Hockey-Vision CV Models
This repository contains five YOLO models trained on broadcast NHL video. These models are designed to be small and efficient (~2.5M parameters, ~5MB each), capable of running in real-time on most devices.
Together, they identify players, goalies, and referees, track the puck, read jersey numbers, and detect rink markings for top-down homography mapping.
| Model | File | What it finds |
|---|---|---|
| Player | new_player_model.pt | Skaters, goalies, and referees |
| Puck | new_nano_puck.pt | The puck |
| Number | new_nums.pt | Jersey digits for player identification |
| Rink | new_rink_model.pt | Lines, circles, goal frame, and creases |
| Dots | new_dots.pt | Faceoff dots |
Model Overviews & Examples
The examples below show each model running on three 10-second clips from a game between the Montreal Canadiens and San Jose Sharks. Click any image to view the full example video.
Player Model
new_player_model.pt
Finds every person on the ice and identifies their team. Classes include team_a_player, team_b_player, goalie_a, goalie_b, and referee. Teams are identified by jersey colors.
| Clip 1 | Clip 2 | Clip 3 |
|---|---|---|
 |  |  |
Puck Model
new_nano_puck.pt
A specialized detector for the puck. Because the puck is small and often obscured, this model is typically run with a higher confidence threshold (~0.6).
| Clip 1 | Clip 2 | Clip 3 |
|---|---|---|
 |  |  |
Number Model
new_nums.pt
A digit detector (0-9) that runs on player crops. It identifies jersey numbers through a multi-step process:
- Digit Detection: Finds single digits on upscaled player crops.
- Assembly: Groups neighboring digits into one- or two-digit numbers.
- Temporal Voting: Aggregates readings across frames to settle on a confirmed number for each tracked player.
| Clip 1 | Clip 2 | Clip 3 |
|---|---|---|
 |  |  |
Rink Model
new_rink_model.pt
Detects painted rink markings (Blue Lines, Center Line, Circles, Goal Posts, and Creases). These detections are used to calculate the homography between the camera view and a top-down rink coordinate system.
| Clip 1 | Clip 2 | Clip 3 |
|---|---|---|
 |  |  |
Dots Model
new_dots.pt
Finds the faceoff dots. Since dots are precise points on the ice, they provide high-confidence anchors for the rink homography mapping.
| Clip 1 | Clip 2 | Clip 3 |
|---|---|---|
 |  |  |
Technical Details
These models are part of the larger Hockey-Vision system, which handles tracking (ByteTrack), homography mapping, and roster integration.
- Architecture: YOLOv8n (optimized as YOLO26n)
- Parameter Count: ~2.5M per model
- Inference Size: ~5MB per model
These models are used in my GitHub project: https://github.com/AlexRHaigh/Hockey-Vision