Adam D. Bull
- Artificial Intelligence
- Computational Theory and Mathematics top 10%
- Management Science and Operations Research top 10%
- Statistics and Probability top 10%
- Statistics, Probability and Uncertainty top 10%
- Co-authors
- Richard NicklMark Roberts
- Topics
- Sports Analytics and Performance (3 papers)Financial Markets and Investment Strategies (2 papers)Statistical Methods and Inference (2 papers)
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchComputational Theory and Mathematics
- Journals
- The Annals of StatisticsJournal of Machine Learning ResearchProbability Theory and Related Fields
- Partner nations
- United KingdomUnited States
In The Last Decade
Adam D. Bull
10 papers receiving 233 citations
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 86
- Computational Theory and Mathematics 63
- Management Science and Operations Research 58
- Statistics and Probability 47
- Statistics, Probability and Uncertainty 27
Countries citing papers authored by Adam D. Bull
This map shows the geographic impact of Adam D. Bull's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Adam D. Bull with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adam D. Bull more than expected).
Fields of papers citing papers by Adam D. Bull
This network shows the impact of papers produced by Adam D. Bull. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Adam D. Bull. The network helps show where Adam D. Bull may publish in the future.
Co-authorship network of co-authors of Adam D. Bull
This figure shows the co-authorship network connecting the top 25 collaborators of Adam D. Bull. A scholar is included among the top collaborators of Adam D. Bull based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Adam D. Bull. Adam D. Bull is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 1 | |
| 3 | 7 | |
| 4 | 5 | |
| 5 | 32 | |
| 6 | 17 | |
| 7 | 164 | |
| 8 | Annual Review of Football Finance: pressure to change | 1 |
| 9 | Annual Review of Football Finance: national interest | 2 |
| 10 | Annual Review of Football Finance: safety in numbers | 3 |
About Adam D. Bull
Adam D. Bull is a scholar working on Finance, Statistics and Probability and Numerical Analysis, having authored 10 papers that have together received 243 indexed citations. Recurring topics across this work include Sports Analytics and Performance (3 papers), Financial Markets and Investment Strategies (2 papers) and Statistical Methods and Inference (2 papers). The work is most often cited by research in Statistics and Probability (47 citations), Management Science and Operations Research (58 citations) and Computational Theory and Mathematics (63 citations). Adam D. Bull has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Richard Nickl and Mark Roberts. Their work appears in journals such as The Annals of Statistics, Journal of Machine Learning Research and Probability Theory and Related Fields.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.