Please use this identifier to cite or link to this item:
http://localhost/handle/Hannan/4702
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor | Madjid Tavana | - |
dc.contributor | Farshad Azizi | - |
dc.contributor | Farzad Azizi | - |
dc.contributor | Majid Behzadian | - |
dc.date.accessioned | 2023-05-01T09:09:07Z | - |
dc.date.available | 2023-05-01T09:09:07Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.issn | https://doi.org/10.1016/j.smr.2012.06.002 | - |
dc.identifier.uri | http://localhost/handle/Hannan/4702 | - |
dc.description.abstract | The success or failure of any team lies in the skills and abilities of the players that comprise the team. The process of player selection and team formation in multi-player sports is a complex multi-criteria problem where the ultimate success is determined by how the collection of individual players forms an effective team. In general, the selection of soccer players and formation of a team are judgments made by the coaches on the basis of the best available information. Very few structured and analytical models have been developed to support coaches in this effort. We propose a two-phase framework for player selection and team formation in soccer. The first phase evaluates the alternative players with a fuzzy ranking method and selects the top performers for inclusion in the team. The second phase evaluates the alternative combinations of the selected players with a Fuzzy Inference System (FIS) and selects the best combinations for team formation. A case study is used to illustrate the performance of the proposed approach. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Fuzzy inference system, Fuzzy sets and logic, Player selection, Team formation, Soccer | en_US |
dc.title | A fuzzy inference system with application to player selection and team formation | - |
dc.type | Article | en_US |
Appears in Collections: | تمامی گرایش های مدیریت شامل مدیریت بازرگانی و صنعتی |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
1.pdf | 1.26 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor | Madjid Tavana | - |
dc.contributor | Farshad Azizi | - |
dc.contributor | Farzad Azizi | - |
dc.contributor | Majid Behzadian | - |
dc.date.accessioned | 2023-05-01T09:09:07Z | - |
dc.date.available | 2023-05-01T09:09:07Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.issn | https://doi.org/10.1016/j.smr.2012.06.002 | - |
dc.identifier.uri | http://localhost/handle/Hannan/4702 | - |
dc.description.abstract | The success or failure of any team lies in the skills and abilities of the players that comprise the team. The process of player selection and team formation in multi-player sports is a complex multi-criteria problem where the ultimate success is determined by how the collection of individual players forms an effective team. In general, the selection of soccer players and formation of a team are judgments made by the coaches on the basis of the best available information. Very few structured and analytical models have been developed to support coaches in this effort. We propose a two-phase framework for player selection and team formation in soccer. The first phase evaluates the alternative players with a fuzzy ranking method and selects the top performers for inclusion in the team. The second phase evaluates the alternative combinations of the selected players with a Fuzzy Inference System (FIS) and selects the best combinations for team formation. A case study is used to illustrate the performance of the proposed approach. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Fuzzy inference system, Fuzzy sets and logic, Player selection, Team formation, Soccer | en_US |
dc.title | A fuzzy inference system with application to player selection and team formation | - |
dc.type | Article | en_US |
Appears in Collections: | تمامی گرایش های مدیریت شامل مدیریت بازرگانی و صنعتی |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
1.pdf | 1.26 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor | Madjid Tavana | - |
dc.contributor | Farshad Azizi | - |
dc.contributor | Farzad Azizi | - |
dc.contributor | Majid Behzadian | - |
dc.date.accessioned | 2023-05-01T09:09:07Z | - |
dc.date.available | 2023-05-01T09:09:07Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.issn | https://doi.org/10.1016/j.smr.2012.06.002 | - |
dc.identifier.uri | http://localhost/handle/Hannan/4702 | - |
dc.description.abstract | The success or failure of any team lies in the skills and abilities of the players that comprise the team. The process of player selection and team formation in multi-player sports is a complex multi-criteria problem where the ultimate success is determined by how the collection of individual players forms an effective team. In general, the selection of soccer players and formation of a team are judgments made by the coaches on the basis of the best available information. Very few structured and analytical models have been developed to support coaches in this effort. We propose a two-phase framework for player selection and team formation in soccer. The first phase evaluates the alternative players with a fuzzy ranking method and selects the top performers for inclusion in the team. The second phase evaluates the alternative combinations of the selected players with a Fuzzy Inference System (FIS) and selects the best combinations for team formation. A case study is used to illustrate the performance of the proposed approach. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Fuzzy inference system, Fuzzy sets and logic, Player selection, Team formation, Soccer | en_US |
dc.title | A fuzzy inference system with application to player selection and team formation | - |
dc.type | Article | en_US |
Appears in Collections: | تمامی گرایش های مدیریت شامل مدیریت بازرگانی و صنعتی |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
1.pdf | 1.26 MB | Adobe PDF | Preview File |