ClaimsNate Silver

“But that data doesn’t reveal very much, and its predictive power tends to be swamped by other indicators”

Nate Silver, editor in chief, writing on FiveThirtyEight 2015 Donald Trump Is Winning The Polls — And Losing The Nomination (FiveThirtyEight)

Factual Science and research methods

A pitcher's high school statistics do not reveal very much, and their predictive power tends to be swamped by other indicators.

Unresolvable The public record could not settle it.

Factual: Statements about the present or the past, checked against the record: did they hold up?

Said for an organisation they lead or work for; it counts on both records.

What would count as true or false

Judge this as of 2015 as a claim about baseball forecasting: that pitchers' high school statistics carry little predictive information and are outweighed by other indicators (such as college or minor-league stats, scouting and physical measures). True: sabermetric research or projection-system practice shows that high school pitching statistics have weak predictive value for professional performance and add little once other indicators are included. Mostly true: the data have some modest standalone value, but other indicators largely dominate. Mixed: the evidence is split, or high school stats keep meaningful independent value in some contexts. Mostly false: the data are shown to have substantial predictive power, and the claim only overstates real noisiness. False: the evidence shows high school stats are strong predictors that other indicators do not swamp.

Set before the research began.

Evidence (9)

  1. E1 Doctoring The Numbers: The Draft, Part Five | Baseball Prospectus Baseball Prospectus · 9 June 2005

    “The 15-year WARP value of high-school pitchers taken in the first round is less than half that of any other subset of draft picks.”
  2. E2 College pitchers the better bet ESPN.com (Keith Scherer, Baseball Prospectus analyst) · 28 May 2004

    “This new study confirmed what Bill James found a long time ago: college pitchers yield a much higher return on the investment than high schoolers.”
  3. E3 High School Arms and the #1 Pick FanGraphs · 5 June 2014

    “But look at much smaller differences in average WAR totals; there's hardly any difference at all for the top 10 and top 5 buckets.”
  4. E4 ESPN.com: MLB - Are high school pitchers worthy of being top picks? ESPN.com (John Sickels, Down on the Farm) · 1 January 2002

    “Well, you have to look at the same things you look for in any pitcher: velocity, command, mechanics, intellect, emotional maturity, workload history, overall athleticism.”
  5. E5 ESPN.com: MLB - Are high school pitchers worthy of being top picks? ESPN.com (John Sickels, Down on the Farm mailbag)

    “As you point out, many studies show that high school pitchers are bad bets in the first round. My colleague here at ESPN.com, Dave Schoenfield, recently wrote an article about this. There's no question that, over a long period of time, first-round high school pitchers have underperformed their college counterparts.”
  6. E6 ESPN.com: MLB - Are high school pitchers worthy of being top picks? ESPN.com (John Sickels, Down on the Farm mailbag)

    “I think what it boils down to is knowing the odds: the odds are stacked against first-round high school pitchers. They are also stacked against high school catchers, yet the Twins had no compunction about drafting Joe Mauer last year, and it is hard to fault their decision.”
  7. E7 The Old College Try | Baseball Prospectus Baseball Prospectus · 3 July 2026

    “High schoolers came in almost 17 points lower, at 35.1%.”
  8. E8 The Old College Try | Baseball Prospectus Baseball Prospectus · 3 July 2026

    “College arms averaged 1.71 and high schoolers averaged 1.50.”
  9. E9 Royals Review Laboratory: What minor league stats are the most predictive, Part I Royals Review · 9 July 2019

    “For this episode, we are just going to look at minor league pitching stats and 1) how that stat translates to major league stats and 2) how that stat predicts overall success, as measured by WAR.”

Reasoning

The evidence covers how high school pitchers turn out as draft picks: lower WARP for first-round high school arms (E1), better returns from college pitchers (E2, E5, E6), small differences at the very top picks (E3), and group averages from a later study (E7, E8). None of it tests whether a pitcher's high school statistics predict professional performance, or whether other indicators outweigh them. E4 says scouts judge high school pitchers on velocity, command and mechanics, but it gives no measure of how predictive the statistics are. E9 is about minor-league stats only, so the criteria cannot be settled.

Cite this claim

Nate Silver, “A pitcher's high school statistics do not reveal very much, and their predictive power tends to be swamped by other indicators.” (said 2015). Verdict: unresolvable. Reliability API, claim c_c864566cb2b0, method 0.1.0+28da144b, dataset release v1.1.2. https://epistacklabs.com/claims/c_c864566cb2b0

This claim is in dataset release v1.1.2, with the same verdict.

Reply to this claim

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  2. Resolved true Factual 9 October 2024
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  3. Resolved true Factual 9 October 2024
    “The recognition that the election is only four weeks away.”

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  4. Resolved true Factual 9 October 2024
    “And yet, there are dozens of polls released every week.”

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  5. Mostly true Factual 8 October 2024
    “This property is even more profound in baseball, where single-run leads are relatively durable because runs tend to come in bunches and the default outcome is not to score at all.”

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All of them

Verdicts are made automatically; how verdicts are made.