Pascal Bauer
Biographic Data
| ID | 3746440 |
|---|---|
| NAME | Pascal Bauer |
| GIVEN NAMES | Pascal |
| FAMILY NAME | Bauer |
| SIGNATURE | BAUER P |
| AFFILIATIONS | University of Tübingen |
| ORCID | 0000-0001-8613-6635 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 7 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 1 |
A Goal Scoring Probability Model for Shots Based on Synchronized Positional and Event Data in Football (Soccer)
Due to the low scoring nature of football (soccer), shots are often used as a proxy to evaluate team and player performances. However, not all shots are created equally and their quality differs significantly depending on the situation. The aim of this study is to objectively quantify the quality of any given shot by introducing a so-called expected goals (xG) model. This model is validated statistically and with professional match analysts. The …
Toward Automatically Labeling Situations in Soccer
We study the automatic annotation of situations in soccer games. At first sight, this translates nicely into a standard supervised learning problem. However, in a fully supervised setting, predictive accuracies are supposed to correlate positively with the amount of labeled situations: more labeled training data simply promise better performance. Unfortunately, non-trivially annotated situations in soccer games are scarce, expensive and almost al…
A Goal Scoring Probability Model for Shots Based on Synchronized Positional and Event Data in Football (Soccer)
Due to the low scoring nature of football (soccer), shots are often used as a proxy to evaluate team and player performances. However, not all shots are created equally and their quality differs significantly depending on the situation. The aim of this study is to objectively quantify the quality of any given shot by introducing a so-called expected goals (xG) model. This model is validated statistically and with professional match analysts. The …
A Goal Scoring Probability Model for Shots Based on Synchronized Positional and Event Data in Football (Soccer)
Due to the low scoring nature of football (soccer), shots are often used as a proxy to evaluate team and player performances. However, not all shots are created equally and their quality differs significantly depending on the situation. The aim of this study is to objectively quantify the quality of any given shot by introducing a so-called expected goals (xG) model. This model is validated statistically and with professional match analysts. The …
Toward Automatically Labeling Situations in Soccer
We study the automatic annotation of situations in soccer games. At first sight, this translates nicely into a standard supervised learning problem. However, in a fully supervised setting, predictive accuracies are supposed to correlate positively with the amount of labeled situations: more labeled training data simply promise better performance. Unfortunately, non-trivially annotated situations in soccer games are scarce, expensive and almost al…
Artificial Intelligence (2 works) · Computer Science (2 works) · Machine learning (2 works) · Sports Analytics and Performance (2 works) · Annotation (1 works) · Artificial neural network (1 works) · Autoencoder (1 works) · Boosting (machine learning (1 works) · Classifier (UML (1 works) · Data mining (1 works)