2023/24 Week 8 Betting Report

Week eight of the NHL season has been logged into the history books and my slump continued Monday to Friday, performing better on the weekend but still finishing the week in the red. Each bad performance only motivates improvement, digging deeper into the numbers and doing a numerical autopsy to ensure that structural mistakes are eliminated. I’m tracking so many more numbers than I’m even looking at on a daily basis. Like my database with the game logs dating back to October 2019 of every goalie that has started a game in that span. That can be plugged directly into my Game Summary worksheet to provide whatever relevant numbers my heart desires.
 
Before we go any further, it’s time for my obligatory *DISCLAIMER* it needs be noted that I’m not betting with real money. These are all fictional wagers in a spreadsheet. My mission is to engage in a mass betting campaign, picking a winner of every single game, every over/under, because it provides a complete dataset for macroeconomic analysis, which can be shared with you, shedding light on what worked and what failed. I’m also tracking the results of betting every outcome, to help me (and you) uncover previously unknown or newly emerging profit vectors. What started as a thought experiment has evolved into much more.
 
If you’d like to read more about the first 3 years of this thought experiment, I wrote a 330-page book outlining the results from every angle. What worked, what failed. Lessons learned, market trends, team-by-team analysis. To read more, visit the Amazon store. My blog has been moved to Substack this season and I’ll be repeatedly encouraging everyone to sign-up for a free subscription to alleviate my dependence on Twitter for traffic. I’m concerned that Elon will follow through on his threat to charge everyone for Twitter and ostensibly destroy his own company. Subscribers receive an email notification each time a new post is published, and even if Twitter stays free, the algorithm likes to hide Tweets with links so you don’t leave.
 

Apologies for not sending out any picks emails to my free subscribers this week, but my spreadsheet renovations were not ready in time to give picks for Sunday. Even my weekly preview was a few hours later than usual while the finishing touches were applied. There is still some error checking left to be done (I’m relentlessly paranoid about checking my numbers/formulas for errors) but the hard work is finished (at least until my next big idea). You can read more about that work in my Week 9 Preview, which also has betting picks for all the Monday games.
 
The improvements to my Game Summary worksheet free up substantial space to start adding as many new variables to my tracking as desired. All my new models created too much clutter on the main page where my decisions for each game are made. It was rebuilt from scratch and is better than ever. This means that the information I can potentially provide in my picks emails can also be expanded in several different ways. It can be plugged directly into my historical database of 5000+ games with all the betting results from each. For spreadsheet nerds out there, it’s all about indicator variables (1 or 0) and the sum product function. SumProduct(x) is the secret behind my extensive tracking where everything updates automatically when I type in the final score of the game.
 
One of the big things I’m setting up is the ability to install “safety protocols” on my betting models, so if they have been losing too much money betting Toronto -1.5 goals, there’s an easy way to limit the bet size. I’m also now able to share exactly how each model has performed making that exact same bet in the last 30 days. This was a bad week to bet anyone -1.5 goals, whether favorite or underdog, well at least until San Jose beat the Devils 6-3 in New Jersey on Friday at +700 on the alt puckline. My Tailing History portfolio did lay more money on favorites +1.5 goals this week, and managed a decent profit, inspiring me to venture more into pucklines +1.5 myself, pumping the brakes on faves -1.5 mid-week.
 
It was favorites -1.5 goals that did most of the damage to me and my models, as a few of the league’s best team really shook my confidence. By the time the dust settled, this finished as a strong week for home underdogs moneyline and that was one of my best categories as well. It wasn’t something I was intentionally targeting, with significantly more invested in favorites ML, which generated a small loss. The two teams making the biggest contribution were Columbus and Arizona on home ice, with the Blue Jackets beating Boston and Ottawa, while the Yotes beat Tampa and Colorado. Arizona slayed two pretty big dragons in Mullett Arena this week, which is worth noting.
 
Unders started the week on fire, but eventually cooled off. I mostly just followed the advice of my primary algorithm (aka “OU Prime”), performing poorly when ignoring its recommendation. It was the best of all my over/under models this week, which helped boost my confidence in the one I call “Prime”. This is my first season of over/under betting where I’m tracking multiple different O/U models week to week. The current primary only won the job last All-Star break and has competition for the title of most trusted advisor, although the “Prime Line Value” algo I was pumping last week finished in the middle of the pack for the last 7 days.
 
 
My Team of the Week: Chicago Blackhawks, +$648
 
The Chicago Blackhawks have won twice in their last 8 games, as the team finds itself embroiled in controversy. Corey Perry was booted of the team, it seems for getting hammered and making an ass of himself at a team function, not getting Connor Bedard’s mom pregnant. Whatever the reason, that’s not good for morale, and the product on the ice is suffering. Although bad performance isn’t the whole reason they’re here, as OU Prime had a good week betting their totals, which is assuring because this team had thrown Prime a curveball with funky variance in recent weeks.
 
This was among my better weeks betting the Toronto Maple Leafs this season, but not thanks to any specific strategy. Prime did well on their over/under, they beat a tired Florida team on a back-to-back, then I bet the Bruins on Saturday because they were underdogs and Boston offered the bigger payout. My other Leafs bet was a little more unusual for my habits, putting a max bet on Toronto +1.5 goals at home vs Seattle at -525. They won the game and the ML would have been better, but favorites +1.5 were having a good week and I was feeling frisky.
 
My Worst Team of the Week: San Jose Sharks, -$747
 
My “big short” of the San Jose Sharks hit another setback this week, as I’ve finally reached the stage where I’m not longer willing to make max bets on their opponents -1.5 goals. Watching them beat the New Jersey Devils 6-3 was the straw that broke the camel’s back, but their victory in Washington also pushed me in that direction. They had started covering +1.5 at home more often, but on the road against good teams appeared to be my safe place, at least until week 8 slapped me in the face. After watching that Devils debacle, I bet Sharks +1.5 goals vs the Rangers, which covered. NYR opened at -535 ML, which was bonkers considering they played the night before and had to fly home from Nashville.
 
My second worst team of the week was the New York Islanders. The Isles were in my dog house and I had big bets on Carolina and Florida to win on home ice and New York pulled out wins as +154 and +136 dogs. To make matters worse, their overs went 3-0, which few of my algorithms anticipated. I’m still pretty sure this team isn’t very good, but they won by scores of 5-4 and 4-3, so they didn’t simply win by virtue of a Sorokin robberies. They outscored good teams in close games. It did put a damper on my enthusiasm betting them to lose, but also didn’t exactly give me the confidence to make any big bets on Isles to win against anyone.
 

My Week 3 Results

*Note* “Overall Market Bets” based on betting exactly $100 on every outcome.
 

Home dogs ML was the big winner this week, which it was for me too, I just also did will on road dogs ML. I’m hoping that my over/under slump is in the rearview mirror, posting a nice profit on unders, which was one of the better bets overall. Although, they were up more than $1,000 2 or 3 days into the week, then overs surged back. I could look this up, but I’m assuming the books started lowering the totals when unders started cashing last week, so it’s entirely plausible that’s the reason overs ended the week strong, smaller hurdles to clear. (I’m in a rush to get this posted).
 

This was a bad week for me picking wins and losses for the Washington Capitals, fortunately I crushed their unders so they were not among my worst two teams. Still, I’m really confused who they are right now. They can beat anybody or lose to anybody, and that can be a dangerous combination. I’m a little surprised to see Colorado on my best teams to bet against list, coming from their road games against Arizona and Los Angeles. Otherwise, I’m not targeting them as a team to bet against. I just like the Kings more and thought there was value on Arizona +154 at Mullett Arena. The Tampa Bay Lightning were the best team to bet against overall this week, mine as well.

Team By Team Profitability Rankings

These profitability rankings are based on the sum of all my bets per team, including where the money was won or lost. Each week my new Profitability Rankings will be based on all the games in the season, not just what happened this week.
 

Me vs Myself

 
For those of you who are new here, the “Me vs Myself” section outlines my competition against my betting models, in my vain attempt to prove my own decision making is superior to the models that I’ve created. Me vs my creations. But rather than explain myself every week, a new post was published outlining how all these models make their decisions. For the full breakdown, click here. My Game Sum model was re-programmed this weekend, but you can read more about that in my Sunday Preview. Below is the chart showing how each model performed by category.
 

Tailing History and Betting Venues both struggled -1.5 goals, both favorites and underdogs, but that risk taking behavior was responsible for their best weeks. Live by the sword, die by the sword. I noticed my own results struggling -1.5 goals and pumped the brakes. Sharks covering +1.5 in 5 of their last 6 helped push me in that direction. There will be more about my model performance coming this week in my First Quarter Report, including how each has performed with each team. That data is also easily accessible by my Game Summary worksheet, so I know exactly where to be careful when taking their advice.
 
My Game Sum model received an overhaul on Saturday, but it was amusing that the new version had most of the same problems, it just wasn’t losing as much money. I’ll take that as a victory. This isn’t necessarily a model I’m expecting to be awesome, but its purpose is to tell me what bet has been profitable with these teams in the current season (now last 30 days), given that my other models mostly ignore the current schedule. Its voice has meaning even if it’s not profitable to follow exactly, because when all 3 models like the same team, then we’re cooking with gas.
 

It brings me comfort seeing OU Prime atop the leaderboard. I would be up there with him but when 0-3 when ignoring his advice. Prime Line Value delivered more profit, and has the lead full season. Tails got destroyed and I knew that was going to happen because it was planning to bet every over when the league was trending under. I could have overruled the picks, but that’s not the point. The replicability of past seasons profit shown in my weekly previews is the reason for Tails existing in the first place. What if people made real bets with that data. That’s what we’re keeping score with that model. Betting Goalies had a bad Sunday in day one of its life, but I’m optimistic it will improve.