The annual Jockey Club Roundtable was recently held in Saratoga Springs, NY.  Presentations covered a potpourri of topics relevant to horse racing, but one stood out in terms of its value.  In fact, of all of the recommendations that I’ve seen at The Jockey Club Roundtable, past and present, the one by Ben Vonwiller of McKinsey & Company has the most potential to provide an immediate catalyst to boost stagnant betting handle.  (You can watch and read Mr. Vonwiller’s entire presentation on The Jockey Club website.)

Basically, the hypothesis McKinsey researchers tested was “if you maximize the share of attention bettors can focus on any one race, they will bet more often.”  This seems logical enough in that if several high-profile races have almost identical post times, bettors won’t wager as much as if the races do not have overlapping post times.

In order to test the hypothesis and to put some mathematical precision to the notion that non-overlapping post times have a salutary effect on handle, McKinsey developed a multiple regression model (using 40,000 races in 2015) with seven (independent) variables that were able to explain 73% (coefficient of determination or R2) of the variance in the dependent variable betting handle.  This is an excellent outcome from a statistical perspective.

Six of the independent or predictor variables (or variants thereof) have been used by previous researchers, so the McKinsey research offered nothing new in this regard:

  • Field size
  • Purse size
  • Track
  • Race type
  • Grade I at track that day
  • Exotic wagers

What makes the McKinsey research distinctive is the seventh independent variable, “Concurrent purse,” which is a very creative proxy for the share of attention that bettors can give to a race.  This concept is operationally defined as “The share of the total aggregate purse represented by each race in any given time period.”

Mr. Vonwiller explained: “We took a race, we took the sum of that race’s purse and then all of the purses that were represented by races that had off times [post times] within five minutes of that race.  So that is the total available aggregate purse.  Then we asked how much or what share of that aggregate purse did our race represent.  If it had 100% share of concurrent purse, it meant it was the ony race running in that time slot.  If there were two races with the same purse size, you’d have a 50% share of concurrent purse for that race.”

He summed up the projected increase from better scheduling of races between and among racetracks: “Our model predicts a $400 million increase in handle across the industry from better scheduling by de-duplicating races.”  This assumes industry-wide cooperation.  However, if only the top-five racetracks (based on handle) cooperated, the predicted increase would still be $150 million.

The McKinsey report was careful to identify and discuss five objections that racetracks might raise about coordinated race scheduling, which you can read in Mr. Vonwiller’s presentation.

I have some technical statistical questions about the independent variables in the McKinsey model that I would want to know the answers to before buying into the $400 million and $150 million projections, but these are too esoteric to delve into here.

It may be that the response by handle from better scheduling among racetracks would turn out to be curvilinear rather than linear, with handle increasing at a declining rate of change, which would reduce the magnitude of the increases in handle predicted by the model.  Yet, it is a good bet that handle will meaningfully go up with more skillful race scheduling.  And it is not a zero-sum outcome in which some racetracks win at the expense of others.  Every track should accrue additional handle from optimizing bettors’ “share of attention” on showcase-type races.

In my view, The Jockey Club and Mckinsey & Company have offered manifestly actionable empirically-based race-scheduling tactics that racetracks have a compelling incentive to implement sooner rather than later.

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