Controlling for Context

S. Burtch © 2014

delta Corsi

How have we traditionally assessed players?

• Traditional Points• Plus/Minus• Faceoffs• Real Time Stats (hits, blocked shots, takeaways/giveaways)• Ice Time

How has that changed in the Behind the Net Era? (2007 – Present)

• Rate Statistics• Possession Metrics (On-Ice)

• Shots For / Against• Shot Attempts For / Against(aka Corsi)• Unblocked Shot Attempts For / Against (aka Fenwick)

• Shot Attempt Differentials• Shot Attempt Percentages

Realizations over Time

• Not all minutes/situations are created equal – we are aware of Contextual impacts resulting from usage.

• We’re working within a dynamic system – teasing out impacts of individuals will never be a simplistic process.

Contextual Factors We Can Account For and Examine

• Zone Starts• Time on Ice• Quality of Teammates• Quality of Competition (more on this later)• Face Off Wins/Losses• Aging

• Score Effects• Time Effects (in game)• Shot Type / Location

How Have We Examined These Things?

• Eyeballing all the various components

• REL Measures (On Ice - Off Ice differential) - Desjardins• WOWY Charts – Tango (via Johnson)• Usage Charts – Vollman• Aging Trajectories / DELTA – Tango• Heavy Lifter Index - Poplichak• Score Adjusted Metrics – Tulsky• Zone Start Adjusted Metrics – Tulsky• Hextally – Thomas / Ventura

Efforts to Reify Metrics Into Single Values For Comparison Between Players

• THoR – Schuckers• Expected Goals – Parkatti/Pfeffer• Delta SOT – Awad• Goals Above Baseline – Thomas / Ventura

• delta Corsi – Burtch

SDI to delta Corsi – organic development

• Need to assess defenders better• Defenders don’t seem to have a massive amount of

impact on SV% or SH%• Defenders DO seem to repeatably impact on Shot Attempt

Differentials• Initially patterned after HLI (Poplichak) – but specific to D

men

• Unhappy with index values / basis for comparison / weighting

• Shifted to a regression model to predict outcomes• Multivariate Linear Regression Model to predict Expected

Corsi

Results of Regression

• Corsi For and Corsi Against are very weakly correlated – Offense does NOT equate to Defense at the team or individual skater level.• This means we should regress CF and CA separately

• Position is Relevant (F and D impact CF/CA differently)• QoT effects are very significant• QoC effects are marginal to nonexistent

• This aligns with the work done by Tulsky and Johnson• TOI is a significant correlate to results (better players tend

to play more)• Zone Starts are significant• Faceoffs matter – but less than people think

Results of Regression

• Yearly Team Effects are very significant• This is likely an indication of team quality / systems /

coaching• Age effects are hard to detect but appear to be present

• CONTEXT MATTERS VERY MUCH – It Explains Over 64% of observed results for Corsi.

Expected vs. Observed Corsi Results from 2007 – 2014 (original Regression)

-10 -8 -6 -4 -2 0 2 4 6 8 10-15

-10

-5

0

5

10

15

13-14 P. Bergeron

13-14 GiordanoR² = 0.649951715389784

Expected Corsi 20 vs. Observed Corsi 20

dCorsi – What Is It?

• dCorsi represents the residual (differential) between a player’s Observed Corsi and their Expected Corsi resulting from the discussed regression.

• This is an improvement on Corsi REL because it is determined directly from contextual factors while the player is ON the ice (the OFF Ice results aren’t weighted equivalently to the other factors).

dCorsi – Is It Meaningful or Reliable?

• 1 SD of dCorsi for NHL skaters is ± 2.0404, population mean µ = 0.019• dCorsi is repeatable at a higher level than individual skater SH% or

goaltender SV%.• Year to Year 5v5 SV% for goalies with 500+ mins has an autocorrelation

coefficient of r = 0.0646, which translates to an r2 of 0.004171 – the prior year explains 0.4% of the following year’s result.

• The r2 year over year for Expected Corsi exceeds 43%, and for dCorsi is approximately 15%.

• dCorsi accounts for yearly team effects so players are not impacted negatively/positively by transitioning from one team to another year to year.

• Impacts of Coaching Effects Can Plausibly Be Observed Year to Year.

dCorsi – Where Can We Get It?

Tableau Visualizations have been created for tracking individual skaters and to make team comparisons.

http://public.tableausoftware.com/shared/5MKNXWTX4?:display_count=yes

http://public.tableausoftware.com/shared/G6HYCG29P?:display_count=yes

THANKS!