The Geeks Shall Inherit the Water

blog-geeks02.jpg

We’re 50 years into the history of B.A.S.S., a portion of the way into the 13th season of the Elite Series, and 17 years past the cancellation of “Freaks and Geeks” and we still aren’t able to apply anything meaningful from the world of statistics unto professional bass fishing.

Part of that is likely due to sample size. Over the circuit’s history, the Elites have held eight to 11 regular season events annually, and only a fraction of each event’s happenings are viewed or recorded, so there’s not a lot of meat to work with. If you want to provide any meaningful statistical information about how a particular pro does in the spring on tidal waters, or in late fall or highland reservoirs, you may have more noise than signal. 

Even on waterways that B.A.S.S. visits comparatively frequently, the finishes themselves don’t tell us much. Keith Combs would be a safe bet to win on any East Texas waterway at just about any time of year (the hardware on his mantel bears this out), yet in four Bassmaster visits to Toledo Bend he’s finished 78th, 20th, 4th and 42nd. What do we learn from those numbers on a page? Nothing. By contrast, an everyday Major League Baseball player may have 600 plate appearances in a year – divided among lefties/righties, day/night, home/away and all sorts of other factors – there’s simply a lot more opportunity to suss out trends and tendencies. 

Furthermore, we simply have fewer “measurables” than the sports that to date have lent themselves to statistical analysis. Football players have the 40 yard dash, the bench press and yards per pass. Basketball players have vertical leap and free throw percentage. Baseball players can be quantified and thin-sliced in seemingly endless manners. When you’re going after a quarry with a brain – albeit a pea-sized one – what constitutes efficiency is up for grabs. Just because you can skip a jig 200 yards under a kneeling grasshopper doesn’t mean you’re going to win every jig-dominated event. The angler who catches a fish on every other cast can still come in with 6 pounds while the one who only gets five bites in an eight hour day can quadruple that. Is 12 pounds a day over three days any better than two 16 pound days and a 4 pound follow-up?

The few statistical efforts I’ve seen have focused on essentially meaningless facts like batting averages based on potential limit fish (i.e., 2 fish out of 5 equals .400, 4 fish out of 5 equals .800). What we need is not only a mathlete capable of crunching the numbers, but also one with the understanding and wisdom to tell us what numbers we need to crunch. In other words, what stats, if any, would help us better understand the game? Is it knowing who is most consistent, or who tends to bounce back most often from a bad first day with a strong second day? Much of that may depend on your definition of success – one angler may prefer a win and a string of 90th place finishes to a sequence of 40th place checks, while another might choose the opposite. Nevertheless, even recognizing those distinctions, in the age of GoPros and BASS Trakk we are on the cusp of being able to find meaningful measurables. 

Where are we going to find the person to accept this task?

I doubt that there is anyone already within our industry with the smarts, training and objectivity to get it done.

There are, however, thousands of graduate student sports fans looking to make their mark on the industry and become the next Billy Beane, Theo Epstein or Daryl Morey. 

Every year the established hammers in the field of sports analytics gather in Boston at the Massachusetts Institute of Technology for the Sloan Sports Analytics Conference where they discuss a wide variety of topics – some accessible to casual sports fans, others less so – about the intersection of data and sports. As they stroll the halls, they can’t roll their twenty-sided dice without hitting someone wielding a resume who wants to take their job. I’m sure that relatively few of them care or know about pro bass fishing. Most are there looking to get a foot in the door with the Yankees or the Patriots or the Mavericks. Some of them will achieve that goal, and some subset of that group will work their way up the ladder until they are the ones speaking at this sort of conference.

I know that working in the big leagues is the brass ring for many of them, and maybe the direct route is the best route. On the other hand, as one of 20 or 50 interns, it’s hard to distinguish yourself. You might even end up as a glorified coffee boy. On the other hand, if someone were to come to B.A.S.S. with even a rudimentary understanding of how pro fishing works, build a far-reaching database of relevant information, and then assemble the architecture of a significant and predictive statistical model, that would distinguish them. It might even provide an express route to the top of the food chain at their preferred league.

It would be a win-win. This is one situation where a newcomer could literally invent the wheel and make a long-term mark while forging new territory. Meanwhile, we would have a better sense of what we’re looking at, and some indication of which numbers are most crunchable.