Comparing baseball greats across eras, who comes out on top?
phys.org
phys.org
Hypothesis 1: statisticians love good data sources, and with its many games, innings, and types of hits / pitches it’s a great source.
Hypothesis 2: makes you seem more interesting at dinner parties
hypothesis 3: a natural overlap of preferences
Further, having the discussion of "steroids" being centered around *steroids* is a bit of an oversimplification as by and large the state of the art had moved on by the heyday of Bonds/McGuire/Sosa. Nevertheless, the focus was always on the chemicals that made players big & strong, meanwhile the ones that helped to *preserve* muscle and/or enhance recovery speed were more impactful.
And even then, simply looking at things like power outliers over time isn't useful. State of the art in terms of play style changed over time. For instance there have been eras where players were intentionally hitting for contact and eras where players were intentionally hitting for power.
Or, one can just relax in the knowledge that players have been cheating, chemically or otherwise, from time immemorial, and that it's impossible to retroactively sort out. So if we compare players relative to their peers and then use that to compare across eras we can get a better sense. But it's folly to read too much into all of this.
That's just way too hand-wavy for me. Not all crimes should be categorized as misdemeanors. We have misdemeanors and felonies for a reason.
For instance, it was understood by those in the uhhh let's call it "sports nutrition" circles at the time that as a class pitchers were benefiting more overall than batters from the chemical enhancement options of that era. But yet the focus was on the home run hitter outliers. Why?
And let's also not forget that the poster children of the anti-steroid brigade are players who would have likely already been all time greats. Anyone who thinks that a Nobody became a HoFer is deluding themselves. Further: who had more to gain? The already great talent, or the marginal AAAA player who was just looking for an edge to make a team out of spring training?
My point here is that views like you're espousing are too black & white, and too narrowly applied. There's *way* too much noise to sort it all out. None of the household names of "the steroid era" were doing anything different than most of the other players. They were just already great.
That's exactly what I proposed above. I didn't say I was right. I proposed a methodology to say that I'm right (or wrong).
> Statistical outlier analysis of different time periods would help settle this matter.
Such an analysis would need to: a) prove that such outliers are caused by cheating, b) prove *which* form of cheating led to those outliers, c) prove that each individual outlier *was* taking part in that form of cheating, etc. And even then all that manages to capture are outliers. It doesn't capture the hordes of players who weren't outliers, rather they were only in the league because they were using whatever form of cheating to help make the cut.
In other words, the strong anti-cheating stances when applied to historical players is just as handwavey as the let it go philosophy I espoused earlier.
This was a guy who took 14 ballots to get in the Hall of Fame.
I'm not sure summing up career WAR is the best way to rank players, though. It favors guys who played a long time, like Blyleven who played 22 seasons. Sandy Koufax played half as long but was undoubtedly better at his peak. Who was really "better" overall? You probably want some metric that combines career totals and peak production, but ultimately there is no universal way to come up with one definitive ranking, so we will debate it forever.
>...but ultimately there is no universal way to come up with one definitive ranking, so we will debate it forever.
WAR is a universal way to come up with a definitive ranking. It's a framework for measuring player contributions that is applied equally to all players. That's not to say it is the universal way, but the beauty of WAR is that the framework can be re-created to value or devalue player contributions as one sees fit and then use those criteria to measure all player contributions.
That's why the authors of this paper cite the two most common WAR frameworks (bWAR and fWAR). And it's why they've created their own version which incorporates a measure of the available talent pool at the time of each player's career.
How does WAR miss this goal? It credits year-to-year player contributions and gives more credit for better seasonal performances. Longevity alone doesn't ensure a higher WAR total since a negative WAR valuation is possible (and common).
> Well there's infinite ways to combine peak and career totals, and "10 years of 1 WAR is equal to 1 year of 10 WAR" is certainly one of them.
That means that you can imagine many different ways of calculating overall career quality, even if you restrict yourself to just using WAR values. Summing up all the seasons is one of them. Others might give some additional value for exceptional seasons. For instance https://a.espncdn.com/magazine/1224NBAHOB.pdf as a simple example. I use a similar formula for Hall of Fame eligibility in my video game.
This sounds like it would be a form of double counting. I'd be more inclined toward something like WAR/162 games (or whatever season length is in play).
Think of it in terms of HN:
Let's say you and I both make the same number of comments and submissions per year. For 7 years each of your comments and submissions gets 100 karma. For 20 years each of mine gets 75 karma. On a per-comment/submission basis you contributed more, but I contributed more in my HN career.