It may be counterintuitive, but learning something new doesn’t always equate to handicapping growth. With so much good data available these days, one has to be wary of information overload.
Call it the “paralysis by analysis syndrome,” or the point where too much information because confusion.
This flies in the face of what I’ve always believed; that horseplayers need to become specialists, carving out their own niche to secure profits. While that approach is still valid, a decline in fan base and pool liquidity makes it almost mandatory that today’s players be well-rounded.
Call it the “new millennium’s gateway to value.”
Today’s smart money might be nothing more than an overwhelming statistical trend that, when coupled with other handicapping criteria, paints a picture that begs for a wager on one particular horse—or a profitable trainer pattern.
The advent of the Saratoga and Del Mar race meets traditionally has been a time when handicappers realize that nothing less than a full handicapping arsenal will suffice.
Professionals are not immune to this and when possible try to stay ahead of the curve by welcoming new handicapping methodology based on unique data or evidenced-based understanding of traditional handicapping precepts.
I first became aware of the methodology in 2009 via “Trackfacts” producer Tom Amello and co-host Nick Kling on the Capital OTB television network soon after Racing Flow was founded.
Interesting concept, I thought, but since I didn’t view my own handicapping approach as being broken, I had no incentive to attempt fixing it. Besides, who wants to work harder, longer? However, five years is an eternity in a horseplayer’s life.
The trainer statistics that I had become reliant upon for a decade suddenly were everywhere. A good set of performance speed figures did not provide the edge it once did; everyone has a good idea who the fastest horse is these days.
And with the burgeoning popularity of Internet wagering with Advance Deposit Wagering, race replays are now readily available at the speed of a keystroke, the value once provided by sophisticated trip handicapping was disappearing fast. The time had come for the next big thing.
Competing ADWs are providing their bettors with the latest in cutting-edge data. So with more wagering being done online, horseplayers can stay in their living rooms which yields more time for additional research.
Racing Flow, as developed by co-founders Jake Jacobs and Phil Gregoire, adds an important scientific component to the art of trip handicapping by measuring how the combination of track bias and race shape can determine future performance.
Racing Flow figures are not the final piece of the handicapping puzzle, nor were they meant to be, but they add a dynamic that can lead to legitimate overlays because the apparent bad running lines was a matter of racing atmospherics and not poor form.
In short, Flow figures indicate whether the shape of a particular race favored speed horses or closers; not a measure of how fast horses run, but how they run fast. Bias figures indicate whether a particular day's running surface favored speed or closers.
At the conclusion of each racing day, Racing Flow compares model-predicted and actual degrees of closing to determine whether a particular surface, on a particular day, has favored speed versus closers.
Bias figures indicate whether a surface favored speed or closers. A Bias Figure is issued when five or more dirt/synthetic races, or five or more turf races were run on a race card and there was no important change in track condition that day.
The combining of these Flow and Bias figures produces a Closer Favorability Ratio. On a scale of 0 to 100, the CFR ranks races from "most speed favoring" to "toughest on speed." A CFR of 1 ranks that race in the top one percentile in speed-favoring terms; conversely a 99 would indicate a strong closer’s bias.
The final piece of Racing Flow methodology is called a BL 12. According to the definition in Racing Flow’s comprehensive online overview and tutorial, the BL 12 simply is the number of lengths the race winner was behind the leader at the first two points of call; the opening quarter-mile and the half-mile. Knowing how much ground a winner makes up in the later stages yields a clearer picture of prevailing race dynamics.
Racing Flow uses well-crafted statistical models containing up to 17 independent variables to determine the probability a given race will be won wire-to-wire, by a stalker, or by a closer. The degree of rallying is based on the number of runners passed between each point of call and the trips of the top 3 finishers.
Predictive variables include final race time, race distance, field size, track condition, and relative speed of each split. Each unique distance and surface is considered separately, because the optimal fractions for speed versus closers differ from course to course.
Different packages at different price points for various durations are available to Racing Flow clients. Included in the entire package is a Track Bias Report, a Flow + Bias Report, an Upgrade/Downgrade Report (includes three major tracks running that day) and an Extreme Race Report.
The latter identifies a race or series of races that were exceptionally kind to speed or closers. The most memorable example of the Extreme Report is 2005 Kentucky Derby winner Giacomo, which moved from extreme speed-favoring scenarios to an extreme closer-favoring scenario. From a Racing Flow perspective, the running lines were not as bad as it looked on paper.
Racing Flow figures are derived from a database of North American races run since 2003. Updated daily, the database covers all major venues in New York, Kentucky, South Florida, California and Illinois. Coverage of races from Fair Grounds, Monmouth, Oaklawn and Woodbine is also available.
“Plodboys” Phil and Jake have been sending me the last two weeks of reports and I consulted the Upgrade/Downgrade report the past two Saturdays. The results were very good, which is to say profitable.
The U/D Report is their interpretation of the figures. It’s not a selection sheet but identifies runners that have been doing better than it may appear on paper. This past Saturday at Belmont Park, after a few disappointing results came two that would make any bettor’s day.
The 6th race contained two Upgrades: the extremely impressive Mentor Care combined with Tiz for Tat to complete the exacta, dovetailing nicely into the 7th race which contained three Upgrades. Capetown Devil won at 13-1 and combined with 9-1 place finisher Mop Head for a $308.50 exacta.
Sunday’s Belmont Park feature race, the Diamondella Stakes, contained three Upgrades and one Downgrade in a field reduced to six by late scratches.
I couldn’t decide between two potential price shots in the open turf sprint. I reasoned that the likely pace scenario would compromise deep closing Magnificent Shirl but would be kind to Effie Trinket. The HRI faithful were rewarded with an $11.60 mutuel.
Needless to say, Racing Flow data is now part of my handicapping arsenal. For those wanting to read more about it, visit .