Introduction

One of the analyses I wanted to do with the publicly available goal tracking data is to see how many goals each team scores off the rush. In order to do that, I had to define criteria for rush goals. That process involved iteratively setting some tentative criteria, reviewing the results, and updating the criteria. At the end of it, I ended up with three criteria that I used to calculate how many rush goals each team scored in the 2025-2026 regular season.

You can find the code I created for this analysis here.

Data

The data I used was the public goal tracking data for the 2025-2026 regular season. This data is the same data that is used for NHL.com’s goal visualizations. Here is one example goal visualization.

For this analysis, I did the same pre-processing steps I had used when looking at goal similarity. This includes trimming the starts and ends of the tracking data to account for things like faceoffs.

I filtered out empty net goals from the data using NHL.com’s API to get empty net goal data.

One caveat: some goals are missing data, but this is a very small percentage of goals (< 0.1% of all goals).

To keep it simple, I only used puck tracking data and not the player tracking data. In the future, I may revisit the criteria to include the player tracking data.

Process

The process I used to come up with criteria to define rush goals was:

  1. Set tentative criteria
  2. Review a sample of goals that were close to being considered rush or non-rush
  3. Update the criteria based on that review and repeat the process

Throughout this process, I reviewed around 60-80 goals in total.

Criteria

The final criteria are:

  1. The puck traveled at least 67 feet along the length of the ice
  2. The puck spent less than 40 timesteps in the offensive zone
    • A timestep is the interval in between data points in the tracking data.
    • In a future analysis, I hope to calculate how much time this interval is.
  3. The puck spent less than 9 timesteps beyond the goal line

Results

Using the above criteria, about 29% of non-empty net goals were off the rush in the 2025-2026 regular season.

Some example goals defined as rush goals by the criteria:

Here are the number of rush goals by team:

Team Number of Rush Goals
CAR 89
PIT 86
UTA 85
BUF 84
EDM 80
LAK 77
MTL 75
ANA 73
STL 73
TBL 73
CBJ 71
NYR 71
CGY 70
MIN 69
TOR 69
NYI 68
PHI 68
VGK 68
NJD 66
WPG 66
COL 65
SJS 65
DET 64
FLA 62
VAN 61
SEA 59
OTT 58
BOS 58
WSH 58
CHI 57
DAL 56
NSH 45

Here are the percentages of goals that were rush goals by team (excluding empty net goals):

Team % of Goals that are Rush Goals
LAK 37%
CGY 36%
STL 34%
UTA 34%
BUF 33%
NYR 32%
NJD 32%
CAR 32%
PHI 31%
CBJ 31%
NYI 31%
WPG 31%
PIT 31%
EDM 30%
TOR 30%
VAN 30%
SEA 29%
ANA 29%
DET 29%
CHI 28%
MTL 28%
TBL 28%
MIN 27%
FLA 27%
SJS 27%
VGK 27%
WSH 25%
COL 24%
OTT 23%
BOS 23%
DAL 21%
NSH 20%

Conclusion

While the criteria I developed seem to work well, I may in a future analysis try to refine them by including player tracking data in addition to the puck tracking data. I would also like to dive deeper into rush goals as well.