I just updated the spreadsheet and found that our MLB plays are +45.76 dimes this season. This is on ALL the plays. Not interconference games, not our day games, not our double-plays, not our games of the week, not on Friday, not our underdog plays -- ALL the plays.
The SDQL gives such an advantage over the linesmakers because we don't just theorize -- for example -- about how a starter does when he had a WHIP of at least two in his last start. We actually check the results.
We don't theorize about how a starter performs in a revenge spot -- we know. We don't speculate about a team's performance in the rubber game of a three-game series -- we know.
We don't guess how the league performs as a dog in a home series opener when they are off a loss in which they stranded 20-plus runners. We have the numbers. We have hundreds of thousands of handicapping situations that are run EVERY night on our state-of-the-art computers.
We can find line value. We aren't fooled by randomness. We forecast a net profit of 60-90 dimes this season and we are +45 at the break. We see no reason why we will not equal or better this pace the rest of the season.
Dr. Ed Meyer *Physics PhD (Case Western Reserve) *Featured in New Yorker: “Brainiacs Build Money Machine!” *Certified SDQL Master!
Hi Doc, are you going to run a special for 2nd half of mlb?
I'm going to talk this over with Tom and see what we can do.
Thanks for the inquiry.
Awesome job this MLB season Ed. Keep up the great work and BOL in the 2nd half
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DR. with killer sports is amazing. Great work.
Just solid! Great 1st half Doc!
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Thank you for sharing your incredible work Dr. Meyer!! I have been fascinated with the SDQL but it's very intimidating, especially when some of your best queries have a few variables.
For example you wrote, "In his career, Alfredo Simon is 4-12 vs a team that has struck out an average of less than 7.3 times per game season-to-date. However, if he is not a dog more than 150 and the opponent has averaged at least 7.5 strikeouts per game season-to-date, he has never lost -- including a couple of starts as a member of the Orioles."
How do you come up with this query? Does it start by examining Simon, tweaking the strikeouts, then tweaking the opponent? Or do you have access to some sort of screener that finds the strongest trends and reports them to you? It seems many of your queries start with statistical outliers such as a bad game from a good player and look to bounce back. Do you ever work the opposite and look to fade bad momentum, creating a query such as "any team that has lost at least 5(maybe 6) / 8 games at any point in the season versus a starter with less than a 1.30 WHIP, or team who has averaged a certain amount of runs the last 8 games, or whatever."?
In the example above you compared a pitcher to a team who strikes out 7.3 and 7.5 times a game, and this looks a great query that can be used for every pitcher every day. Is there a way to create some sort of script that gives you a daily report for something like that? Are there any other favorite base queries that you use on a regular basis to start your exploration into the depths of the SDQL?
Dr. Meyers, thank you very much for your time and I understand if you don't want to answer any of those questions! I have to take full advantage of the opportunity to communicate with such a bright fella, do you know what I mean?! :)
Indeed, the SDQL can intimidating for complicated queries that involving averaging a team's stats, however there are a LOT of simple queries that can be profitable.
Tomorrow's NFL SDQL Query of the Day presents a good example. It should be up by 6:00 am EST tomorrow morning.
There are a series of six video lessons on how to use the SDQL to query simple situations available here:
Click on NFL in the menu bar and then click on NFL How-To. Each video is only a couple of minutes long. The first starts with the straightforward parameters H, A, F and D for home, away, favorite, and dog.
Indeed, the SDQL is not something that can be easily used to handicap from "ground zero." One way to use the SDQL is to already have a situation that you want to investigate. For example, how do the Cardinals do in the third game of a three game home series that is tied at one game each?
Another is to perform data-mining. Our computers do this every morning. They run about 500,000 thousand handicapping situations and then rank them from top to bottom (by p-value) and then group them by match-up. So, for example, when I look at the Red Sox and Royals match-up for Friday, I usually have about 10-20 active systems and about 100 trends for each team. Some are play on, some are play-against. By clicking on the trend link, I can view the complete game listing for the trend and by clicking on any game in the listing, I can look at the box score. Sometime, I investigate the trend further by expanding the search parameters or by looking at the opposite site of the trend.
For example, in the Alfredo Simon trend, there is a dichotomy and that, to me, makes the trend more valuable. If Simon was also good vs a team that didn't strike out much, then it wouldn't really be a trend that could provide line value.
So, yes, we have a daily report.
Also, we have a special set of saved trends in our "My MLB Trends" file. These are trends and systems that we find valuable. We start every handicapping day with this set.
Anyone can have their own personal saved trend file. These are run automatically very early every morning. When a trend is active for today's action, it will appear in the active trend listing.
There is a video on how to save trends at:
click on "Special How-Tos" in the menu bar.