Last year Moneyball introduced statistical thinking for baseball to the masses. Now Wayne Winston and Jeff Sagarin are applying “numbers” to basketball in a way people will not expect:
This is the exact type of “thinking” that goes into trend following success.
Winston and Sagarin’s Winval system, used by the Dallas Mavericks, evaluates NBA players using a variation of hockey’s plus-minus statistic rather than traditional box score statistics like points, rebounds, and assists. The core question Winval answers is the same one Billy Beane was asking in baseball: does this player make the team more likely to win? Not does he score a lot of points. Not does he have impressive surface statistics. Does the team play better or worse when he is on the floor?
This produces counterintuitive findings. The players who score the most are not always the players who contribute the most to winning. A player who screens, takes charges, tips balls to teammates, and stays in front of his man makes contributions that never appear in box scores but show up clearly in the plus-minus calculation. Conversely, a player who scores 20 points per game but allows his defender to score 22 is a net negative despite the impressive scoring figure.
The parallel to trend following is the parallel the original page identifies. Conventional analysis in both sports and financial markets focuses on the most visible and easily measured metrics: batting average, P/E ratio, earnings growth, win-loss record, stock price momentum measured over arbitrary short windows. These metrics are not wrong. They are incomplete. They measure what is easy to measure rather than what actually predicts the outcome that matters.
Winval measures what matters: net points contributed. Trend following measures what matters: sustained price direction. Both approaches are dismissed by the establishment when first introduced because they challenge the metrics the establishment has always used. Both produce results that cannot be explained away once they accumulate. The Winval system shows that “the same players who do the most to help the Mavericks win sometimes score the fewest points and get the smallest number of rebounds” — exactly the kind of finding that changes how you think about measurement.
The resistance is also identical. Cuban “is often mocked for using Winval” and “people see it as some kind of threat to the old school way of thinking.” The trend follower with a 40% win rate is mocked by the analyst who wins 80% of his recommendations but loses money overall because his winners are small and his losers are large. In both cases the mockery comes from people evaluating the wrong metric. The correct metric is not win rate or scoring average. It is the outcome that matters: does the team win, and does the account grow?
Winston’s approach requires processing a 38,000-row spreadsheet of raw data before every Dallas game — the same kind of systematic, rigorous data processing that trend following requires. Neither approach relies on gut feel, conventional wisdom, or the opinions of respected authorities. Both rely on what the data actually shows about what actually works.
Frequently Asked Questions
Who are Wayne Winston and Jeff Sagarin and what is Winval?
Wayne Winston is a professor of decision sciences at Indiana University and a former Jeopardy champion. Jeff Sagarin is a sports statistician whose Sagarin Ratings have been used by the NCAA Tournament Selection Committee and the Bowl Championship Series. Together they developed Winval, an adjusted plus-minus rating system used by the Dallas Mavericks to evaluate NBA players based on how much better or worse the team plays when each player is on the floor, rather than on traditional box score statistics.
Why is the Winval approach similar to trend following thinking?
Both reject conventional metrics in favor of the measurement that actually predicts the outcome that matters. Winval rejects points and rebounds in favor of net team performance. Trend following rejects earnings forecasts and fundamental analysis in favor of price direction. Both produce counterintuitive findings. Both face institutional resistance from practitioners comfortable with established metrics. Both demonstrate through results that the unconventional measurement is more reliable than the conventional one.
What does the Moneyball movement in sports tell traders?
That institutions consistently measure the wrong things because they measure what is easy and traditional rather than what is predictive. When a rigorous analytical framework identifies better metrics, it produces consistent outperformance that the established methods cannot match. The resistance from scouts, coaches, and general managers mirrors the resistance from analysts and portfolio managers when systematic trading approaches challenge conventional investment wisdom. The pattern is identical because the underlying human psychology is identical.
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