Between PPs, result charts, and wagering ticket summaries, the way that horse racing information has been presented to regular fans hasn’t changed very much over the years. In this post, I use data visualizations to try to increase comprehension of advanced wagering advice.

It was May of 2017 when, deep into the development of Handycapper, I took a break and browsed Twitter.

I saw a tweet from Darin Zoccali (@atTheTrack7) referencing a column he published at DRF.com titled, “Trust is a must or your handicapping game is a bust” (archive link).

In this column, Darin explained how a well-known wagering professional, @InsideThePylons (ITP), had called out inefficiencies and mistakes in the construction of Pick 4 tickets Darin had posted in late 2016. Darin reported that this advice had helped him wager smarter, increase churn, and win far more when his opinion was correct.

Intrigued, I wanted to find this conversation, and, with a little Twitter Search-fu, I was able to locate the Pick 4 in question.

As I tried to understand the finer points of ticket construction @InsideThePylons was making, I remember making a mental note that this kind of feedback would be a great candidate to potentially benefit from data visualizations to aid understanding, for the average racing fan, of the interaction between Darin and ITP.

dataviz

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