Sunday, Feb 9th — Late
Bye Week:
49ers
Bears
Bengals
Bills
Broncos
Browns
Buccaneers
Cardinals
Chargers
Colts
Commanders
Cowboys
Dolphins
Falcons
Giants
Jaguars
Jets
Lions
Packers
Panthers
Patriots
Raiders
Rams
Ravens
Saints
Seahawks
Steelers
Texans
Titans
Vikings

Willing To Lose 12.23

Larejo is a mid-stakes tournament mastermind who specializes in outmaneuvering 150-max players with a small number of entries

In 2013, while getting my MBA in marketing at an institution in New York City, I signed up for an Analytics Boot Camp. This was an accelerated, two-month course focused on diving into different areas of analytics, some related to data collection, visualization, and so on. The first few weeks were more boring than I had anticipated. There were a lot of do this, now do that, and then click here and see what happens. Naturally, we spent a ton of time on Microsoft Excel and other basic programs. But nothing was really catching my interest. Until we had two or three of the night classes with a specific focus on predictive analytics. Predicting the future, yes!

I was so enthused about these. I sat in the first row and took copious notes as we dove into more advanced programs like MySQL, R, and spent some time programming in Python. We were performing very basic tasks compared to what many can do with these tools but we were practicing advanced analytics and crunching data to predict patterns, outputs, and solutions to problems. I thought this was the start of my data science career. But then, after many hours, and some practice on my own, I realized the limitations of data. Here I was about a decade ago, thinking if we have all the data, and we put it all into one system or application, then it’s always going to give us a result we can trust. But then we (rightfully so) as a class started realizing why data can only do so much for us, and most of my excitement turned into skepticism. No matter how much data you have, and how well-crafted your story with said data can be, there will always be a limitation. The complexities and unlimited variables that exist in our world are the reason why.

Data can only really account for the past. It’s the best it can do. We can make very confident guesses in a data story or visualization that can show us what should happen next. Or, in a football context, what the best matchups are, where the right game environments lie, and how some players and teams should experience regression, good or bad. But we don’t know what can happen tomorrow until tomorrow happens. And here I was thinking I could make all this money with super sharp predictions on sports 10 years ago. I’ve done just fine, and the professor from this course was nothing short of a master, but I still want my money back from the boot camp.

I am not a quant. I try not to try to be one, but I do try to always understand and consider data. I try to make sure it’s a part of any story I tell because it’s the best we have at our disposal. But always, always try to incorporate the non-quantifiable part of your brain. Everything that succeeds has balance, and DFS is no different. You can be the best at any one category of sports predictions but if you fail to recognize other categories, you’ll be in trouble. Consider all angles, tell a story on your rosters at all times, and as long as you back up your “whys” for building those rosters, you’ll win in due time.

Josh Jacobs

Anytime you see a player at their cheapest price all season, count me in ($6,700 on DK). In Jacobs’ case, he has the added benefit of his head coach saying publicly he’d like to give him 20 carries as well. The Chiefs defense is a tough matchup overall for the Raiders offense, but if they have a vulnerability, it’s via the run (28th DVOA in this department). PFF has this matchup (Raiders offensive line vs. Chiefs defense) ranked as the tied for third-best rushing matchup on the week, trailing Atlanta, Indy, and tied with Philadelphia. Many will be reluctant to roster Jacobs because of the spread on this game, with Vegas as heavy underdogs. However, despite not topping two catches since October 9th, let’s not forget Jacobs’ Week 4 performance through the air with 8/81 on 11 targets with Aidan O’Connell starting against the Chargers. His pass game role has ceased to exist lately, but it’s in there somewhere. As long as his snap rate is consistent, the game script doesn’t matter.

The Chiefs defense showed they could clamp down on opposing wide receivers yet again last week with their stifling performance against AJ Brown, so it’s possible they come in with a similar game plan against Davante Adams. The question of whether they do this comes down to whether the Chiefs felt that strategy against Brown and the Eagles was effective. By focusing on Brown, they allowed production via the ground by Jalen Hurts and D’Andre Swift and ultimately lost the game. However, Hurts underperformed without Brown doing much, and the Chiefs know they would have won this game if Valdes-Scantling brought in the deep ball late. So, in hindsight, I think it’s likely they shift to neutralize Adams here, let Jacobs work underneath (maybe Meyers too is sneaky), and take their chances against O’Connell.

Josh Allen + James Cook + Gabriel Davis + AJ Brown

<< 90% OFF!!! >>

Don’t play DFS without it!

Use code OWS90