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Model Zoo

This page lists the pretrained OpenSportsLib models published on Hugging Face. Use the model repository ID with load_weights(...) to load a checkpoint into an OpenSportsLib model.

Available Models

Model Task Dataset trained on Backbone / architecture Classes / label set Scores Hugging Face link Load weights snippet
OSL-cls-action-mvitv2 Action / Event Classification SoccerNet - MVFouls classification subset MViT v2 Not reported on model card Accuracy: 0.57
Balanced Accuracy: 0.40
Top-2: 0.78
OpenSportsLab/OSL-cls-action-mvitv2 myModel.load_weights(weights="OpenSportsLab/OSL-cls-action-mvitv2")
OSL-loc-snbas-2023-e2e Action Spotting / Localization SoccerNet - Ball Action Spotting 2023 E2E, DALI backend PASS, DRIVE tight mAP: 71.48
loose mAP: 85.62
OpenSportsLab/OSL-loc-snbas-2023-e2e myModel.load_weights(weights="OpenSportsLab/OSL-loc-snbas-2023-e2e")
OSL-loc-snbas-2025-e2e Action Spotting / Localization SoccerNet - Ball Action Spotting 2025 E2E, DALI backend PASS, DRIVE, HEADER, HIGH PASS, OUT, CROSS, THROW IN, SHOT, BALL PLAYER BLOCK, PLAYER SUCCESSFUL TACKLE, FREE KICK, GOAL tight mAP: 47.98
loose mAP: 58.35
OpenSportsLab/OSL-loc-snbas-2025-e2e myModel.load_weights(weights="OpenSportsLab/OSL-loc-snbas-2025-e2e")

OSL-cls-action-mvitv2

Intended use: video-based soccer action / event classification.

Dataset/training source: SoccerNet - MVFouls classification subset, using video clips.

Reported metrics:

Metric Score
Accuracy 0.57
Balanced Accuracy 0.40
Top-2 0.78

Hugging Face: OpenSportsLab/OSL-cls-action-mvitv2

myModel.load_weights(weights="OpenSportsLab/OSL-cls-action-mvitv2")

OSL-loc-snbas-2023-e2e

Intended use: video-based soccer action spotting / localization.

Dataset/training source: SoccerNet - Ball Action Spotting 2023, using video clips at 224p resolution. The model card reports two classes: PASS and DRIVE.

Reported metrics:

Metric Score
tight mAP 71.48
loose mAP 85.62

Hugging Face: OpenSportsLab/OSL-loc-snbas-2023-e2e

myModel.load_weights(weights="OpenSportsLab/OSL-loc-snbas-2023-e2e")

OSL-loc-snbas-2025-e2e

Intended use: video-based soccer action spotting / localization.

Dataset/training source: SoccerNet - Ball Action Spotting 2025, using video clips at 224p resolution. The model card reports twelve classes: PASS, DRIVE, HEADER, HIGH PASS, OUT, CROSS, THROW IN, SHOT, BALL PLAYER BLOCK, PLAYER SUCCESSFUL TACKLE, FREE KICK, and GOAL.

Reported metrics:

Metric Score
tight mAP 47.98
loose mAP 58.35

Hugging Face: OpenSportsLab/OSL-loc-snbas-2025-e2e

myModel.load_weights(weights="OpenSportsLab/OSL-loc-snbas-2025-e2e")