How Many Runs Makes a Win?

I'm sort of gearing up to do some historical work on the Reds (I hope!).  One of the questions I wanted to answer was how many runs equals a win.  We did something like this in SABR 101x, but something about the algebra didn't seem right at the time, and the estimates we were finding seemed low.

In any case, I decided to instead generate this estimate in a fairly inelegant way called the "+1 method" (mentioned here by Patriot, though in a different context).  The approach is:

1. For each year in baseball history, find the average PythagenPat record based on average runs scored and runs allowed per team.  This will, obviously, be a 0.500 record, unless there is a clerical error.
2. For each year, find the expected PythagenPat record if you add 1 run scored to the average team.  This will be, barely, a 0.500+ record.
3. Figure the expected number of wins each year based on those two records.  This will vary depending on the number of games, and, of course, the expected record.
4. Calculate the difference between the "0.500 record" wins and the ".500 record +1 run" wins.  This gives you the wins per run.
5. Take the reciprocal of wins per run.  This is runs per win.

I actually added 0.1 runs instead of 1 run, just to avoid changing the run environment.  It probably doesn't matter.  I also tried it using +1 run allowed or -1 run scored, and it really didn't change the estimates.

Here are the results!

In addition to my run per win estimate (the blue line), I've also added straight-up total runs scored per game (i.e. runs scored + runs allowed for each game).  In the past, I've advocated just using total runs scored per game as a shorthand for the runs per win estimate.  You can see that it tracks pretty well (although it consistently underestimates the correct number over most of baseball history.

To get away from the noise of the 1800's, let's just look at the live ball era:

Ok, so from this you can see that runs per win (again, focus on the blue line) tracks between 9 and 10 runs pretty consistently.  But it definitely does vary with run environment.  As runs per game increases (orange line), so too does the number of runs you need to score to win a game.  That makes sense.

When I was working on my player value series, and as the WAR frameworks at FanGraphs and Baseball Reference were being developed in the mid-2000's, you often heard people say that 10 runs = 1 win.  That was pretty much true from 1993-2009.  But as the run environment has plummeted over the past several years (the strikeout era?), the runs needed per win has decreased as well.  In 2013, I have it at 9.07 runs per game.  It's a small thing, but something to keep in mind as we look at different eras over baseball history.

Also, different leagues unquestionably differ in runs per win.  The AL should always require more runs per win than the NL, at least since the debut of the designated hitter.  But I just wanted a blanket per-year conversion, so...

I'm sure these numbers are available elsewhere, but for those interested I'm posting a spreadsheet with these data on google docs.  If you use those data for a project that is published somewhere, please link back to this post.  All data pulled from the Lahman Database.

What caused increased use of term "sabermetrics"?

Ok, first little ditty stemming from the course.  In his introduction, Andy Andres pointed out, using the Google Ngram viewer, that the use of the term sabermetrics started with Bill James coining the term in 1980, started to fade after his last abstract in 1988, but then rose again starting around the year 1998.  I've always thought of Moneyball as the major force driving the increased interest in (and thus use of the term) sabermetrics.  But it was clearly on the rise before Moneyball's release in 2003:

Why?  Well, if you look at the graph, I'm proposing one possible reason: the rising interest in fantasy baseball.  Fantasy baseball became far easier to play as the internet took off in the mid-90's.  For many of us, myself included, fantasy baseball is the gateway drug into sabermetrics.

Of course, it certainly might run the other way, too: increased interest in sabermetrics might be driving more people to be interested in playing fantasy baseball.  But I'd guess that more come from fantasy than are driven to it.

Just a thought!

MLB Strikeouts Rising, Walks Not

One of the things I meant to address in my piece on strikeout rate last Thursday (but forgot!) was the fact that strikeouts are up across the board.  There's been a lot of discussion of this year's spike: MLB-average strikeout rate has cleared 20% for the first time (at least as far back as I've looked at it), and is now at 20.5%.  It was 19.9% last season.

This spike is not a new trend, however:

I just went back to 1980, but strikeouts have been consistently on the rise over the last 35 years (at least).  The slope has been particularly steep since 2006, and has increased every year by an average of 0.5%.

Interestingly, walk rate has simultaneously been almost flat.  This comes despite the fact that on-base percentage has become so much more heavily emphasized in the game over that stretch.

The question, of course, is what's causing the surge in strikeout rate.  Are hitters steadily becoming more willing to trade contact for power?  They could also be biasing toward taking more pitches, but if that were true one would expect walk rates to also increase.

Or is it the pitchers who are just becoming better and better, leaving hitters in the dust?  Or a bit of both?

Furthermore, when is this trend going to slow down?  It might not slow, without action by major league baseball.  This was the subject of a recent roundtable discussion on Effectively Wild.  I think there's a legitimate argument that MLB might need to follow Brian Bannister's suggestion and lower the pitching mound.  Otherwise, we're on pace to see strikeouts occur in one out of four plate appearances by the middle of the next decade.  Yikes.