Public Favorites Crush in Game 1 of the NCAAB Season
Yesterday, I wrote about how ranked teams do very well against the spread early in the season. The rest of the year, they cover less than 49% of the time.
I decided to do a bit more digging, though, and found something rather groundbreaking. Something that the team at Sports Insights would find cringe-worthy.
Public favorites absolutely destroy in the first game of the season.
Generally speaking, we love going against teams like this. If you’ve followed us for any span of time, you’d know that we advise taking a contrarian approach and betting against the public. We have plenty of data to back up how good of a strategy this is and it’s why we’ve been so successful over the years.
However, just like ball don’t lie in the NBA, data don’t lie in sports betting. Although it hurts to admit, betting with the public over the next couple of days is a good idea.
Dating back to the 2005-06 season, favorites getting 65% of bets or more in Game 1 have gone 446-330 ATS, covering nearly 57% of the time and providing over a 10% return on investment.
If we look at favorites getting 65% of bets by game number, we’ll see that this really sticks out. For the majority of the season, teams like this are rather unprofitable. Meanwhile, they’ve won over 80 units in game one since 2005.
So why does this happen? I’m basically saying the same thing that I did yesterday, but I think the biggest reasons are that teams are trying to make a statement and that non-conference games give favorites the edge.
Favorites aren’t going to just try and win in the first game of the year, they want to win in a blowout. Start the season out on the right foot and make a statement, you know what I’m sayin? Put some fear into their upcoming opponents and conference rivals.
When it comes to games against conference or non-conference opponents, it’s very clear that public favorites do much better against seldom seen non-conference foes.
Teams that play each other every season become very familiar with their respective styles of play, which favors the underdog. Most non-conference games feature two teams that essentially never play each other, which favors the…favorite.
For all you squares out there, savor this while you can. I don’t think you’ll see another article advocating trendy favorites for a long time.
Anthony C
11/09/2017 at 2:37 pmI’ve noticed that. My theory says that giving squares easy wins out the gate, gets them in the betting mood along with joy their sport is back. They bet bigger after a couple wins and books get their money back as always. It’s an ivestment in the people who make betting possible.
James
11/10/2017 at 1:09 amGlad I caught this article. I was getting excited for the addition of NCAAB on the board. Saved me from what could be a potential negative start. Laying off the contrarian bet signals (if any) for day 1. Barring the occasional rogue season, 5dimes signals and contrarian signals have been kind to me. Just usually wait until the 5dimes starts hovering around the +10 unit mark to start the grind.
J Mac
11/11/2017 at 5:45 amWell Mark, unfortunately data sometimes lies…well only when its incomplete, incorrect or not properly filtered. As you now know, this system went 11-19 (36.7%) for game 1 this Friday (11/10-2017). A closer look at the games that the “game 1”, “fav” and “spread % > 66%” filters gives you (and what you based this system on), you’ll notice that a good portion are not from “opening day” (i.e. the first Friday of NCAABB). Some included games were played as late as Feb and Mar lol. Going through and choosing just the first Friday of each season, using the custom date range, gives you a win % of around 55.3% (144-116-5 since 2006. In 2005 there were as many games played before Friday as on Friday for this filter) for favs, with the last two seasons being 50% or below (11/13/15 was 16-19). Adding the latest data from yesterday brings the system to 53.4%. This is strictly looking at the data returned by the betlab filter of game1, fav and above 66% spread for the first Friday of each season with lined games. So naturally this hinges directly on the validity of said data, which I have already voiced my concerns about with Travis.