Monitoring Training Load and Data Analysis Methods in Football

Yıl 2020, Cilt: 14 Sayı: 3, 481 - 493, 10.12.2020

Zeki Akyıldız , Cengiz Akarçeşme

Öz

Given the nature of the game pace and weekly fixture density of today's football, athletes with millions of lira costs should be protected from injuries and reached their optimum performance levels. The meaningful information revealed by the follow-up of the training load and the analysis of the data obtained facilitates the athletes to reach their goals by making it easier to cope with the pace of today's football. Therefore, it is very important for the football world to transform and make sense of the physiological, kinematic, psychological and mechanical loads created by training and competitions on athletes. The training load tracking methods that allow the observation of the positive and negative situations occurring in athletes and to take action according to these situations, the development of technological tools today and the fact that the users in the world of sports science are more experienced than the past, facilitates the loads more effective in the training of athletes.The systems that enable us to direct the training by transforming the obtained data into understandable information as well as measuring the training load are developing in parallel with the technology today. It is thought that sports scientists and coaches can transform the information they have gained from all these methods and technologies into understandable visuals that enable them to communicate easily with technical staff or players in the team. In this review, contrary to the studies that have been done previously and have not only examined the training load tracking methods but can not answer the questions how we can analyze the obtained data and transform it into practical usable information, however, how the data obtained in the analysis methods should be converted into understandable visuals. Intended to pass on to readers.

Anahtar Kelimeler

Training Load, Data Analysis, Data Visualization

FUTBOLDA ANTRENMAN YÜKÜ TAKİBİ VE VERİ ANALİZ YÖNTEMLERİ

Öz

Günümüzdeki futbolun maç temposunun ve haftalık fikstür yoğunluğunun yapısı göz önünde bulundurulduğunda, milyonlarca liralık maliyetleri olan sporcuların sakatlıklardan korunmaları ve optimum performans seviyelerine ulaştırılmaları gerekmektedir. Antrenman yükünün takibi ve elde edilen verilerin analizi sonucu ortaya koyulan anlamlı bilgilerde sporcuların günümüz futbolundaki tempoyla başa çıkmalarını kolaylaştırarak amaçlarına ulaşmalarını kolaylaştırmaktadır. Bu nedenle antrenmanların ve müsabakaların sporcular üzerinde oluşturduğu fizyolojik, kinematik, psikolojik ve mekanik yükleri objektif verilere dönüştürüp anlamlandırmak futbol dünyası için oldukça önemlidir. Sporcularda oluşan pozitif ve negatif durumları gözlemleyip bu durumlara göre aksiyon almayı sağlayan antrenman yükü takip yöntemleri, günümüzde teknolojik araçların gelişmesi ve spor bilimi dünyasındaki kullanıcıların geçmişe göre daha tecrübeli olması, sporcuların antrenmanlarında oluşan yüklerin daha efektif bir şekilde elde edilmesini kolaylaştırmaktadır. Antrenman yükünün ölçülmesi kadar, elde edilen verilerin işlenip anlaşılabilir bilgilere dönüştürülerek antrenmanlara yön verebilmemizi sağlayan sistemlerde günümüzde teknolojiye paralel bir şekilde gelişmektedir. Spor bilimciler ve antrenörler tüm bu yöntemler ve teknolojilerden elde etmiş olduğu bilgileri anlaşılabilir görsellere dönüştürerek takımdaki teknik personellerle ya da oyuncularla kolay iletişim kurmalarını sağlayabilirler. Bu derlemede daha önce yapılmış olan ve sadece antrenman yükü takip yöntemlerini incelemiş fakat elde edilen verileri nasıl analiz ederek pratik kullanılabilir bilgilere dönüştürebiliriz sorularına cevap veremeyen çalışmaların aksine, antrenman yükü takibini ve elde edilen verilerin analizini aynı zamanda analiz yöntemlerinde elde edilen verilerin anlaşılabilir görsellere nasıl dönüştürülmesini gerektiğini okuyuculara aktarmak amaçlanmıştır.

Anahtar Kelimeler

Antrenman Yükü, Veri Analizi, Veri Görselleştirme

Kaynakça

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