2023/24 Week 9 Betting Report

Week nine of the NHL season has been logged into the history books as we are now 2 weeks into the second quarter of the schedule. For a full breakdown of the first quarter, check out my First Quarter Report published on Friday, breaking down each of the 32 teams, how me and my models performed betting their games. This was my best week in a while, sticking mostly to betting moneylines and pucklines +1.5 goals. Favorites -1.5 continued their downward slide, but didn’t bring me along for the ride. My primary OU (aka OU Prime) algorithm had a decent week, but a new model on the block might become my new primary.
 
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.
 

Renovations continue for my betting spreadsheet, and it might be another two weeks before those are completely finished. The biggest news was that my Tailing History portfolio received a significant overhaul to the sample its analyzing. You can read all about it in my Week 10 Preview, but the short version is that it now looks only at the two previous seasons (tossing the 2021 data because that schedule was fraudulent), it looks backwards and forward by 7 “days of the season” which will also include the past 7 days of the current season.
 
The “Tails” you knew and loved no longer exists. It was down more than $7,000 on the week by Friday, in a sudden catastrophic collapse. Frankly, I never expected it to post profit for the entire first quarter of the schedule, its purpose was to measure the replicability of history to determine if the data provided in my previews has any relevance. Well, it did in the first quarter, then fell off a cliff. Is there a lesson to be learned there? Most of its biggest gains were in week one, then it mostly broke even for the rest of the quarter. Maybe early in the schedule is the most replicable, then chaos ensues by December.
 
I’m completely overhauling how my data is saved, sorted and displayed. In the past, my historical data from previous seasons was in a separate worksheet that I would check when there was a hypothesis that needed testing, but now the historical DB has been merged with the current season. The new system is far more efficient with less moving parts that can lead to errors. I’m drawing all my data from the same worksheet. I do need to apologize; all these renovations are happening so fast that there will be mistakes. Please just be patient, because this all setting up for a very exciting second half.
 
There will be extensive error checking needed to filter out any formulaic mistakes, but the good news is that the old info summary worksheets were not deleted, the new ones were built from scratch. So as the new data comes online, I can easily check if it matches the old data. As I’ve said many times, I’m very paranoid about errors and run regularly scheduled diagnostic testing to make sure everything is right. The new system will allow for much faster and easier analysis. I’m also going to have category charts by day of season that update as soon as new information is added. I’ll be able to visit a single worksheet that has several charts, and just browse if there’s any trend data worth sharing.
 
 
My Team of the Week: Anaheim Ducks, +$823
 
The Anaheim Ducks were one of my bandwagon teams early in the schedule when they were exceeding expectations, but alas, they have been regressing to the mean for the last few weeks. This is not a good stage of the season traditionally for John Gibson, but the offense is also struggling to score. All my Ducks profit this week was from betting them to lose and unders. Anaheim is 9-1 in their last 10 and have lost all my confidence, especially with McTavish and Zegras battling injuries. But losing confidence on one side does increase confidence in the opposing team. That will continue until it ceases to be profitable.
 
The Winnipeg Jets were my second-best team of the week, mostly from betting them to win and unders. However, they were dealt a serious blow losing Kyle Connor Sunday night to a knee injury, and their offense is really going to miss him if the injury is long-term. I’m already taking San Jose ML tomorrow (Sharks were also among my best teams this week), and will need a little line value if I’m taking them in Connor’s absence. Thankfully Winnipeg managed to fight back and win that Ducks game, because I had a max bet on Jets ML (shared in an email exclusively to my free subscribers Saturday).
 
 
My Worst Team of the Week: New York Rangers, -$909
 
The New York Rangers successful western road trip followed by continued victories without Shesterkin or Fox inflated my confidence in their ability. That confidence was only reinforced when Igor returned and played well. Betting the Rangers to win led me down a dark path marked by red ink. Not only did they lose, they lost be a combined score of 10-2 to the Ottawa Senators and Washington Capitals, who haven’t exactly been powerhouses lately. That made me feel safe betting Kings to win Sunday, but that was the game Rangers won. This is a team that often makes me feel stupid for both betting them to win and lose.
 
The Tampa Bay Lightning were my second worst team of the week, thanks mostly to their 4-0 victory against Dallas, who had blown them out the previous game. That’s the type of situation where I should have known Vasilevskiy would be back in net on a mission, but hadn’t seen any evidence of his return to form. Shutting out Dallas is evidence he’s at least capable of showing flashes of himself. How he sustains that over the rest of the schedule remains to be seen, but if he’s going to be good, it’s hard to bet a significant amount of money on a Lightning opponent.
 

My Week 9 Results

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

 

This was a strong week for road dog moneylines and unders, but my own best categories were very different with a nice profit on both dogs and favorites ML. My Tailing History model might have collapsed from bad data in my preview last week, but one nugget of history that repeated itself, it was a good time to bet against teams back-to-backs. It also needs to be said, if you ever see “bet back-to-backs” in my work, that ALWAYS means bet against the tired team. Sometimes I will indeed bet on the tired team (usually because the line swung too far, or some other circumstances), but not often do I encourage others to do so. Mostly because I’ll feel stupid having done that and they get blown out because they’re tired.

The LA Kings losing twice this week did hurt my feelings, especially blowing a 3rd period lead against the Islanders. They lost the next game to the Rangers, and that’s when NY finally got their act together for a big win. It was my one blight on an otherwise great week. Betting Pittsburgh to beat the Flyers and Pens +1.5 goals vs Tampa were my other big losses. The San Jose Sharks recaptured first place in my profitability ranks from LA, thanks to betting them +1.5 goals every game. Surprisingly their overs went 3-0 mostly because the team has suddenly started scoring, even against a few really good defensive teams.
 

 

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. Below is their table displaying results by category and ignoring their advice more often paid off. All of them have been struggling in the 2nd quarter, this is not a newly emerging trend, but those early struggles are why I wasn’t listening as much this week.

My spreadsheet has been modified to allow for unlimited models. Yeah, I may have said a couple weeks ago that I’m done building new models for a while because my spreadsheet was crowded, but instead just overhauled the spreadsheet. The new integration in my spreadsheet merging 2023/24 with my historical database makes it really easy to build and track new models. However, what is getting crowded are my reports and previews analyzing and reporting on all the models. For example, the full season average over/under model is in dead last, but I’m still sharing all its choices in all my picks graphics.
 
At some point in the not-too-distant future, I’ll start dropping the worst performing models from the information I’m sharing. I’ll continue tracking them because there’s unlimited space for me to do so, but that doesn’t mean that they all need to be shared with you in every game review. Take the newest model introduced yesterday in my preview, Megatron, who is just a villainous thief who steals from the other models. It got absolutely destroyed betting ML & PL, worse than any model it stole from, but it was the best performing over/under algorithm.  Stealing was very effective when it came to totals. It’s ML+PL picks are still shared below, because it received surgery this morning.
 
The Tailing History results for the week are the updated version. I went back and retroactively changed its picks starting Monday (also filling out Megatron in the process), so that disaster described earlier is not reflected in the table above. Betting Venues continued to struggle, but that began 3 weeks ago. On one hand, I’m narrowing the gap between us which should restore my faith in my own decision-making ability, but it was more fun when it was excelling. That reminds me, B.V received an upgrade this week, as it now includes games from the current season. Integrating current and past seasons made that very easy. If Betting Venues continue to struggle, I may tweak its bet selection algorithm.

OU Prime has the best record in the second quarter, but Megatron had an excellent first week and I’m already starting to take its advice more often. Hopefully it doesn’t deceive me, because I went 1 for 5 this week when disagreeing with Prime (hence why my record was worse when I’m following 90% of the time). I’m also interested seeing Game Sum creep up the leaderboard, because it received an update recently, adding up betting every over and under for all games in the last 30 days involving either of these teams with that precise opening total. I’m not surprised at all to see that do well. Also, if you use full season average goals to make over under bets, stop. It sucks by this stage of the season.