{"url":"/dataset/esports-sensors-dataset","name":"eSports Sensors Dataset","full_name":null,"description_markdown":"The eSports Sensors dataset contains sensor data collected from 10 players in 22 matches in League of Legends. The sensor data collected includes:\r\n\r\n* Hand/head/chair movements.\r\n* Heart rate.\r\n* Muscle activity.\r\n* Gaze movement on the monitor.\r\n* Galvanic skin response(GSR).\r\n* Electroencephalography (EEG).\r\n* Mouse and keyboard activity.\r\n* Facial skin temperature.\r\n* Environmental data.\r\n\r\nThe data were collected for one team of 5 people simultaneously. In-game logs and meta information for each match are also provided for each match.\r\n\r\nSource: [https://github.com/smerdov/eSports_Sensors_Dataset](https://github.com/smerdov/eSports_Sensors_Dataset)","description_withheld":null,"homepage":"https://github.com/smerdov/eSports_Sensors_Dataset","introduced_date":"2020-11-02","introduced_date_note":null,"introduced_by":{"paper":"/paper/collection-and-validation-of","title":"Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset","first_author":"Anton Smerdov","url":null},"license":{"name":"https://github.com/smerdov/eSports_Sensors_Dataset/blob/master/LICENSE","url":"https://github.com/smerdov/eSports_Sensors_Dataset/blob/master/LICENSE"},"modalities":[{"name":"Biomedical","url":"/datasets/modality/biomedical"},{"name":"Tabular","url":"/datasets/modality/tabular"},{"name":"Environment","url":"/datasets/modality/environment"},{"name":"Time series","url":"/datasets/modality/time-series"},{"name":"6D","url":"/datasets/modality/6d"},{"name":"Replay data","url":"/datasets/modality/replay-data"},{"name":"Actions","url":"/datasets/modality/actions"},{"name":"Tracking","url":"/datasets/modality/tracking"},{"name":"EEG","url":"/datasets/modality/eeg"}],"tasks":[{"name":"Time Series Analysis","url":"/task/time-series","datasets_with_task":"/datasets/task/time-series"},{"name":"Person Re-Identification","url":"/task/person-re-identification","datasets_with_task":"/datasets/task/person-re-identification"},{"name":"Real-Time Strategy Games","url":"/task/real-time-strategy-games","datasets_with_task":"/datasets/task/real-time-strategy-games"},{"name":"Skills Assessment","url":"/task/skills-assessment","datasets_with_task":"/datasets/task/skills-assessment"},{"name":"Skills Evaluation","url":"/task/skills-evaluation","datasets_with_task":"/datasets/task/skills-evaluation"},{"name":"Sensor Modeling","url":"/task/sensor-modeling","datasets_with_task":"/datasets/task/sensor-modeling"},{"name":"Physiological Computing","url":"/task/physiological-computing","datasets_with_task":"/datasets/task/physiological-computing"}],"languages":[],"variants":["eSports Sensors Dataset"],"data_loaders":[{"repo":"https://github.com/smerdov/eSports_Sensors_Dataset","url":"https://github.com/smerdov/eSports_Sensors_Dataset","frameworks":[]}],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/person-re-identification-on-esports-sensors","task":"Person Re-Identification","dataset_variant":"eSports Sensors Dataset","rows":5,"metrics":["Accuracy","LogLoss","ROC AUC"],"first_row_in_archive_order":{"model":"Random Forest","paper":"/paper/collection-and-validation-of","metrics":{"Accuracy":"52.1","LogLoss":"0.01617","ROC AUC":"0.919"},"code_links":[{"title":"smerdov/eSports_Sensors_Dataset","url":"https://github.com/smerdov/eSports_Sensors_Dataset"},{"title":"asmerdov/DataCollectionSystem","url":"https://github.com/asmerdov/DataCollectionSystem"},{"title":"smerdov/DataCollectionSystem","url":"https://github.com/smerdov/DataCollectionSystem"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/skills-evaluation-on-esports-sensors-dataset","task":"Skills Evaluation","dataset_variant":"eSports Sensors Dataset","rows":5,"metrics":["Accuracy","LogLoss","ROC AUC"],"first_row_in_archive_order":{"model":"SVM","paper":"/paper/collection-and-validation-of","metrics":{"Accuracy":"85.6","LogLoss":"0.311","ROC AUC":"0.945"},"code_links":[{"title":"smerdov/eSports_Sensors_Dataset","url":"https://github.com/smerdov/eSports_Sensors_Dataset"},{"title":"asmerdov/DataCollectionSystem","url":"https://github.com/asmerdov/DataCollectionSystem"},{"title":"smerdov/DataCollectionSystem","url":"https://github.com/smerdov/DataCollectionSystem"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/collection-and-validation-of","title":"Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset","date":"2020-11-02","rows_on_this_dataset":10,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}