Week 10 NHL Betting Preview

Week ten of the NHL season is nearly upon us and my gaze is already focused on what worked best in the last 2 seasons +/- 7 days by “day of schedule”. There has been a change since I’m having doubts about the replicability of the historical data provided in my weekly previews because the Tailing History model (aka Tails) that uses the data to bet on every game just had a devastatingly awful week. This embarrassment can’t even be blamed on pucklines not hitting, with the bulk of the losses being moneylines, whether home or road, favorite or dog, it lost big on all them. History was not unfolding in a similar matter compared to past seasons, after being mildly replicable throughout the first quarter.

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.

Here’s the good news, the whole reason Tails exists in the first place was to measure the profitability of betting based on the data in my reports. If it crapped out, it would signal the data in my previews is not worth using for betting decisions. Then it shocked me by hitting the jackpot in week one and its full-season balance never sunk below zero for the rest of the first quarter. Sadly, it has been trending downwards since the quarter wrapped. Looking at the chronological category charts in my First Quarter Report, the current season did start deviating significantly from the historical pattern in late November. Below is Tails chronological chart.

You can see the magnitude of the collapse. The current season took off in a completely different direction than precedence predicted. Tails has received a renovation, which also means that the data I’ll be sharing in my weekly previews is also changing. This week’s data will be a little incomplete while my spreadsheet reno is being finished, but the number of stats and details shared will be significantly better upon completion. I’m preparing for the creation of several new models that will be competing in a “Tournament of Models” in the 2nd half. I’m hoping to take suggestions from my subscribers on different models to create, now that my Game Summary worksheet has been integrated with both the current season and my historical database.

Just a note to be aware of, the Betting Goalies over/under model that debuted last week is off to a bad start. I’m going to let it continue for another week or two just to figure out what’s wrong before carrying out repairs. Because it involves me providing a probability of each goalie starting, I can’t test it on older games to see if it’s profitable. I just need to let it fail then fix. But now that I’m keeping a permanent record of my “expected probability of starters”, I’ll be able to test how different versions would have succeeded retroactively. I can also start tracking my accuracy predicting starters for every team. Some teams are pretty easy, others are less predictable.

The information feeding Tailing History has changed, which means so has the information being presented in my weekly previews. What I’ve done here is narrowed the line ranges to 4 on each side instead of six. Instead of looking back at all “week nines” since October 2019, we’re only looking at the last 2.3 years, since 2021 had a freaky schedule and protocols and is not to be trusted. Also, I’m going to be looking forward 7 days and backwards 7 days by “day of season”, and it’s also going to include the previous 7 days of the current schedule in the numbers (roughly 20%). So going forward there will be a little recent history in the preview data (as there is for the graphic above).

These changes were retroactively made to Tails starting Monday, and it went from a $7,000 loss to a $4,000 loss. Still bad, but not as much, and favorites -1.5 was the biggest detriment. Version 2.0 is already a little better. There is yet another new model that needs a proper introduction. This one is just a composite score of the other models input data. It doesn’t actually do anything or have a specific angle it plays. It just steals from everyone else, so I’m calling this one Megatron. It just adds up the input data on VML, V+1.5, V-1.5, HML, H+1.5, H-1.5 used by each individual model, picking the one with the best return.

Megatron did not have a good opening week, but it was following Tails too closely because it has a much larger sample size than the other model inputs. The weighting was changed so only 50% of Tails gets added to the composite score. Megatron did have a good week on over under picks. It just adds up the amount of profit from my advisory team of algorithms (aka the OU Council) picks on that total with these teams the last 30 days, and bets the side reporting the larger profit (or smaller loss). Just be aware, the “Return” beside Megatron in the over/under graphics are a sum of everyone.

If you are new here and don’t know how the models work, you may want to click this link before proceeding. I’ll be sending out at least one picks email exclusively to my free subscribers sometime this week, so subscribe for free if you’d like more game breakdowns like the ones below.

TOR @ NYI:

While I’m sharing a pick for this game, I’m running a large full-season deficit betting both teams to win. That’s why I’m just making a small bet on Isles +1.5 goals at -218. This should be Sorokin vs Samsonov (who just shutout the Predators yesterday). None of my models have a track record making those picks for these teams in the last 30 days, except Tailing History lost two $500 bets, one on Leafs to win on the road by at least -1.5, the other on Isles to lose at home by at least -1.5. It’s a different story for my “Over/Under Council” who almost unanimously picked the over, most of them running a nice positive balance on over 6 goals last 30 days with these teams. Note the “return” for Megatron is $2,397. He adds up everyone else’s results betting over or under 6 goals in the last 30 days. In this case, they had all collectively profited $2,397. So that number is a sum, it’s not Megatron’s actual results betting overs, while the others are. I might need to permanently denote that in my pick graphics.

ARI @ BUF:

I’ve been struggling to predict the starter in Arizona games, writing in my game notes “this has to be Vejmelka, they can’t play Ingram every game” multiple times. I was wrong. Ingram has started 7 in a row.  Vejmelka is sporting an .833 SV% in his last 3 starts. Now Ingram has given up 9 goals in his last 2 starts, so it would be prudent to start giving him more rest. On the other side, I have no idea which two goalies will even be dressed in this game. UPL has missed a couple games due to “illness” with Levi back up from the AHL (giving up only 3 goals in 2 games, beating Boston in one of them). Given my concern about Vejmelka, I can’t follow my models picking the Yotes. I’ll just put a minimum bet on Buffalo ML at -125. Everyone loves under 6.5 here, but Vejmelka overs are 7-3 this season. Everyone is running a nice profit on under 6.5 because of Ingram. I’m tempted to take the over and defy the entire OU Council, but will instead fall in line. Note that Vejmelka does have .970 SV% in 2 career starts in Buffalo, if that even matters. Tailing History and Betting Venues both like Yotes -1.5 goals and are running a nice profit in the last 30 days betting against Buffalo -1.5 goals at home.

DET @ DAL:

Dylan Larkin suffered what could be a serious injury last night, and he’s crucial to their success as high-end first line center. If Detroit completely craters in his absence, it will help build a strong case for his Hart trophy campaign. My models mostly like Detroit, but are using data where the Wings have one of the best centers in the league. Betting Venues and I are both taking the Dallas moneyline at -198 (that has moved to -205). The Stars have won Detroit’s last 7 trips to Dallas (it would like the bet more but the Starts were HEAVILY favored in nearly all those games, so the sum of the payouts was small relative to the W:L ratio). The Wings have been alternating goalies, Lyon has mostly been good while Husso has sucked (.878 SV% last 30 days). I’m giving either guy a 50-50 chance but it’s Husso’s turn if the current rotation holds. I just don’t understand why they keep rolling him out. This should be Oettinger for Dallas, and nearly everyone loves over 6 goals and are running a nice profit with that bet for these teams last 30 days. Granted, Detroit might not score any goals for the entire duration of Larkin’s absence…..

CGY @ COL:

The Colorado Avalanche have lost 5 of their last 6 games, a few of those without Valeri Nichushkin, who did return for their 5-2 loss to Philly. Granted, they were on a 7-1 run before this new slump. The models favor Colorado, but Megatron is only putting a minimum bet on Avs +1.5 goals if that’s any indication of the model input data. I’m going with a small bet on the Avs moneyline at -180 hoping that slump is over and they go on another nice run. I’m expecting Dan Vladar to start for Calgary but there might not be much difference between him and Wolf (who is younger with better long-term upside). Should be Georgiev for Colorado.  There was unanimous support for under 6.5 goals, but when Megatron added up their collective profit on that bet with these teams last 30 days, the result was less decisive.