"Datacappers" vs. "Handicappers"

With the advent of micro-computing has come the ability for the sports handicapper to crunch numbers with far more information at his beck and call. Indeed, my own sideline is the ability to retroanalyze systems for handicappers, no matter how skilled or experienced they are. For the most part, the difference between the wannabes and the real pros are the amount of time they invest in honing their correlative skills, as well as intangibles that take a lot of development and insight into the particular sports, their knowledge of the principles (namely, players, but peripherally coaches), and finally, their own internalized intuition.

And then there is a new breed...the "Datacappers."

Armed with nothing but historical box score data and as much quantifiable figures they can get their megabytes on, the datacappers play with the numbers as much as possible, trying to eke out the elusive "key" that will trigger future winnings. ERA stats vs. OBP of batters; steals vs. slugging percentages; the datacappers scrutinizes data until they believe they have come up with a consistent theme. Using historical odds, they determine if they, indeed, have found the Holy Grail of the sports bettor: The consistent 56% aggregate winning percentage that doubles a bankroll, annually, with disciplined betting patterns, over a 9.09% vigorish amount.

As someone who is admittedly lax (hell, downright ignorant) in trying to identify the trends of using box score statistics, I'm nevertheless fascinated by the correlations that some of my clients bring to the table. Essentially, a datacapper is nothing but a "business rule" creator; someone who creates a formula based upon past performances. Now, sound analysis of past events is a must for any competent handicapper, but the difference between the two is this:

• A Datacapper makes his plays based strictly on the results of the data analysis and the ensuing formula answer
• A Handicapper uses the analysis as a baseline, then he makes his picks upon painstaking, intangible correlation between the past data and his own intuitive, fact-based experiences to craft a more substantial pick

Now, does this make Datacappers amateurs? No, not entirely. Many good handicappers use pen and paper, or at the most simple Excel spreadsheets, to chart their picks with no automation. But many handicappers use their own correlative skills to craft their selctions. However, such handicappers may be spending time on essentially trying to figure out, literally, by pencil and paper, how past data ties into the current event play.

So datacappers would have this information, literally instantly, at their beck and call. To that end, datacappers have hit upon one of a handicapper's biggest needs: a quantifiable data cruncher that funnels the pertinent data for analysis.

Where the datacapper remains an amateur is when he does no further research into the pick. A Handicapper would look at the data and correlate it with his own experiences, no matter if he gathered the data by computer or by hand. There may be injuries, players with personal problems, unique field dynamics, and a whole slew up unquantifiable data that play as much into the value of a bet as past performance trends.

So the bottom line: A datacapper is not a handicapper, and should never be considered a true handicapper. A handicapper may use an automated data service, but it is only the start of his selection process, not an end-all. And that is what separates the Handicapper from the Datacapper.