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-VQA-XFOUL-XVARS-lora |
Visual Question Answering (VQA) | OSL-XFoul | X-VARS VideoChatGPT + LoRA | Referee-style soccer VQA | Accuracy: 72.24% Balanced Accuracy: 50.00% |
OpenSportsLab/OSL-VQA-XFOUL-XVARS-lora | myModel.load_weights(weights="OpenSportsLab/OSL-VQA-XFOUL-XVARS-lora") |
OSL-VQA-XFOUL-qwen2.5-7B-VL-lora |
Visual Question Answering (VQA) | OSL-XFoul | Qwen2.5-VL-7B-Instruct + LoRA | Referee-style soccer VQA | Accuracy: 65.77% Balanced Accuracy: 36.59% |
OpenSportsLab/OSL-VQA-XFOUL-qwen2.5-7B-VL-lora | myModel.load_weights(weights="OpenSportsLab/OSL-VQA-XFOUL-qwen2.5-7B-VL-lora") |
OSL-VQA-XFOUL-qwen3-8B-VL-lora |
Visual Question Answering (VQA) | OSL-XFoul | Qwen3-VL-8B-Instruct + LoRA | Referee-style soccer VQA | Accuracy: 69.96% Balanced Accuracy: 48.33% |
OpenSportsLab/OSL-VQA-XFOUL-qwen3-8B-VL-lora | myModel.load_weights(weights="OpenSportsLab/OSL-VQA-XFOUL-qwen3-8B-VL-lora") |
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
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
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
OSL-VQA-XFOUL-XVARS-lora¶
Intended use: soccer visual question answering focused on foul analysis and referee-style explanations.
Dataset/training source: OSL-XFoul, using video clips and VQA supervision.
Reported metrics:
| Metric | Score |
|---|---|
| Accuracy | 72.24% |
| Balanced Accuracy | 50.00% |
Hugging Face: OpenSportsLab/OSL-VQA-XFOUL-XVARS-lora
Recommended config:
OSL-VQA-XFOUL-qwen2.5-7B-VL-lora¶
Intended use: native end-to-end soccer visual question answering with Qwen VL.
Dataset/training source: OSL-XFoul, using video clips and VQA supervision.
Reported metrics:
| Metric | Score |
|---|---|
| Accuracy | 65.77% |
| Balanced Accuracy | 36.59% |
Hugging Face: OpenSportsLab/OSL-VQA-XFOUL-qwen2.5-7B-VL-lora
Recommended config:
OSL-VQA-XFOUL-qwen3-8B-VL-lora¶
Intended use: native end-to-end soccer visual question answering with Qwen VL.
Dataset/training source: OSL-XFoul, using video clips and VQA supervision.
Reported metrics:
| Metric | Score |
|---|---|
| Accuracy | 69.96% |
| Balanced Accuracy | 48.33% |
Hugging Face: OpenSportsLab/OSL-VQA-XFOUL-qwen3-8B-VL-lora
Recommended config: