FanGraphs Baseball


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  1. What’s the relationship between VOL and K rate, especially on the team level? Seems like it would be pretty high.

    Comment by olethros — June 17, 2013 @ 12:19 pm

  2. Fascinating topic.

    One question raised in the article from last year (follow the first link above) was regarding the value of consistency. Thinking of it purely in BA, is it better to go 1/3 every day, or 0/3,0/3,3/3?

    I can come up with reasoning either way, but have no strong gut guess either way at this point.

    Comment by Mac — June 17, 2013 @ 12:31 pm

  3. Sorry if this is known, but why are we assuming lower volatility is better for an offense? Wouldn’t it be better to have a team that scores 4 runs in half of its games and 0 in the other half than a team that scores 2 runs in every game (assuming an average pitching staff)?

    Comment by mjmetro — June 17, 2013 @ 1:49 pm

  4. As a follow-up, isn’t it sort of a known that if two pitchers have equal ERA, the one with the higher volatility will be more effective?

    Comment by mjmetro — June 17, 2013 @ 1:51 pm

  5. That is indeed the big question. Trying to reason it out would be fruitless. I need to see what, if any, correlation there is to winning before I could care about it.
    A very rough eyeball comparison to winning and volatility in the team chart above doesn’t encourage me to think this is worthwhile.

    Comment by Baltar — June 17, 2013 @ 1:52 pm

  6. Here’s an earlier look, but there’s certainly more work to be done

    Comment by Bill Petti — June 17, 2013 @ 2:01 pm

  7. Nice, I actually remember this now. This is actually what I was going to suggest looking at :)

    Comment by mjmetro — June 17, 2013 @ 2:03 pm

  8. On a team level, the answer would obviously be 1/3 every day. Obviously 1/3 is high, but even if we took 1/4. Basically the team is losing 3 out of 4, and then winning a blowout. 1/4 from everyone every day, and some days the other pitcher might dodge that and only give up 0-2 runs, but that is a better result than the 0-fers.

    On an individual level, it just comes down to situation. One probably isn’t that much “better” than the other, as long as the hits come when they are beneficial.

    Comment by Steve — June 17, 2013 @ 2:16 pm

  9. Maybe this is an oversimplification but I think you can look at it like this. Two basic aspects to the game. Pitching and hitting. Both can be considered poor, average or good. Both can be considered inconsistent, somewhat consistent or very consistent.

    All told you have 18 different “terms” (ex. consistent average hitting). I think you then have to see how they matchup with each other to see what is best option for one aspect of the game, given the other. For example, if you have consistent poor pitching and an average offence, than you want that offence to be volatile to have any hope of winning more than you lose.

    Comment by MaxPower417 — June 17, 2013 @ 2:21 pm

  10. Is there any way to measure pitcher volatility?

    Comment by rahi321 — June 17, 2013 @ 4:22 pm

  11. Starling Marte at 81+ jumps out to me. If a player has been remarkably consistent at one point or another, will a prolonged slump not really affect the metric?

    Comment by frivoflava29 — June 17, 2013 @ 8:39 pm

  12. Interesting that there’s a total separation between AL and NL on the leaderboard

    Comment by Peter — June 17, 2013 @ 9:20 pm

  13. VOL doesn’t mean the results are good or bad, just that they’re consistent.

    Comment by Andrew — June 18, 2013 @ 12:12 am

  14. Day to day comparisons will accentuate volatility. I would think a larger sample set, e.g., rolling 10, 20, plate appearances, etc. would give a better measure.

    Comment by primi timpano — June 18, 2013 @ 12:19 am

  15. As a Braves fan, this is not at all surprising.

    Comment by Dan — June 18, 2013 @ 9:41 am

  16. I find this very interesting and have always wondered whether there is a way to take a measurement like this and use it better construct a lineup using the basic concept of diversification from portfolio theory. The thought stems from the idea that it seems that teams, rather than just players, are often inherently streaky and volatile. A ideal team therefore would want to minimize its volatility with the highest expected run output not have a bunch of low volatility players but have all highly volatile players, whose performance is lowly or negatively correlated to the other players (likely through other factors such as time of season, home/away etc)

    I’m very much a newbie at this stuff so I’m sure this concept has been well thought-out. I guess a very basic example of this occurs with right/left hand platoon splits but I’ve never seen any analysis that attempts to identify other factors that create volatility and could be used on a team-wide basis.

    Comment by Josh — June 26, 2013 @ 8:01 am

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