cs.CVAug 3, 2025
SaveSoccerTrack v2: A Full-Pitch Panoramic Video Dataset for Game State Reconstruction and Ball Action Spotting
Organizations: Nagoya University∗ · University of Tsukuba
Abstract
Soccer analytics draws on two kinds of information: spatio-temporal data describing where players and the ball are, and event data describing what they do. Public datasets offer them apart, or together only on broadcast footage that leaves players outside the frame unobserved. SoccerTrack v2 combines continuous full-pitch video, long player trajectories and actor-linked events in one resource: ten university-level matches, 932 minutes of fixed-camera 4K panoramic video, annotated per frame with metric pitch coordinates, jersey numbers and persistent identities, roles and team sides for all players, and with ball action events in twelve classes, linked to the acting players through the same identifiers used in the trajectories. We fix a match-level split and report baselines for two tasks. For game state reconstruction, we run a full pipeline over all twenty halves and find that GS-HOTA scores degrade as sequence length increases. For ball action spotting, we train a model on the player trajectories, with and without the ball track. The data, the split and the evaluation tooling are released so that both tasks can be developed and compared at match length on the same footage.
Figures & tables
Figure 1 : Example panoramic frames from SoccerTrack v2: the released field of view spans the pitch across venues and lighting conditions.
Figure 2 : One match at a glance: M2, first half. (a) A frame of the released panoramic video at the instant of a Throw In event, 24:40 into the half: all twenty-two players are annotated, drawn as markers carrying their jersey numbers, with the acting player named by the event (jersey 21) in red. (b) The game state at the same frame, drawn from the game state annotations: all twenty-two players in metric pitch coordinates, coloured by team side, the event’s actor at m, beyond the touchline to take the throw. (c) The ball action layer of the same half: all events over 45 continuous minutes, one row per class, coloured by acting team, with the pictured instant marked. The events name their actors in the same identity space as the tracks, so the three views resolve to the same players at the same instants.
Figure 3 : Dataset statistics. (a) Ball action class distribution over the -event benchmark (log scale): the two most frequent classes account for of events and the support spans a factor of . (b) Ball action events per match; asterisks mark the two matches whose recorded ball track is clamped to the pitch rectangle (Table 1 ). (c) Density of all million annotated player positions of the game state layer in metric pitch coordinates, pooled over the ten matches (log colour scale). Positions are annotated on a grid of the pitch, so each histogram cell measures m; of positions fall outside the displayed margin. (d) How long identities stay annotated. Each of the ground-truth tracks follows one player through one half; the histogram counts tracks by their annotated duration (log count scale). The median track is annotated for continuous minutes, while the dashed line marks the -second clips on which existing game state benchmarks are defined Somers et al. (2024b) .
| Match | Duration (min) | Events |
|---|---|---|
| M1 | 90 | 2,085 |
| M2 | 92 | 2,252 |
| M3 | 97 | 2,117 |
| M4 | 97 | 2,129 |
| M5 | 97 | 1,945 |
| M6 | 94 | 2,106 |
Table 1 : The ten SoccerTrack v2 matches, labelled M1 to M10 throughout the paper. Duration is the annotated play time of each match at . Every frame carries game state annotations for all players on the pitch: metric pitch coordinates on a canonical system, jersey number and persistent player identity, role, and team side. Events counts the twelve-class ball actions. A curated tracking subset, one four-minute clip per match with every player boxed in every frame ( frames and million boxes in total), is described in Section 4.5 . marks the two matches whose recorded ball track is clamped to the pitch rectangle and therefore never leaves play.
| Dataset | Video released | Pitch state | Events | Length |
| SoccerNet Giancola et al. (2018) ; Deliege et al. (2021) ; Cioppa et al. (2022) ; Cioppa et al. (2021) | broadcast, full matches | estimated positions of visible persons, no identities; image-space boxes on 30 s clips | 110,458, not actor-linked | 500 matches, 764 h |
| SoccerNet-GSR Somers et al. (2024b) | broadcast, 30 s clips | visible persons only | none | 200 clips, 100 min |
| SportsMOT Cui et al. (2023) | broadcast clips, three sports | no | none | 240 clips, 150 k frames |
| SoccerNet-GAR Karki et al. (2025) | broadcast, 4.5 s event clips | all 22 and ball, refined from broadcast | 87,939, group-level | 64 matches, event windows only |
| FOOTPASS Ochin et al. (2026) | broadcast, full matches (NDA) | all 22, partly imputed (9 to 12 visible) | 102,992, actor-linked | 54 matches |
| Bassek et al. Bassek et al. (2025) | withheld | all 22, observed at 25 Hz | 11,137, actor-linked | 7 matches |
Table 2 : Positioning of SoccerTrack v2. The first four groups are defined by where the game state comes from relative to the released video: inferred from the released broadcast, measured by an instrument separate from the released camera, released without video, or rendered. The final group is defined by footage instead: releases of full-pitch video, with this release last; whether its provider measured the positions on the released view is not documented (Section 4.1 ). Events counts released event annotations and states whether each names the acting player. Length is as each release reports it.
| Opening 30 s | Full half (45 min) | ||||||
| Half | GS-HOTA | Attrs off | GS-HOTA | DetA | AssA | LocA | Attrs off |
| M1, 1st | 23.10 | 27.37 | 6.68 | 4.29 | 10.50 | 71.77 | 8.46 |
| M1, 2nd | 6.49 | 31.31 | 3.60 | 1.15 | 11.25 | 72.06 | 7.44 |
| M2, 1st | 55.20 | 66.12 | 14.28 | 10.04 | 20.37 | 83.02 | 22.14 |
| M2, 2nd | 26.49 | 49.15 | 12.13 | 8.01 | 18.38 | 83.00 | 22.08 |
| M3, 1st | 36.49 | 61.75 | 16.59 | 10.78 | 25.73 | 82.73 | 26.09 |
Table 3 : Game state reconstruction on all twenty halves, each run and scored over the whole half and, independently, on its opening 30 seconds, the clip length of the SoccerNet-GSR benchmark: the game state reconstruction pipeline of Section 4.7 , configured by the authors on released footage that includes a test-split half and run end to end under one configuration, the per-detection team assignment. GS-HOTA is the official metric, which classes detections by (role, team, jersey); DetA, AssA and LocA are its detection, association and localisation components; Attrs off rescores the same predictions with attribute matching disabled, so that only geometry and association count (components in Supplementary Table 1 ). The test split of the released match-level split is marked . Means are unweighted means of the per-half scores in each column, computed from unrounded scores.
| Configuration | GS-HOTA | DetA | AssA | Marginal |
|---|---|---|---|---|
| Geometry and association only | 26.04 | 51.21 | 13.41 | ceiling |
| + role | 25.64 | 49.36 | 13.48 | |
| + role, team | 22.36 | 35.12 | 14.37 | |
| + role, team, jersey (official) | 18.09 | 14.67 | 22.32 |
Table 4 : Marginal cost of each game state attribute, computed on the first half of match M7 (the best-performing half of the test split in Table 3 ). GS-HOTA classes detections by the triple (role, team, jersey), so a detection with any incorrect attribute cannot match ground truth at all; each row switches one further attribute on, and Marginal is the incremental cost of enabling that attribute after those in the preceding row, computed from unrounded scores, so it may differ by from the difference of the displayed values. DetA and AssA are the detection and association components of the metric. The first row, with no attributes scored, is the ceiling available to the official metric: perfect attributes would score exactly this, so it carries no marginal cost.
Figure 4 : Game state reconstruction accuracy against the length scored. Filled markers: the whole-half predictions of every half (Table 3 ) scored over their first 30 seconds, 1, 2, 5 and 10 minutes and the whole half, mean over the twenty halves (Supplementary Table 2 ), under the official metric (black) and with attribute matching disabled (blue); the bands span the twenty halves. Hollow markers: the mean of the independent 30-second runs of Table 3 , in which the pipeline saw only the clip.
| s | s | ||||
| Input | Test fold | mAP | mAP w | mAP | mAP w |
| trajectory | M7, M9 (Challenge) | 0.207 | 0.202 | 0.472 | 0.637 |
| M1, M2 | 0.222 | 0.272 | 0.501 | 0.676 | |
| M3, M4 | 0.231 | 0.259 | 0.600 | 0.709 | |
| M5, M6 | 0.199 | 0.258 | 0.516 | 0.678 | |
| M8, M10 | 0.252 | 0.275 | 0.531 | 0.664 | |
Table 5 : Five-fold cross-match evaluation of the spotting model on the supplied trajectories. Each match appears in the test set exactly once; fold 0 is the SoccerTrack Challenge 2025 pair. Validation for each fold is the following fold’s test pair, so no fold’s decoding or stopping epoch is chosen on its own test matches; the network settings shared by all folds were fixed once on M2 and M10 (Section 4.9 ). Each entry is a single training run. The last block gives the two matches of the Challenge fold separately: the ball track is unclamped in M7 and clamped to the pitch rectangle in M9, so the value of the ball differs sharply between them and the fold’s pooled row averages two regimes.
| Class | chance | trajectory | +ball | |
|---|---|---|---|---|
| Pass | 9315 | 0.042 | 0.286 | 0.853 |
| Drive | 8255 | 0.036 | 0.227 | 0.830 |
| High Pass | 1157 | 0.007 | 0.320 | 0.745 |
| Out | 771 | 0.004 | 0.148 | 0.364 |
| Cross | 394 | 0.001 | 0.327 | 0.794 |
| Throw In | 385 | 0.006 | 0.254 | 0.910 |
Table 6 : Per-class average precision at s, pooled over the five cross-match folds and therefore over all ten matches. is the number of ground-truth events across the benchmark. Rows marked have . Classes are ordered by support. Because AP is pooled over matches, the column means differ slightly from the fold-averaged means of Table 5 .
Figure 5 : From released pixels to metric pitch coordinates, match M2, first half. (a) A frame of the released panoramic video: the stitched view is distorted and the pitch lines are curved. (b) The same frame after distortion correction, with the FIFA-standard pitch template and the frame’s annotated player positions (coloured by team side) projected into the image through a homography fitted on the hand-annotated pitch keypoints, shown over the pitch region with the boxed region enlarged below. (c) The same instant in the metric coordinate system of the annotations: a m pitch with the origin at the centre circle, the touchline nearer the camera at the bottom.
Figure 6 : The two baselines. (a) Game state reconstruction. White boxes are published components; highlighted elements mark our contributions: the calibration stage fitted from the hand-annotated keypoints, the relaxed jersey-region gate, the per-detection team-assignment variant compared with the original on nested prefixes (Section 4.7 ), and the four fixes that let the pipeline run at match length (Section 4.8 ). (b) Ball action spotting, every stage of which is ours (Section 4.9 ). Per-frame features computed from the supplied ground-truth player trajectories and sampled at , in four groups and optionally more from the ball track, pass through a non-causal temporal convolutional network: a pointwise projection to channels, six residual blocks with dilations to (receptive field ) and a pointwise projection to twelve per-frame logits. Independent sigmoids score each class, and per-class peak picking above a floor with within-class non-maximum suppression yields ranked spots per class.
| Half | DetA | AssA | LocA | Tracklets | Identities |
| First 30 s, all twenty halves | |||||
| M1, 1st | 21.60 | 35.39 | 73.05 | 24 | 22 |
| M1, 2nd | 25.33 | 39.19 | 73.59 | 27 | 22 |
| M2, 1st | 60.06 | 73.36 | 85.98 | 26 | 22 |
| M2, 2nd | 41.67 | 58.57 | 82.69 | 33 | 22 |
| M3, 1st | 57.79 | 66.38 | 85.65 | 25 | 22 |
Supplementary Table 1 : Components of the attributes-off scores of Table 3 : the same predictions rescored with attribute matching disabled, so that DetA, AssA and LocA measure geometry and association alone; Tracklets is the number of predicted identities and Identities the number of annotated identities in the sequence, substitutes included. The upper block is the opening 30 seconds of every half; the lower block is the full half of the same halves. Configuration is as in that table; the released test split is marked . Means are per column within each block, computed from unrounded scores.
| Half | 30 s | 1 min | 2 min | 5 min | 10 min | 20 min | Whole half |
|---|---|---|---|---|---|---|---|
| Official GS-HOTA | |||||||
| M1, 1st | 14.28 | 10.70 | 8.18 | 8.60 | 6.32 | 6.39 | 6.68 |
| M1, 2nd | 9.90 | 7.08 | 5.48 | 5.77 | 3.92 | 4.14 | 3.60 |
| M2, 1st | 29.15 | 21.02 | 17.24 | 17.44 | 16.87 | 17.01 | 14.28 |
| M2, 2nd | 25.45 | 25.33 | 23.47 | 26.12 | 20.70 | 16.99 | 12.13 |
| M3, 1st | 32.19 | 29.11 | 29.82 | 21.39 | 17.31 | 17.16 | 16.59 |
Supplementary Table 2 : GS-HOTA of the whole-half predictions of Table 3 scored over growing windows from kickoff: the first 30 seconds, 1, 2, 5, 10 and 20 minutes, and the whole half (Methods). The predictions are fixed and only the scored window changes, so the last column reproduces Table 3 . The upper block is the official metric, the lower block the same windows with attribute matching disabled. Means are per column, computed from unrounded scores; the released test split is marked .