All
Beyer-like speed figures have a foundation of a theoretical class-par-time
hierarchy. As described last week, simply listing the classes of races
at a track in ascending order of speed is no easy trick. Somehow, bending
and fudging times in fifths of seconds for Thoroughbreds seemed less
of a problem than doing the same with decimal times, so it took a run
at Quarter Horses to make me blink and realize that, if the Emperor
wasn’t totally naked, he was at least in a G-string, and it wasn’t a
pretty sight.
Since
I suggested that a good alternative to The Beyers is to make your own
Beyers, the G-string is important. That is the thread of truth that
ties all this together. Beyer figures are pretty good—certainly the
best speed figures that have been published for the world at large.
But, since everyone has them, the question becomes can you do better?
Eventually,
I’ll explain an alternative way to calculate and compare speeds in horse
racing, but to understand the crowd’s Beyers, you can’t beat experimenting
with the steps that are used to create them.
I
am an unabashed Beyer fan for a number of reasons, the main one being
the level of journalism he brought to this sport—another is the fact
that in his approach to making speed figures, there are no magical numerical
factors; he derives and describes every step. The only cockroach in
the salad is that underlying all of this is the 1960’s man-to-the-moon
belief that the universe—and horses’ times—are orderly.
Pick
a track, any track. Get a stack of Forms or other data source
from last season. Paying no attention to times or surface, simply make
a list of every class of race run at that track. At cheaper tracks,
the list will be relatively short. There may be no graded races at
all, and claiming and allowance conditions may be straightforward and
simple.
At
other tracks, depending upon the inclination of the managers and/or
Racing Secretary, conditions can be very complicated, and very situational,
sometimes written for a particular handful of horses the Secretary knows
is in the barns. After you have written down every different set of
conditions for races at the track, put them in order from “highest class”
to “lowest class.”
Right
here you run straight into the oldest debate in horse racing: what
is “class,” and “is class speed?” If you ignore times and deal
only with race conditions, there are still numerous internal decisions
to make, even at a cheap track. Is an Allowance $4,200 N1 higher or
lower than a Clm $5,000 N2? Is purse value the common denominator of
all racing?
As
someone who used to haul friends' losing horses to the track to run
in Allowance races because they were pets, I can testify that the Allowance
classes are not automatically listed above Claiming at the same or similar
purse values.
If
you make the list and end up with something like last week’s tables
for the entire track, the traditional next step is to make a table for
each distance (separating dirt and turf), and go back through the race
results, marking down final times run within each class. This is where
you start “fudging.” You’ve decided that the Allowance class above
is higher than the $5K Clm, but there are only three Allowance times
to average for 7 furlongs on the turf and none for the $5K Claimers—so
what do you do? You make up a time that is appropriately
lower.
As
I said early on, the great value of the original Beyer approach was
that is was do-it-yourself. If you did it, you could not help but learn
a great deal about times and running conditions at a track. It is hard
to separate which is more valuable to your ultimate profit—the learning—or
the figures. If you are going to do this, I’d suggest a couple of steps
to make the figures more valuable.
First,
do not make a blanket class hierarchy for track and then apply it to
each dirt and turf distance, making up numbers to fill unraced classes
or changing numbers to fit preconceived notions. Instead, use a spreadsheet.
(If you are reading this on the Internet, you almost certainly have
one.)
Make
a heading for each dirt and turf distance, and under it—without worrying
about class order—list only the classes of races run at that distance
and surface. Enter every time recorded on a fast track for that class
and distance, and write a little formula to average them in the last
column. Most spreadsheets have built-in formulas, which make this very
easy.
This
may sound like a bigger task than you want to bite off—and doing an
entire track history is work—but if you want to have an interesting
hour or so, try it for just a couple of moderately run distances at
one of your favorite tracks.
Your
spreadsheet should look something like this (abbreviated for space and
not all classes and times shown):
Distance:
5.5 Furlongs Surface: Dirt
One
of the first things you should notice while entering numbers, even in
small samples, is that times within the classes overlap. You
will also find that for many cases, only a few classes actually run
the distance, and when they do, there may be only a small number
of races each season.
In
all situations, wild-flyer times (fast or slow) are not uncommon. The
conventional wisdom is to throw out flyers, but the computer doesn’t
know that and, for this exercise, let the chips fall where they may—leave
them in.
Now,
for the moment of truth. This was very difficult to visualize with
the pencil-and-paper technology that originated these methods, but it
just takes a couple of clicks of a mouse button now: Sort the table
by the "average time" column.
Sometimes
sorting from fastest to slowest times will rearrange the rows such that
“Class” makes pretty good sense. At least as often, the order
of “Class” will be almost as garbled as it was at random to begin with.
Most often, there will be a general trend that the highest Class will
be faster than the rock-bottom lowest Class—with a bizarre mix of classes
in between.
If
you want to take this beyond just an interesting exercise and actually
make the foundation class-pars for improving upon the method, the next
step is to break with tradition and either lump classes, or accept an
unconventional hierarchy.
Suppose
“Maiden Special Weight” turns up the fastest class on the track at some
seldom-run distance? Should you throw out the data and give it an artificial
time to force it into the hierarchy pattern for the track as a whole?
Two factors could be operating to make it appear the fastest class.
First of all, maybe it is the fastest class. Some tracks may
run hotly contested short-distance races for two-year-olds early in
the season, and only a few races at that distance for plugs that can’t
stand up a full 6 furlongs. OR, it could be a function of pure
flukes and flyers. (Understand that these are not just rhetorical questions
for making your own numbers—they are built into the speed figures fed
to the public.)
If
you can recognize a true pattern like the first example, or the absence
of a true pattern, like the second, you will make better speed figures
and variants if you follow the advice of Tommy Chong and "...go
with it." Let the upside-down classes stand—or, if there is
no valid pattern, lump them into several, or even one group, and simply
use one or two times as pars for the distance. This creates a very
complicated scheme for comparing speed figures across distances, but
it can be done.
The
approach that I use makes all of these issues moot, but the purpose
here is to understand the published figures the public is using, and
understand where art and errors can enter—as well as how you might do
better on your own if you wish.