Moneyball. baseball and Stock Markets
We have all seen the movie MoneyBall.
Its one of my favorite movies and this blog dwells deeper into its origin and a possible parallel with stock markets.
Bill James — The Baseball Abstract (1977–1988)
In 1977, Bill James self-published 1977 Baseball Abstract: Featuring 18 Categories of Statistical Information That You Just Can’t Find Anywhere Else — 68 pages held together with staples, sold for $3.50. By 1982, Ballantine Books was publishing it annually. James named his method “Sabermetrics” after SABR (the Society for American Baseball Research). Awesomestories
His core argument: the way players are evaluated is inherently wrong. Instead of focusing on speed, power, and hitting, coaches should look for players who can “run bases” — as this is what ultimately wins games. B.BIAS
His key formula was Runs Created: RC = (Hits + Walks) × Total Bases ÷ At-Bats — an attempt to estimate how many runs a hitter actually contributes to his team. Wikipedia
2. What Billy Beane Actually Did
Instead of relying on gut instinct and traditional metrics, Beane began selecting players based on two previously overlooked statistics: on-base percentage (OBP) and slugging percentage. Together these form OPS. Gri
Beane believed that power could be developed, but patience at the plate and the ability to get on base could not. He also preferred college players over high school phenoms who needed development. The Sport Journal
3. The Book That Framed It All
Michael Lewis’s Moneyball: The Art of Winning an Unfair Game (2003) documented this. The noted “Moneyball” Oakland A’s team of 2002 went on to win 20 consecutive games, and the approach gained national recognition when Lewis published his book detailing Beane’s use of advanced metrics. Wikipedia
The Stock Market Equivalent
The analogy holds up remarkably well. The core Moneyball idea — market participants systematically misprice assets using the wrong metrics; use better metrics to find undervalued ones — maps directly onto established investment frameworks.
The closest direct parallel is Joel Greenblatt’s Magic Formula:
Magic formula investing is an investment technique outlined by Joel Greenblatt that uses the principles of value investing — specifically identifying “cheap and good companies” with a high earnings yield and a high return on invested capital (ROIC). Wikipedia
The strategy involves ranking stocks based on these two criteria, then buying 20–30 of the highest-ranked stocks and regularly rebalancing. Greenblatt achieved 40% annualized returns since Gotham Capital’s inception in 1985. StableBread
When Greenblatt backtested his formula on the 3,500 largest U.S. stocks (excluding utilities and financials), the top 30 stocks generated an annualized return of 30.8% from 1988 through 2004, versus 12.4% for the S&P 500. fool
The academic underpinning is Fama-French (1992):
Fama and French (1992) argued that value stocks outperform growth stocks, and that the reason is higher risk of value stocks. Lakonishok et al. (1994) countered that the value premium arises because the market undervalues distressed stocks and overvalues growth stocks — when mispricing corrects, value stocks produce high returns.
Where the Analogy Breaks Down
Baseball has a closed, stable statistical universe — the rules don’t change, the metrics are observable, and “winning” is unambiguous. Markets are different:
- Once a pricing anomaly is widely known, arbitrage closes it. Moneyball stopped working in baseball once all teams adopted OBP/OPS — the same happens in markets.
- Stock prices are set by participants who can learn and adapt; a baseball player’s OBP doesn’t change because scouts now measure it.
- Greenblatt’s own backtest is now 20+ years old, and the spread between the Magic Formula and the S&P 500 has narrowed as the strategy became widely followed.
The original Moneyball insight — the market (for players, for stocks) is using the wrong scorecard — is valid and has been repeatedly demonstrated. The harder problem is that acting on it at scale closes the gap.
