Technical and Tactical Command Decision Algorithm of Football Matches Based on Big Data and Neural Network

A successful football team not only consists of more than a dozen people on the field but also includes a complete training, analysis, coaching team behind it, and the same basic education and youth training system. With the development of scientific concepts and the advancement of computer technolo...

Full description

Saved in:
Bibliographic Details
Published inScientific programming Vol. 2021; pp. 1 - 9
Main Authors Fang, Lei, Wei, Qiang, Xu, Cheng Jian
Format Journal Article
LanguageEnglish
Published New York Hindawi 2021
John Wiley & Sons, Inc
Subjects
Online AccessGet full text
ISSN1058-9244
1875-919X
DOI10.1155/2021/5544071

Cover

Loading…
Abstract A successful football team not only consists of more than a dozen people on the field but also includes a complete training, analysis, coaching team behind it, and the same basic education and youth training system. With the development of scientific concepts and the advancement of computer technology, more people have begun to study the use of modern technology to replace part of the traditional human work with low creativity and the use of more convenient quantitative analysis, prediction and other technologies to assist football professionals’ decision-making. Based on big data and neural network technology, this paper has designed a novel football technical and tactical command decision algorithm. First, the use of big data technology for analyzing the characteristics of the historical big data of football competitions provides valuable data for the work of this article. Secondly, to formulate scientific and reasonable football technical and tactical command, it requires learning effective offensive or defensive strategies from the big data of football competitions. This article uses deep neural networks to learn massive amounts of football competition data, which can effectively predict the offensive and defensive tactics of each position of the team to a certain extent. In addition, in order to better learn the timing video data of football matches, this paper also has proposed to use long- and short-term memory networks to improve the algorithm of this paper. The proposed method has achieved good results in football technical and tactical command and decision-making and also provides some new ideas for the subject of football combined with computer technology.
AbstractList A successful football team not only consists of more than a dozen people on the field but also includes a complete training, analysis, coaching team behind it, and the same basic education and youth training system. With the development of scientific concepts and the advancement of computer technology, more people have begun to study the use of modern technology to replace part of the traditional human work with low creativity and the use of more convenient quantitative analysis, prediction and other technologies to assist football professionals’ decision-making. Based on big data and neural network technology, this paper has designed a novel football technical and tactical command decision algorithm. First, the use of big data technology for analyzing the characteristics of the historical big data of football competitions provides valuable data for the work of this article. Secondly, to formulate scientific and reasonable football technical and tactical command, it requires learning effective offensive or defensive strategies from the big data of football competitions. This article uses deep neural networks to learn massive amounts of football competition data, which can effectively predict the offensive and defensive tactics of each position of the team to a certain extent. In addition, in order to better learn the timing video data of football matches, this paper also has proposed to use long- and short-term memory networks to improve the algorithm of this paper. The proposed method has achieved good results in football technical and tactical command and decision-making and also provides some new ideas for the subject of football combined with computer technology.
Author Fang, Lei
Xu, Cheng Jian
Wei, Qiang
Author_xml – sequence: 1
  givenname: Lei
  surname: Fang
  fullname: Fang, Lei
  organization: Northwest University for NationalitiesLanzhou 730124GansuChinaxbmu.edu.cn
– sequence: 2
  givenname: Qiang
  surname: Wei
  fullname: Wei, Qiang
  organization: Department of Physical EducationTangshan Normal UniversityTangshanChina
– sequence: 3
  givenname: Cheng Jian
  orcidid: 0000-0001-6879-0799
  surname: Xu
  fullname: Xu, Cheng Jian
  organization: Department of Competitive SportsGuangdong Sports Vocational and Technical CollegeGuangzhou 510663GuangdongChina
BookMark eNp9kMlOwzAURS1UJNrCjg-wxBICHuNk2YECUimbIrGLXMdpXNK42K4q_h53WCHB6g069z692wOd1rYagGuM7jHm_IEggh84ZwwJfAa6OBM8yXH-0Yk94lmSE8YuQM_7FUI4wwh1wWquVd0aJRso2xLOpQqHYWTX6_1irJXxxrZw0CytM6FeQ1vBibVhIZsGvsqgau3hUHpdwogNzRKOZZAHt5neuug102Fn3eclOK9k4_XVqfbB--RxPnpOpm9PL6PBNFGUipDolMhcLXIh1IJglildKsHSPNUlzXVWVqoUiGpOiNKSVlVKI15yUiHKBOOU9sHN0Xfj7NdW-1Cs7Na18WRBOGaYC4J5pMiRUs5673RVKBNkiK8GJ01TYFTsMy32mRanTKPo7pdo48xauu-_8NsjXpu2lDvzP_0DdFSFmQ
CitedBy_id crossref_primary_10_1155_2022_9502218
crossref_primary_10_1155_2022_3897180
crossref_primary_10_1155_2022_8091838
crossref_primary_10_1080_02640414_2024_2383065
crossref_primary_10_2478_amns_2023_2_01415
crossref_primary_10_3389_fpls_2023_1102855
Cites_doi 10.2478/hukin-2019-0084
10.1519/jsc.0000000000002147
10.1111/1467-9884.00108
10.1016/j.neucom.2020.05.106
10.1109/lsp.2020.3032277
10.1123/jsm.2019-0308
10.1109/access.2020.2979348
10.1080/24748668.2020.1726158
10.1109/access.2020.3005189
10.1109/access.2020.2986267
10.1002/cpe.6276
10.30492/ijcce.2005.8108
10.1080/17461391.2020.1845814
10.1109/tip.2018.2806229
10.1109/TIFS.2020.3023279
10.1111/j.1478-4408.2000.tb00035.x
10.1109/tcsvt.2020.3043026
10.1109/lgrs.2020.3026587
ContentType Journal Article
Copyright Copyright © 2021 Lei Fang et al.
Copyright © 2021 Lei Fang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
Copyright_xml – notice: Copyright © 2021 Lei Fang et al.
– notice: Copyright © 2021 Lei Fang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
DBID RHU
RHW
RHX
AAYXX
CITATION
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
DOI 10.1155/2021/5544071
DatabaseName Hindawi Publishing Complete
Hindawi Publishing Subscription Journals
Hindawi Publishing Open Access
CrossRef
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
DatabaseTitle CrossRef
Technology Research Database
Computer and Information Systems Abstracts – Academic
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts Professional
DatabaseTitleList Technology Research Database
CrossRef

Database_xml – sequence: 1
  dbid: RHX
  name: Hindawi Publishing Open Access
  url: http://www.hindawi.com/journals/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 1875-919X
Editor Nazir, Shah
Editor_xml – sequence: 1
  givenname: Shah
  surname: Nazir
  fullname: Nazir, Shah
EndPage 9
ExternalDocumentID 10_1155_2021_5544071
GrantInformation_xml – fundername: Social Science Development Research Project of Hebei Province
  grantid: 20200502100
GroupedDBID .4S
.DC
0R~
4.4
5VS
AAFWJ
AAJEY
ABDBF
ABJNI
ACGFS
ADBBV
AENEX
ALMA_UNASSIGNED_HOLDINGS
ARCSS
ASPBG
AVWKF
BCNDV
DU5
EAD
EAP
EBS
EDO
EMK
EPL
EST
ESX
GROUPED_DOAJ
HZ~
I-F
IAO
IHR
IOS
KQ8
MIO
MK~
ML~
MV1
NGNOM
O9-
OK1
RHU
RHW
RHX
TUS
24P
AAYXX
ACCMX
CITATION
H13
7SC
7SP
8FD
AAMMB
AEFGJ
AGXDD
AIDQK
AIDYY
JQ2
L7M
L~C
L~D
ID FETCH-LOGICAL-c337t-e62a9cb977cb2148cedc74696ed39e8dfcd703e522cea3ff63a9cd52f03474533
IEDL.DBID RHX
ISSN 1058-9244
IngestDate Fri Jul 25 09:31:11 EDT 2025
Thu Apr 24 23:01:39 EDT 2025
Tue Jul 01 02:50:04 EDT 2025
Sun Jun 02 19:18:03 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Language English
License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
https://creativecommons.org/licenses/by/4.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c337t-e62a9cb977cb2148cedc74696ed39e8dfcd703e522cea3ff63a9cd52f03474533
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0001-6879-0799
OpenAccessLink https://dx.doi.org/10.1155/2021/5544071
PQID 2514157215
PQPubID 2046410
PageCount 9
ParticipantIDs proquest_journals_2514157215
crossref_citationtrail_10_1155_2021_5544071
crossref_primary_10_1155_2021_5544071
hindawi_primary_10_1155_2021_5544071
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2021-00-00
PublicationDateYYYYMMDD 2021-01-01
PublicationDate_xml – year: 2021
  text: 2021-00-00
PublicationDecade 2020
PublicationPlace New York
PublicationPlace_xml – name: New York
PublicationTitle Scientific programming
PublicationYear 2021
Publisher Hindawi
John Wiley & Sons, Inc
Publisher_xml – name: Hindawi
– name: John Wiley & Sons, Inc
References 23
Z. Wang (30)
26
S. M. Arabzad (25) 2014; 1
27
Z. L. Yang (16) 2020; 16
T. Reilly (22) 2013; 23
J. Lee (34)
J. Perl (21) 2013; 12
D. Krzysztof (18) 2014; 4
W. Cai (12) 2021
10
32
11
H. Li (28) 2020; 24
13
14
17
M. A. Russo (31)
M. Michalls (19) 2019; 19
Y. C. Huang (33)
2
3
D. Memmert (1) 2019; 33
4
6
7
8
R. Izzo (5) 2020; 13
9
S. Booth (29) 2020
20
W. Cai (15) 2019
L. R. Medsker (24) 2001; 5
References_xml – volume: 1
  start-page: 159
  issue: 3
  year: 2014
  ident: 25
  article-title: Football match results prediction using artificial neural networks; the case of Iran Pro League
  publication-title: Journal of Applied Research on Industrial Engineering
– ident: 20
  doi: 10.2478/hukin-2019-0084
– volume: 23
  issue: 6
  year: 2013
  ident: 22
  article-title: International research in sports and exercise science including physiology, psychology, sports medicine and biomechanics, coaching and talent identification
  publication-title: Journal of Sports Sciences
– ident: 2
  doi: 10.1519/jsc.0000000000002147
– ident: 23
  doi: 10.1111/1467-9884.00108
– year: 2020
  ident: 29
  article-title: Sampling prediction-matching examples in neural networks: a probabilistic programming approach
– ident: 11
  doi: 10.1016/j.neucom.2020.05.106
– ident: 9
  doi: 10.1109/lsp.2020.3032277
– volume: 13
  start-page: 30
  issue: 1
  year: 2020
  ident: 5
  article-title: The role of fatigue in football matches, performance model analysis and evaluation during quarters using live global positioning system technology at 50 Hz
  publication-title: Sport Science
– volume: 33
  start-page: 574
  year: 2019
  ident: 1
  article-title: Data analytics in football: positional data collection, modeling, and analysis
  publication-title: Journal of Sport Management
  doi: 10.1123/jsm.2019-0308
– volume: 12
  year: 2013
  ident: 21
  article-title: Tactics analysis in soccer–an advanced approach
  publication-title: Dshs
– volume: 5
  year: 2001
  ident: 24
  article-title: Recurrent neural networks
  publication-title: Design and Applications
– ident: 8
  doi: 10.1109/access.2020.2979348
– ident: 4
  doi: 10.1080/24748668.2020.1726158
– ident: 32
  doi: 10.1109/access.2020.3005189
– year: 2019
  ident: 15
  article-title: Diversity-generated image inpainting with style extraction
– start-page: 1
  ident: 33
  article-title: TrackNet: a deep learning network for tracking high-speed and tiny objects in sports applications
– start-page: 1
  year: 2021
  ident: 12
  article-title: TARDB-Net: triple-attention guided residual dense and BiLSTM networks for hyperspectral image classification
  publication-title: Multimedia Tools and Applications
– ident: 14
  doi: 10.1109/access.2020.2986267
– ident: 17
  doi: 10.1002/cpe.6276
– ident: 26
  doi: 10.30492/ijcce.2005.8108
– start-page: 1161
  ident: 34
  article-title: A study on sports player tracking based on video using deep learning
– ident: 3
  doi: 10.1080/17461391.2020.1845814
– volume: 24
  start-page: 1
  year: 2020
  ident: 28
  article-title: Analysis on the construction of sports match prediction model using neural network
  publication-title: Soft Computing
– ident: 13
  doi: 10.1109/tip.2018.2806229
– volume: 16
  start-page: 880
  year: 2020
  ident: 16
  article-title: VAE-Stega: linguistic steganography based on variational auto-encoder
  publication-title: IEEE Transactions on Information Forensics and Security
  doi: 10.1109/TIFS.2020.3023279
– volume: 4
  start-page: 47
  issue: 5
  year: 2014
  ident: 18
  article-title: Analysis of goals and assists diversity in English premier league
  publication-title: Journal of Health Sciences
– ident: 27
  doi: 10.1111/j.1478-4408.2000.tb00035.x
– start-page: 1
  ident: 31
  article-title: Classification of sports videos with combination of deep learning models and transfer learning
– ident: 7
  doi: 10.1109/tcsvt.2020.3043026
– ident: 6
– ident: 10
  doi: 10.1109/lgrs.2020.3026587
– start-page: 499
  ident: 30
  article-title: Effective and efficient sports play retrieval with deep representation learning
– volume: 19
  start-page: 452
  issue: 3
  year: 2019
  ident: 19
  article-title: The creation of goal scoring opportunities in professional soccer
  publication-title: International Journal of Performance Analysis in Sport
SSID ssj0018100
Score 2.2506535
Snippet A successful football team not only consists of more than a dozen people on the field but also includes a complete training, analysis, coaching team behind it,...
SourceID proquest
crossref
hindawi
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 1
SubjectTerms Algorithms
Artificial neural networks
Big Data
Cooperation
Decision analysis
Decision making
Football
Machine learning
Neural networks
Performance evaluation
Professionals
Soccer
Tactics
Technology assessment
Technology utilization
Training
Video data
Title Technical and Tactical Command Decision Algorithm of Football Matches Based on Big Data and Neural Network
URI https://dx.doi.org/10.1155/2021/5544071
https://www.proquest.com/docview/2514157215
Volume 2021
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LS8NAEB5sQfDiW6zWsod6kmCT3U2aY2stRWjx0EJvIdlHW4mN2Ih_39lkU9AiesuG2T3M7Ox83z5mANqu9ISnOHUwmkuH8ZA6IVXK8ViiAiEEQnKzDzme-KMZe5rzuU2StNk9wsdoZ-i5e49Rz1CPGtRwghlSPppvDwu6bqdMOsDRdzFcVffbf_T9Fnn2l4byfq52luAirgyP4dACQtIrLXgCe2p9CkdVsQVife8MXopNcKNSguSfTIvHTdgwLzzMj4EtlkN66SJDxr98JZkmwyzLkzhNyTg25tmQPkYtSVCsv1qQQZzHxWgmRQeONSnvhJ_DbPg4fRg5tlCCIygNckf5XhyKBKGcSDzkN0JJESDv9ZWkoepKLSQ6tkKoJVRMtfYpikvu6Q5lAUPAdwH1dbZWl0B87TIUoXHX1cwNNK6F2Cvw8UOHVPIG3FVKjITNIm6KWaRRwSY4j4zKI6vyBtxupd_K7Bm_yLWtPf4Qa1bGiqyrbSIEaAhCkMjyq_-Ncg0HplnuozShnr9_qBtEFnnSgprHnlvF7PoC1qnETQ
linkProvider Hindawi Publishing
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Technical+and+Tactical+Command+Decision+Algorithm+of+Football+Matches+Based+on+Big+Data+and+Neural+Network&rft.jtitle=Scientific+programming&rft.au=Fang%2C+Lei&rft.au=Wei%2C+Qiang&rft.au=Xu%2C+Cheng+Jian&rft.date=2021&rft.pub=Hindawi&rft.issn=1058-9244&rft.eissn=1875-919X&rft.volume=2021&rft_id=info:doi/10.1155%2F2021%2F5544071&rft.externalDocID=10_1155_2021_5544071
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1058-9244&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1058-9244&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1058-9244&client=summon