 words since I started my sabermetrics 101 series, and I think we've reached a good point to wind down rather than get into overly detailed discussions of individual statistics. It's not an exhaustive trek through the subject matter, and I've left quite a lot of material out (both deliberately and because I'm thick sometimes), but writing a full-blown encyclopedia wasn't really the intent. My hope was to lay down a good foundation for understanding the rest of the material written by sabermetrically inclined authors, which I think I've accomplished. If you've missed any, or just want a hub with all the links (in the correct order), here you go.

#1: Game State
#2: Regression
#3: Value
#4: Correlation
#5: Environment
#6: Pythag
#7: Run/Win Conversion
#8: Linear Weights
#9: Base Runs
#10: Rate & Counting Stats
#11: Financial & Roster Constraints
#12: Replacement Level
#13: Isolation
#14: Positional Adjustments
#15: Park Factors
#16: League Equivalencies
#17: Aging
#18: Sample Size
#19: Splits
#20: WPA
#21: Data
#22: Pitching
#23: Batting
#24: Defence

So now that that's taken care of, I have an announcement to make: Over the next few months I'll be working on a big project that I'm very excited about. Unfortunately it's going to be taking up most of my time, meaning I won't be able to contribute to Lookout Landing for the foreseeable future. It's only a sabbaticaLL, but hey, this is a good opportunity to thank my colleagues on the site and the readers of this fine blog for having me around. I'll catch y'all around in a few months. Unless you're reading the comments, in which case I'll catch y'all around whenever I next get bored at work. Or while at home. You get the drift.

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I think this is the last major one I'll be doing!

Prerequisites for Understanding: The Isolation Problem, Linear Weights, Base Runs, Value, Regression, Correlation, Park Effects, Environment, Data.

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Only a few left! Yay!

Prerequisites for Understanding: The Isolation Problem, Linear Weights, Base Runs, Replacement Level, The Run-Win Conversion, Value, Regression, Correlation, Park Effects, Environment, WPA and LI, Data.

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We're into the stretch run now. I'm not going to go into individual statistics - the idea was never to walk through absolutely everything but rather to provide a solid foundation that facilitates good, logical thinking about sabermetrics. So instead of talking about strikeouts, wins, tRA, xFIP, whatever over the next few days, I'll describe how I think pitching/batting/defence should be evaluated - but in general. We'll start with pitching.

Prerequisites for Understanding: The Isolation Problem, Linear Weights, Base Runs, Replacement Level, Expected Wins/Losses, The Run-Win Conversion, Value, Regression, Correlation, Park Effects, Environment, WPA and LI, Data.

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I believe quite strongly that before you look at statistics you should be aware of the data sources and their limitations. Hence... this.

Prerequisites for understanding: None

Prerequisites for derivation: N/A

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I feel like Jeff should be writing this one, but hey, it's my series

Prerequisites for understanding: Game state, linear weights, isolation.

Prerequisites for derivation: Game state; data.

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I find splits almost fascinating (they're good writing material!), but it's very very easy to misuse them.

Prerequisites for understanding: Sample sizes

Prerequisites for derivation: Data

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Now seemed as good a time as any.

Prerequisites for understanding: Regression, correlation.

Prerequisites for derivation: Data, regression, correlation.

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