
PICK SIXTY SPORTS BETTING ADVICE + SDQL TRENDS
SDQL Sports Betting News You Can Use!
SDQL Sports Betting News You Can Use!
PICK SIXTY SPORTS is an online information source for stories, picks and systems backed by SDQL research. Jarvis Simes is the lead handicapper at Pick Sixty and can be reached on Twitter or IG if you have any sports betting related questions.
I am a handicapper, just like you, and we all face the everyday challenge of trying to beat the bookmaker's number and make a profit. SDQL is the ultimate tool for this task, and with my winning systems, you'll learn how to attack matchups with advanced handicapping techniques that allow you to think outside the box.
My league-wide systems focus on statistical averages, time of year, previous season results, and the current setup for each team. The goal is to find line value vs. public opinion. Remember, the book sets a line to try and attract balanced action that guarantees them a profit. Lopsided betting toward one side or total is often going to be what triggers the opportunity for value.
My systems include a brief explanation, alerts for potentially "live" plays, and tips on how to write advanced SDQL codes. Whenever I book an actual play for the matchups listed, it will be available on the Pick Sixty site or Twitter feed.
Enjoy these betting profiles, save them for future use, and feel free to contact me @PickSixtySports with any questions.
Jarvis has been betting on sports for over 20 years, writing for dozens of publications, including the Killer Sports NFL weekly, loaded with SDQL trends and sports betting advice.
Christie inspires my social platform and what this site will eventually become. Part-time consultant, full-time awesome!
KC came to us from a marketing team in the K-Dub region. Optimization, planning, and finances are her specialties.
Copyright © 2023 Pick Sixty Sports - All Rights Reserved.
Powered by GoDaddy
We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.