Fabian Wunderlich
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Fabian Wunderlich has a total of 28 co-authors. Here are the top co-authors by number of shared publications:
- Daniel Memmert
Institute of Exercise Training and Sport Informatics, German Sport University Cologne, Cologne, Germany
13 shared publications Daniel Memmert
6 shared publications- Philip Furley
German Sport University, Cologne, Germany
3 shared publications Alessandro Seck
German Sport University Cologne
2 shared publications- Marc Garnica Caparrós
German Sport University Cologne
2 shared publications Robert Rein
German Sports University Cologne, Cologne, Germany
2 shared publications
Latest Publications
- Open Access
- 30 October 2026
- Published by Springer Nature in Psychological Research
- Vol. 90 (6) , 195
Trusting the AI rather than the expert? Evidence from sports-related assessments in relation to the Olympic Games 2024
We investigated how predictions regarding the outcome of sports competitions are affected by concurrent predictions which were believed to originate from either a human sports expert or an AI system. Participants were asked to estimate the probability of a certain team to win a group match against the respective opponent in various matches of the 2024 Olympic Games and to report their confidence in that estimate. Moreover, they received numerical estimates for that probability which were either high or low, and which were believed to originate from a human expert or an AI system. Participants’ estimates were biased towards these supplementary estimates, thus reflecting an anchoring effect. Yet, this effect’s size was independent of the believed source of the anchor and even non-significantly higher for AI support. Confidence in provided judgments was even significantly higher when the believed origin of supplementary estimates was AI rather than human. Altogether, the results suggest no bias against AI-generated sports outcome predictions, highlighting the task-dependency of reliance on AI.
- 30 October 2026
- Published by Springer Nature in Psychological Research
- Vol. 90 (6) , 195
Open AccessTrusting the AI rather than the expert? Evidence from sports-related assessments in relation to the Olympic Games 2024
We investigated how predictions regarding the outcome of sports competitions are affected by concurrent predictions which were believed to originate from either a human sports expert or an AI system. Participants were asked to estimate the probability of a certain team to win a group match against the respective opponent in various matches of the 2024 Olympic Games and to report their confidence in that estimate. Moreover, they received numerical estimates for that probability which were either high or low, and which were believed to originate from a human expert or an AI system. Participants’ estimates were biased towards these supplementary estimates, thus reflecting an anchoring effect. Yet, this effect’s size was independent of the believed source of the anchor and even non-significantly higher for AI support. Confidence in provided judgments was even significantly higher when the believed origin of supplementary estimates was AI rather than human. Altogether, the results suggest no bias against AI-generated sports outcome predictions, highlighting the task-dependency of reliance on AI.
- Open Access
- 8 October 2026
- Published by Elsevier in Psychology of Sport and Exercise
- Vol. 88
Studying trust in AI in sports: An interdisciplinary primer
- 8 October 2026
- Published by Elsevier in Psychology of Sport and Exercise
- Vol. 88
Open AccessStudying trust in AI in sports: An interdisciplinary primer
- Open Access
- 23 April 2026
- Published by Elsevier in International Journal of Forecasting
- Vol. 42 (4) , 1123-1134
Does the consideration of market prices in model selection increase model profitability? Evidence from theory, artificial data and real-world data
- 23 April 2026
- Published by Elsevier in International Journal of Forecasting
- Vol. 42 (4) , 1123-1134
Open AccessDoes the consideration of market prices in model selection increase model profitability? Evidence from theory, artificial data and real-world data
- Open Access
- 22 July 2025
- Published by Springer Nature in Psychological Research
- Vol. 89 (4) , 1-11
The perils of the first try: experimental evidence for visuomotor calibration in darts and hammering
Task such as hammering or throwing darts involve intentional actions performed with the anticipation of a desired effect that requires precision to achieve success. Visual perception of the goal, defined in an external frame of reference, plays a crucial role in specifying movement parameters in a body-centered frame of reference. Physical interruption of the task decouples the internal and external frames of reference leading to rapid performance decrements. Motor calibration, as noted by the ‘Calibration Effect’, is the fine-tuning of motor commands following performance-related feedback in the external frame of reference. Here we test the calibration effect with non-skilled populations in both a sport specific and an everyday type of task, darts and hammering. Participants performed 20 rounds of five attempts of hitting a goal with a stable bodily position. Between rounds they moved around to perturb the fine tuning. The first repetition within a round of repeated attempts was less accurate than the subsequent attempts within that same round, even if controlling for gradual learning effects. Thus, the calibration effect, a rapid component of warm-up, is present both in professional athletes and unskilled dart players as well as in everyday activities such as hammering.
- 22 July 2025
- Published by Springer Nature in Psychological Research
- Vol. 89 (4) , 1-11
Open AccessThe perils of the first try: experimental evidence for visuomotor calibration in darts and hammering
Task such as hammering or throwing darts involve intentional actions performed with the anticipation of a desired effect that requires precision to achieve success. Visual perception of the goal, defined in an external frame of reference, plays a crucial role in specifying movement parameters in a body-centered frame of reference. Physical interruption of the task decouples the internal and external frames of reference leading to rapid performance decrements. Motor calibration, as noted by the ‘Calibration Effect’, is the fine-tuning of motor commands following performance-related feedback in the external frame of reference. Here we test the calibration effect with non-skilled populations in both a sport specific and an everyday type of task, darts and hammering. Participants performed 20 rounds of five attempts of hitting a goal with a stable bodily position. Between rounds they moved around to perturb the fine tuning. The first repetition within a round of repeated attempts was less accurate than the subsequent attempts within that same round, even if controlling for gradual learning effects. Thus, the calibration effect, a rapid component of warm-up, is present both in professional athletes and unskilled dart players as well as in everyday activities such as hammering.
- 22 July 2025
- Published by Springer Nature
- p. 295-305
Responsible Use of Machine Learning in Sports Science
- 22 July 2025
- Published by Springer Nature
- p. 295-305
Responsible Use of Machine Learning in Sports Science
- 17 June 2025
- Published by Springer Nature
- p. 343-355
Verantwortungsvoller Einsatz von maschinellem Lernen in der Sportwissenschaft
- 17 June 2025
- Published by Springer Nature
- p. 343-355
Verantwortungsvoller Einsatz von maschinellem Lernen in der Sportwissenschaft
- 28 January 2025
- Published by Springer Nature in Machine Learning
- Vol. 114 (2) , 1-28
Assessing machine learning and data imputation approaches to handle the issue of data sparsity in sports forecasting
- 28 January 2025
- Published by Springer Nature in Machine Learning
- Vol. 114 (2) , 1-28
Assessing machine learning and data imputation approaches to handle the issue of data sparsity in sports forecasting
- 19 December 2024
- Published by Taylor & Francis in International Journal of Performance Analysis in Sport
- Vol. 25 (4) , 687-706
Using the wisdom of crowds in sports: how performance analysis in football can benefit from the information enclosed in betting odds
- 19 December 2024
- Published by Taylor & Francis in International Journal of Performance Analysis in Sport
- Vol. 25 (4) , 687-706
Using the wisdom of crowds in sports: how performance analysis in football can benefit from the information enclosed in betting odds
- 6 March 2024
- Published by Springer Nature
- p. 65-72
Predictive Models