These are statistical projections and shouldn’t be the only thing that factors in to betting on a team, the stats only tell part of the story. Keep an eye on injuries, back to backs, COVID Issues, and players returning from injury. All stats pulled are TEAM stats from the season and don’t account for individual players.

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**Note:** Series Projections added to the bottom, below the game projections.

**Updated:** 13 May 2022, 7:00am CT

## Records

#### Top Performing Models

Based on Average Win % between ATS, Moneyline, and O/U.

## Summary of Projections

#### Consensus Record

#### Consensus Profit

#### Consensus Projections

## Team Trends

Quick look at how teams have performed recently as compared to their season stats. I pulled the stats from NHL.com from the last 2 Months (about 30 games).

This chart shows teams that are playing better or worse recently compared to there season as whole (in regards to goals). The stats shown are each teams Goals For per Game (GF/G) both season and recently. The “Off Trend” shows if a team has averaged more goals recently than their season average, which typically indicates an improvement in offense recently. The next 2 columns show the Goals Allowed per Game (GA/G) both season and recent. That is how many goals each team is giving up on average. A positive number in the “Def Trend” column indicates a team is allowing less goals per game and playing better defense lately. The overall trend just adds the Off and Def trend to give an overall goal per game difference compared to the season average. Positive numbers mean the team is playing better recently. The trend numbers are color coded to make it easier to read, Green is positive and indicates improvement compared to season average. Red is negative and indicates a team playing worse compared to season average. What the “Total goals Trend” column shows is teams with a higher positive number (Positive, Shaded in green) are scoring more points and/or allowing more points per game recently, indicating their games have been higher scoring and a likelihood that they have been hitting more overs lately. Teams with lower numbers (Negative, Shaded in red), have been scoring less points and/or allowing less points per game recently, indicating their games have been lower scoring and likely trend towards them hitting more under’s lately. Both the overs and unders hitting will be affected by Vegas adjusting the lines based on recent trends.

## Team Variance

What this chart is showing is each teams Variance & Standard Deviation (Std Dev). Variance and Std Dev are calculated from the season stats. The list is ordered from lowest team variance to most team variance. The variance is how wide spread the data is, a team that scores between 0 to 10 goals every night will have very high variance, whereas a team that scores anywhere from 2 to 3 on a given night will have very low variance. The Std Dev is the square root of the variance and is a good measure for how consistent a team is… NOT how good or bad a team is, but how consistent they are. Std Dev shows the amount a teams score typically deviates from the average on a given night. The Jets score (typically) will deviate about 1.40 goals from there average on a given night, where the Blues score (typically) will deviate 2.16 goals from their average on a given night. Obviously the lower the Std Dev the easier it is for my models to project the score and provide higher probabilities.

# Model Projections

## My Model Choice: Random Forest

#### Model Projections

How to read the projections: The model type is at the very top. Matchups are denoted by the alternating white/green pairings, away teams are on top, home teams on bottom. The model analyzes the matchup and projects the home and away teams score (Proj Score). The difference between the home teams score and the away teams score give us what the model says the line should be (Proj Line). The “Line” column is what the Vegas line is at the time I run the model. The “Line Diff” is the difference in the projected line and the Vegas line. A positive line diff means the projected line is in the away teams favor compared to the Vegas line, negative means the projected line is in the home teams favor. The “Cover Prob” uses a normal distribution and the teams variance to project each teams probability to cover the listed Vegas line. Same thing for totals, “Proj Total” is the sum of the projected scores, “Line Total” is the listed Vegas total for the game, the difference between the two, and the probability to go over or stay under denoted by “O” and “U”. The “ML prob” is the probability of a team to cover the moneyline, or the outright winner.

#### Betting Edge

If you don’t understand what you are looking at, I recommend reading my post about betting tips. The percentages show the betting Edge, which is the cover prob (from above) minus the implied probability (-110 odds implied prob is 52.4%). If a team has a 92.4% chance to win and a 52.4% implied probability (or -110 odds), the Edge is 40%. The Edge alone doesn’t mean you should blindly bet it. To quantify, >35% is great value, 20-35% is really good, 10-20% is decent, <10 is ok value, blanks are negative value.

## Top Performing Model: SVM

#### Model Projections

How to read the projections: The model type is at the very top. Matchups are denoted by the alternating white/green pairings, away teams are on top, home teams on bottom. The model analyzes the matchup and projects the home and away teams score (Proj Score). The difference between the home teams score and the away teams score give us what the model says the line should be (Proj Line). The “Line” column is what the Vegas line is at the time I run the model. The “Line Diff” is the difference in the projected line and the Vegas line. A positive line diff means the projected line is in the away teams favor compared to the Vegas line, negative means the projected line is in the home teams favor. The “Cover Prob” uses a normal distribution and the teams variance to project each teams probability to cover the listed Vegas line. Same thing for totals, “Proj Total” is the sum of the projected scores, “Line Total” is the listed Vegas total for the game, the difference between the two, and the probability to go over or stay under denoted by “O” and “U”. The “ML prob” is the probability of a team to cover the moneyline, or the outright winner.

#### Betting Edge

If you don’t understand what you are looking at, I recommend reading my post about betting tips. The percentages show the betting Edge, which is the cover prob (from above) minus the implied probability (-110 odds implied prob is 52.4%). If a team has a 92.4% chance to win and a 52.4% implied probability (or -110 odds), the Edge is 40%. The Edge alone doesn’t mean you should blindly bet it. To quantify, >35% is great value, 20-35% is really good, 10-20% is decent, <10 is ok value, blanks are negative value.

**Series Projections**

Each series was run through the machine learning algorithms to project the score.

I ran 500 Monte Carlo simulations to project how the series would go. If you don’t know what a Monte Carlo sim is, it’s basically just running the matchups 500 times using a teams Variance to come up with 500 different game results. Using the 500 Games, I counted the first team to 4 wins to get the expected series winner and counted the number of times a team won the series and the series and the score when a given team won.

The number of wins and win percentage is fairly easy to understand, its just the number of games out of the 500 that a particular team won and the corresponding win %.

The average game margin can tell you how close or how tight the games were on average. A larger positive average scoring margin says there blew out their opponent more often than they lost by a large margin. A value close to 0 indicates a lot of closer games or an equal number of blowouts from each side.

The average margin of victory in games won tells you how close the games were in games that a team won. A large number typically means that when they did win, they usually won by a wide margin. A small number means that when they did win, it was typically a close game.

Average score is just the average score by each team across all Monte Carlo Sims and the Game total is the average amount of goals scored by both teams across all 500 simulations.

*[LR = Linear Regression, kNN = k-Nearest Neighbor, RF = Random Forest, SVM = Support Vector Machine, NN = Neural Network, Ada Boost = Adaptive Boosting]*

Do you update the projections for each game? If so at what time ?

I was, but I have been working a lot of OT these last 2 weeks so I haven’t been able to find time to update NHL or NBA these last few days. Overall, the game proje tons won’t change much, these last few I’ve missed are just 2-3 games out of the 82+ games played throughout the regular season and playoffs. Maybe 0.1-0.2 point difference for each team.

Okay I totally understand. I was just making sure I wasn’t tripping when the lines were the same. You deserve a vacation 🙂