A recent Wall Street
Journal article features a Credit Suisse study that measures the usefulness
of three common financial stats– sales growth, net income growth, and gross
profitability— and compares these standard business metrics to three baseball
metrics for hitting (batting average, the strikeout rate, and the somewhat more
esoteric “on-base percentage plus slugging percentage”).
The finding is a bit shocking: the three common financial stats are far less helpful than some of those used in baseball.
What makes a
statistic useful? Its persistence and predictive value. As summarized by WSJ, “a
statistic is persistent if it is correlated with what happened in the past.
It’s predictive if, as the word suggests, the stat is successful at predicting
outcomes.”
Turning to college football, here are the biggest buyouts of
college football coaches: Charlie Weis, Notre Dame ($18.9 million not to coach);
Bo Pelini Nebraska ($7.9 million not to coach); Gene Chizek Auburn ($7.5
million not to coach); Will Muschamp Florida ($6.3 million not to coach); Charlie
Weis Kansas ($5.625 million) (double dipper); and Jeff Tedford Cal ($5.5
million). The list of million-dollar buyouts goes on, but the point is that ADs
probably make hiring decisions based on short-term, shallow, and non-empirical “hunches”
about coaching hires. Common approaches,
with mixed results: NFL to college; OC/DC at elite school; MAC champ to Big Ten.
But what if someone studied in-depth the data that has the
most persistent and predictive value for successful college coaches, like Credit
Suisse? You might measure entirely different things, such Nick Saban’s
obsessive detail to focusing short-term on executing minute goals that stack up
to big success. Quoting Saban: "Don't think about
winning the SEC Championship. Don't think about the national championship.
Think about what you needed to do in this drill, on this play, in this moment.
That's the process: Let's think about what we can do today, the task at hand."
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