## Distribution of the batting order slot that ends a baseball game

The God Plays Dice blog has a nice piece attempting to model a baseball question. Baseball is wonderful for all kinds of mathematics questions, partly because the game has since its creation kept data about the plays made, partly because the game breaks its action neatly into discrete units with well-defined outcomes.

Here, Dr Michael Lugo ponders whether games are more likely to end at any particular spot in the batting order. Lugo points out that certainly we could just count where games actually end, since baseball records are enough to make an estimate from that route possible. But that’s tedious, and it’s easier to work out a simple model and see what that suggests. Lupo also uses the number of perfect games as a test of whether the model is remotely plausible, and a test like this — a simple check to whether the scheme could possibly tell us something meaningful — is worth doing whenever one builds a model of something interesting.

Tom Tango, while writing about lineup construction in baseball, pointed out that batters batting closer to the top of the batting order have a greater chance of setting records that are based on counting something – for example, Chris Davis’ chase for 62 home runs. (It’s interesting that enough people see Roger Maris’ 61 as the “real” record that 62 is a big deal.) He observes that over a 162-game season, each slot further down in the batting order (of 9) means 18 fewer plate appearances.

Implicitly this means that every slot in the batting order is equally likely to end the game — that is, that the number of plate appearances for a team in a game, mod 9, is uniformly distributed over {0, 1, …, 8}.

Can we check this? There are two ways to check it:

• 1. find the number of plate appearances in every game…

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## Reblog: Lawler’s Log

I don’t intend to transform my writings here into a low-key sports mathematics blog. I just happen to have run across a couple of interesting problems and, after all, sports do offer a lot of neat questions about probability and statistics.

benperreira here makes mention of “Lawler’s Law”, something I had not previously noticed. The “Law” is the observation that the first basketball team to make it to 100 points wins the game just about 90 percent of the time. It was apparently first observed by Los Angeles Clippers announcer Ralph Lawler and has been supported by a review of the statistics of NBA teams over the decades.

benperreira is unimpressed with the law, regarding it as just a restatement of the principle that a team that scores more than the league average number of points per game will tend to have a winning record in an unduly wise-sounding phrasing. I’m inclined to agree the Law doesn’t seem to be particularly much, though I was caught by the implication that the team which lets the other get to 100 points first still pulls out a victory one time out of ten.

To underscore his point benperreira includes a diagram purporting to show the likelihood of victory to points scored, although it’s pretty obviously meant to be a quick joke extrapolating from the data that both teams start with a 50 percent chance of victory and zero points, and apparently 100 points gives a nearly 90 percent chance of victory. I am curious about a more precise chart — showing how often the first team to make 10, or 25, or 50, or so points goes on to victory, but I certainly haven’t got time to compile that data.

Well, perhaps I do, but my reading in baseball history and brushes up against people with SABR connections makes it very clear I have every possible risk factor for getting lost in the world of sports statistics so I want to stay far from the meat of actual games.

Still, there are good probability questions to be asked about things like how big a lead is effectively unbeatable, and I’ll leave this post and reblog as a way to nag myself in the future to maybe thinking about it later.

Lawler’s Law states that the NBA team that reaches 100 points first will win the game. It is based on Lawler’s observations and confirmed by looking back at NBA statistics that show it is true over 90% of the time.

Its brilliance lies in its uselessness. Like NyQuil helps us sleep but does little to help our immune systems make us well, Lawler’s Law soothes us by making us think it means something more than it does.

Why is it so useless, one may venture to ask?

This is a graphical representation of Lawler’s Law. Point A represents the beginning of a game. This team (which ultimately wins this game) has roughly a 50% chance of winning at that point. As the game goes on, and more points are scored, the team depicted here increases its chance of victory based on the number of points it has scored. Point B…

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## Trivial Little Baseball Puzzle

I’ve been reading a book about the innovations of baseball so that’s probably why it’s on my mind. And this isn’t important and I don’t expect it to go anywhere, but it did cross my mind, so, why not give it 200 words where they won’t do any harm?

Imagine one half-inning in a baseball game; imagine that there’s no substitutions or injuries or anything requiring the replacement of a batter. Also suppose there are none of those freak events like when a batter hits out of order and the other team doesn’t notice (or pretends not to notice), the sort of things which launch one into the wonderful and strange world of stuff baseball does because they did it that way in 1835 when everyone playing was striving to be a Gentleman.

What’s the maximum number of runs that could be scored while still having at least one player not get a run?