1. A Preliminary Look at 82-Game Trends with a Focus on Expected Goals
March 3rd, 2018
Emily Jo Michele
Over 82.
A Preliminary Look at 82-Game Trends with a Focus on Expected Goals

2. Are goals really more difficult to come by later in the season?
Goals seem to fluctuate ever so slightly, with a very minor increase in even strength goals as the season progresses.

3. Overview Season Trends Expected Goals
The 82-Game Season
Expected Goals
What are expected goals?
How do goals, expected goals, and their differentials fluxuate or trend?
Topics:
Are expected goals more difficult to come by later in the season?
GF vs xGF
Actuals vs Expected Differentials
Percentage Differentials
Team Trends

4. Sources & Methodology
Raw data was gathered from Emmanuel Perry via Alex Novet and Corsica.Hockey
Data from season through
Excluded data from Lockout Year
All data used from this point forward is Even Strength Data
Where appropriate, only home team data was used to avoid duplication or equal and opposite cancellation
Five Game Rolling Averages were used for all charts so averages for games 1-4 are unavailable
Where appropriate, slope equations of trend lines were used to assess a positive or negative trend

5. Are expected goals more difficult to come by later in the season?
While it doesn’t appear to be much here, there actually is a small, fluctuating, but definitely upward trend for expected goals throughout the season at 5v5. It mirrors the extremely minor uptick in 5v5 actual goals.

6. Is there a fluctuation in the differential between Actual and Expected goals throughout the season?

7. What about For Percentage differentials?
* - to avoid cancelling percentages, only the home team was used in the calculation of this differential.

8. Traps to Avoid
These differentials do not imply one team is better or worse at the beginning or end of the season
It characterizes how predictable a team is at a given point in the season based on xGF metrics
These differentials don’t indicate whether teams are under- or over- performing
Further research would have to be performed to examine in what direction teams trend in matching their xGF percentages and why

9. Next Steps
Analyze why the differential between goals for percentage and expected goals for percentage may decrease throughout a season
Analyze similar trend on a team by team basis. Do all teams follow these trends?
The “40s” flux - what about this time of year seems to produce a “bump” or “dip” in the rolling average across examined metrics? xG
GF vs xGF
GF% vs xGF%

10. Special Thank You
Alex Novet & all those involved in the Hockey Graphs Mentorship Program
Corsica.Hockey

11. Thank you! In case this wasn’t your thing, here’s a picture of my dog.
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12. Team by Team Trend in Differential between GF% & xGF%