The Best Statement I Read Today

Tom Boswell, as quoted in The Hidden Game of Baseball:

the more ambitious the stat, the more complex and arbitrary it almost always becomes. What it gains in sophistication and the intuitive wisdom of its creator, it loses in simplicity and objectivity. How can you love a stat, or use it in arguments, if you can’t really explain it?

8 Responses “The Best Statement I Read Today”

  1. LeShawn Anderson says:


    OK, I’ll bite: How ambitious/complex do you think PrOPS is?

  2. JC says:

    It hinges on what you think of OPS. PrOPS is an estimate of OPS. It is complicated, and I don’t rely on it for much. Without past performance and OPS, PrOPS doesn’t offer much guidance.  OPS is just OBP + SLG, which most people understand; however, its chief virtue is its ease of calculation from scoreboard statisitics.  Linear Weights and Runs Created are easier to explain, but are quite difficult to calculate. I think VORP and Total Average (ironically developed by Boswell) don’t make intuitive sense and are difficult to calculate.

  3. If this were true, how is QB rating accepted and popular with NFL fans and broadcasters? If find it comparable to EqA or wOBA in complexity, yet I see it used on TV all the time.

  4. Rick says:

    I don’t like any stat that uses Replacement Players as a benchmark because there are no such animals in MLB besides maybe just a couple that are placeholders. Linear Weights is an excellent stat.

  5. JC says:

    That a stat is popular does not make it worthwhile. The QB rating is about the most arbitrary and useless statistic in existence.  I don’t find EqA and wOBA helpful when analyzing hitters (unnecessarily complicated); however, the metrics are designed with the intent of properly valuing player contributions.  They are far superior to the QB rating, which is a random assortment of things sort-of related to QB performance.

  6. Phil Birnbaum says:

    Shouldn’t you want to use the most accurate statistic possible, without regard to how complicated it is?

    In other fields, like economics, do they ever revert to less accurate measures in the academic literature because they’re simpler?

  7. JC says:

    I’m not sure how the above statement is at odds with accuracy.

  8. Phil Birnbaum says:

    Yes, I guess you’re right.