Araştırma Makalesi
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UEFA Şampiyonlar Ligi'nde son 16 yolu: Grup aşamalarından yükselmek için anahtar oyun içi istatistikler

Yıl 2025, Cilt: 28 Sayı: 54, 853 - 868, 16.12.2025
https://doi.org/10.31795/baunsobed.1566318
https://izlik.org/JA46MW34AC

Öz

Bu çalışmanın amacı, UEFA Şampiyonlar Ligi (UCL) gruplarında hangi takımların son 16 tura ilerlediğini ayırt eden oyun içi istatistikleri belirlemektir. Araştırma, 2019/2020 ile 2021/2022 sezonları arasında oynanan 288 maçı (n=288) ve 57 takımı analiz etmiştir. Lineer ayırt edici analiz, takım ilerlemesini belirlemede her bir oyun içi istatistiğin katkısını ve sınıflandırmasını değerlendirmek için kullanılmıştır; karar ağaçları analizi ise kritik kesim noktalarını tanımlamada yardımcı olmuştur. Sonuçlar, ev sahibi olduğu maçları kazanmanın, deplasman maçlarını kazanmanın ve yenilen gol sayısının, bir takımın son 16 tura ilerlemesini etkili bir şekilde tahmin ettiğini göstermiştir. Özellikle, karar ağaçları analizi, en az iki ev sahibi galibiyeti ve en az bir deplasman galibiyeti olan takımların, eleme aşamasına ilerleme olasılığının çok yüksek olduğunu belirtmiştir. Ayrıca, sadece bir veya hiç ev sahibi galibiyeti olan takımların, ilerlemek için en az iki deplasman galibiyeti elde etmesi gerektiği ortaya çıkmıştır. Ayırt edici fonksiyon, grup aşamalarından son 16'ya geçen takımları doğru bir şekilde sınıflandırarak %94,8'lik yüksek bir doğruluk oranı göstermiştir. Ayrıca, grup aşamalarında dokuz veya daha az gol yiyen takımların da son 16'ya ilerlemede başarılı olduğu bulunmuştur.

Kaynakça

  • Allister, A., Byrne, P. J., Nulty, C. D., & Jordan, S. (2018). Game-related statistics which discriminate elite senior Gaelic football teams according to game outcome and final score difference. International Journal of Performance Analysis in Sport, 18(4), 622-632.
  • Almeida, C. H., Ferreira, A. P., & Volossovitch, A. (2014). Effects of match location, match status and quality of opposition on regaining possession in UEFA Champions League. Journal of human kinetics, 41(1), 203-214.
  • Armatas, V., & Pollard, R. (2014). Home advantage in Greek football. European Journal of Sport Science, 14(2), 116-122.
  • Armatas, V., Yiannakos, A., Galazoulas, C., & Hatzimanouil, D. (2007). Goal scoring patterns over the course of a match: Analysis of Women's high standard soccer matches. Physical Training, 1(1), 1-9.
  • Armatas, V., Yiannakos, A., Papadopoulou, S., & Skoufas, D. (2009). Evaluation of goals scored in top ranking soccer matches: Greek “Super League” 2006-07. Serbian Journal of Sports Sciences, 3(1), 39-43.
  • Bar-Eli, M., Tenenbaum, G., & Geister, S. (2006). Consequences of players' dismissal in professional soccer: A crisis-related analysis of group-size effects. Journal of sports sciences, 24(10), 1083-1094.
  • Berlanga, V., Rubio Hurtado, M., & Vilà Baños, R. (2013). How to apply decision trees in SPSS. Revista d'Innovació i Recerca en Educació, 6(1), 65-79. https://doi.org/10.1344/reire2013.6.1615.
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  • Charalampos, M., Yiannis, M., Michalis, M., & Zisis, P. (2013). Analysis Of Goals Scored in The Uefa Champions League in The Period 2009/2010. Serbian Journal of Sports Sciences, 7(2).
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  • Collet, C. (2013). The possession game? A comparative analysis of ball retention and team success in European and international football, 2007–2010. Journal of sports sciences, 31(2), 123-136.
  • Cushion, C. (2007). Modelling the complexity of the coaching process. International journal of sports science & coaching, 2(4), 395-401.
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2018). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları, 5. Baskı, Ankara: Pegem Akademi.
  • Devecioğlu, S., Çoban, B., & Karakaya, Y. (2014). Futbol yönetimi ve organizasyonlarının görünümü. Spor ve Performans Araştırmaları Dergisi, 5(1), 35-48.
  • Díaz-Pérez, F. M., & Bethencourt-Cejas, M. (2016). CHAID algorithm as an appropriate analytical method for tourism market segmentation. Journal of Destination Marketing & Management, 5(3), 275-282.
  • Evangelos, B., Gioldasis, A., Ioannis, G., & Georgia, A. (2018). Relationship between time and goal scoring of European soccer teams with different league ranking. Journal of Human Sport and Exercise. 2018, 13(3): 518-529. https://doi:10.14198/jhse.2018.133.04.
  • Fowler, P., Duffield, R., & Vaile, J. (2014). Effects of domestic air travel on technical and tactical performance and recovery in soccer. International Journal of Sports Physiology and Performance, 9(3), 378-386.
  • Franks, I. M., & Hughes, M. (2016). Successful coaching through match analysis (1st Ed.). Meyer and Meyer Sport.
  • Gai, Y., Volossovitch, A., Lago, C., & Gómez, M. Á. (2019). Technical and tactical performance differences according to player’s nationality and playing position in the Chinese football super league. International Journal of Performance Analysis in Sport, 19(4), 632-645. https://doi.org/10.1080/24748668.2019.1644804.
  • García-Rubio, J., Gómez, M. Á., Lago-Peñas, C., & Ibáñez, J. S. (2015). Effect of match venue, scoring first and quality of opposition on match outcome in the UEFA Champions League. International Journal of Performance Analysis in Sport, 15(2), 527-539.
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  • Hughes M.D., Evans S., & Wells J. (2001). Establishing normative profiles in performance analysis. International Journal of Performance Analysis in Sports 11(1), 1-26
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Road to the round of 16 in UEFA Champions League: Key in-game statistics for advancing from the group stages

Yıl 2025, Cilt: 28 Sayı: 54, 853 - 868, 16.12.2025
https://doi.org/10.31795/baunsobed.1566318
https://izlik.org/JA46MW34AC

Öz

The objective of this study was to identify the in-game statistics that help differentiate between the teams in the UEFA Champions League (UCL) group stage that advance to the round of 16.The research analyzed all matches (n=288) played among 57 teams in the UCL group stages from the 2019/2020 to 2021/2022 seasons. Linear discriminant analysis was utilized to evaluate the contribution and classification of each in-game statistic in determining team progression, while decision tree analysis helped identify critical cut-off points. Results showed that winning home games, winning away games, and the number of goals conceded effectively predicted a team's advancement to the last 16. Specifically, decision tree analysis indicated that teams with at least two home wins and at least one away win are highly likely to progress to the knockout stage. Additionally, teams with only one or no home wins must achieve at least two away wins to advance. The discriminant function demonstrated a high accuracy rate, correctly classifying 94.8% of the teams that moved on from the group stages to the last 16. Moreover, teams that conceded nine or fewer goals in the group stages were also successful in advancing to the round of 16.

Kaynakça

  • Allister, A., Byrne, P. J., Nulty, C. D., & Jordan, S. (2018). Game-related statistics which discriminate elite senior Gaelic football teams according to game outcome and final score difference. International Journal of Performance Analysis in Sport, 18(4), 622-632.
  • Almeida, C. H., Ferreira, A. P., & Volossovitch, A. (2014). Effects of match location, match status and quality of opposition on regaining possession in UEFA Champions League. Journal of human kinetics, 41(1), 203-214.
  • Armatas, V., & Pollard, R. (2014). Home advantage in Greek football. European Journal of Sport Science, 14(2), 116-122.
  • Armatas, V., Yiannakos, A., Galazoulas, C., & Hatzimanouil, D. (2007). Goal scoring patterns over the course of a match: Analysis of Women's high standard soccer matches. Physical Training, 1(1), 1-9.
  • Armatas, V., Yiannakos, A., Papadopoulou, S., & Skoufas, D. (2009). Evaluation of goals scored in top ranking soccer matches: Greek “Super League” 2006-07. Serbian Journal of Sports Sciences, 3(1), 39-43.
  • Bar-Eli, M., Tenenbaum, G., & Geister, S. (2006). Consequences of players' dismissal in professional soccer: A crisis-related analysis of group-size effects. Journal of sports sciences, 24(10), 1083-1094.
  • Berlanga, V., Rubio Hurtado, M., & Vilà Baños, R. (2013). How to apply decision trees in SPSS. Revista d'Innovació i Recerca en Educació, 6(1), 65-79. https://doi.org/10.1344/reire2013.6.1615.
  • Boczon, M., & Wilson, A. J. (2018). Goals, constraints, and public assignment: A field study of the UEFA Champions League. University of Pittsburgh. Retrieved January, 12, 2024.
  • Boscá, J. E., Liern, V., Martínez, A., & Sala, R. (2009). Increasing offensive or defensive efficiency? An analysis of Italian and Spanish football. Omega, 37(1), 63-78.
  • Broich, H., Mester, J., Seifriz, F., & Yue, Z. (2014). Statistical analysis for the First Bundesliga in the current soccer season. Progress in Applied Mathematics, 7(2), 1-8.
  • Carmichael, F., Thomas, D., & Ward, R. (2000). Team performance: the case of English premiership football. Managerial and decision Economics, 21(1), 31-45.
  • Castellano, J., Casamichana, D., & Lago, C. (2012). The use of match statistics that discriminate between successful and unsuccessful soccer teams. Journal of human kinetics, 31(2012), 137-147.
  • Charalampos, M., Yiannis, M., Michalis, M., & Zisis, P. (2013). Analysis Of Goals Scored in The Uefa Champions League in The Period 2009/2010. Serbian Journal of Sports Sciences, 7(2).
  • Cohen, J. (1988). Statistical power analysis for the behavioural sciences (2nd ed.) Hillsdale, NJ: Lawrence Erlbaum.
  • Collet, C. (2013). The possession game? A comparative analysis of ball retention and team success in European and international football, 2007–2010. Journal of sports sciences, 31(2), 123-136.
  • Cushion, C. (2007). Modelling the complexity of the coaching process. International journal of sports science & coaching, 2(4), 395-401.
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2018). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları, 5. Baskı, Ankara: Pegem Akademi.
  • Devecioğlu, S., Çoban, B., & Karakaya, Y. (2014). Futbol yönetimi ve organizasyonlarının görünümü. Spor ve Performans Araştırmaları Dergisi, 5(1), 35-48.
  • Díaz-Pérez, F. M., & Bethencourt-Cejas, M. (2016). CHAID algorithm as an appropriate analytical method for tourism market segmentation. Journal of Destination Marketing & Management, 5(3), 275-282.
  • Evangelos, B., Gioldasis, A., Ioannis, G., & Georgia, A. (2018). Relationship between time and goal scoring of European soccer teams with different league ranking. Journal of Human Sport and Exercise. 2018, 13(3): 518-529. https://doi:10.14198/jhse.2018.133.04.
  • Fowler, P., Duffield, R., & Vaile, J. (2014). Effects of domestic air travel on technical and tactical performance and recovery in soccer. International Journal of Sports Physiology and Performance, 9(3), 378-386.
  • Franks, I. M., & Hughes, M. (2016). Successful coaching through match analysis (1st Ed.). Meyer and Meyer Sport.
  • Gai, Y., Volossovitch, A., Lago, C., & Gómez, M. Á. (2019). Technical and tactical performance differences according to player’s nationality and playing position in the Chinese football super league. International Journal of Performance Analysis in Sport, 19(4), 632-645. https://doi.org/10.1080/24748668.2019.1644804.
  • García-Rubio, J., Gómez, M. Á., Lago-Peñas, C., & Ibáñez, J. S. (2015). Effect of match venue, scoring first and quality of opposition on match outcome in the UEFA Champions League. International Journal of Performance Analysis in Sport, 15(2), 527-539.
  • Gómez, M. A., Gómez-Lopez, M., Lago, C., & Sampaio, J. (2012). Effects of game location and final outcome on game-related statistics in each zone of the pitch in professional football. European Journal of Sport Science, 12(5), 393-398.
  • Gündüz, M., & Lutfi, H. M. (2021). Go/no-go decision model for owners using exhaustive CHAID and QUEST decision tree algorithms. Sustainability, 13(2), 815.
  • Hughes M.D., Evans S., & Wells J. (2001). Establishing normative profiles in performance analysis. International Journal of Performance Analysis in Sports 11(1), 1-26
  • Işıkdemir, E. (2020). Futbolda Puan ve Eleme Usulüne Göre Oynanan Karşılaşmalarda Ev Sahibi Olmak Bir Avantaj Mıdır?: 2018-2019 Şampiyonlar Ligi Analizi. Spormetre Beden Eğitimi ve Spor Bilimleri Dergisi, 18(2), 157-165.
  • Janković, A., Leontijević, B., Pašić, M., & Jelušić, V. (2011). Influence of certain tactical attacking patterns on the result achieved by the teams participants of the 2010 FIFA World Cup in South Africa. Fizička kultura, 65(1), 34-45.
  • Kapidžić, A., Mejremić, E., Bilalić, J., & Bečirović, E. (2010). Differences in Some Parameters of Situation Efficiency Between Winning and Defeated Teams at Two Levels of Competition. Sport Scientific & Practical Aspects, 7(2).
  • Konefał, M., Chmura, P., Zacharko, M., Chmura, J., Rokita, A., & Andrzejewski, M. (2018). Match outcome vs match status and frequency of selected technical activities of soccer players during UEFA Euro 2016. International Journal of Performance Analysis in Sport, 18(4), 568-581. https://doi.org/10.1080/24748668.2018.1501991.
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  • Lago-Peñas, C., Gómez-Ruano, M. Á., Owen, A. L., & Sampaio, J. (2016). The effects of a player dismissal on competitive technical match performance. International Journal of Performance Analysis in Sport, 16(3), 792-800. https://doi.org/10.1080/24748668.2016.11868928.
  • Lago-Peñas, C., Gómez-Ruano, M., Megías-Navarro, D., & Pollard, R. (2016). Home advantage in football: Examining the effect of scoring first on match outcome in the five major European leagues. International Journal of Performance Analysis in Sport, 16(2), 411-421.
  • Lago-Peñas, C., Lago-Ballesteros, J., & Rey, E. (2011). Differences in performance indicators between winning and losing teams in the UEFA Champions League. Journal of human kinetics, 27(1), 135-146.
  • Lago-Peñas, C., Lago-Ballesteros, J., Dellal, A., & Gómez, M. (2010). Game-related statistics that discriminated winning, drawing and losing teams from the Spanish soccer league. Journal of sports science & medicine, 9(2), 288.
  • Lago, C. (2009). The influence of match location, quality of opposition, and match status on possession strategies in professional association football. Journal of sports sciences, 27(13), 1463-1469.
  • Lago, C., & Martín, R. (2007). Determinants of possession of the ball in soccer. Journal of sports sciences, 25(9), 969-974.
  • Liu, H., Gomez, M. Á., Lago-Peñas, C., & Sampaio, J. (2015). Match statistics related to winning in the group stage of 2014 Brazil FIFA World Cup. Journal of sports sciences, 33(12), 1205-1213.
  • Liu, H., Hopkins, W. G., & Gómez, M. A. (2016). Modelling relationships between match events and match outcome in elite football. European journal of sport science, 16(5), 516-525.
  • Liu, H., Hopkins, W., Gómez, A. M., & Molinuevo, S. J. (2013). Inter-operator reliability of live football match statistics from OPTA Sportsdata. International Journal of Performance Analysis in Sport, 13(3), 803-821. https://doi.org/10.1080/24748668.2013.11868690.
  • Luhtanen, P., Belinskij, A., Häyrinen, M., & Vänttinen, T. (2001). A comparative tournament analysis between the EURO 1996 and 2000 in soccer. international Journal of performance Analysis in sport, 1(1), 74-82.
  • Mackenzie, R., & Cushion, C. (2013). Performance analysis in football: A critical review and implications for future research. Journal of sports sciences, 31(6), 639-676.
  • Mao, L., Peng, Z., Liu, H., & Gómez, M. A. (2016). Identifying keys to win in the Chinese professional soccer league. International Journal of Performance Analysis in Sport, 16(3), 935-947.
  • Mechtel, M., Bäker, A., Brändle, T., & Vetter, K. (2011). Red cards: Not such bad news for penalized guest teams. Journal of Sports Economics, 12(6), 621-646.
  • Memmert, D., & Raabe, D. (2018). Data analytics in football: Positional data collection, modelling and analysis. Routledge.
  • Michailidis, Y., Michailidis, C., & Primpa, E. (2013). Analysis of goals scored in European Championship 2012. Journal of Human Sport & Exercise, 8(2), 367-375. https://doi.org/10.4100/jhse.2012.82.05.
  • Milanović, M., & Stamenković, M. (2016). CHAID decision tree: Methodological frame and application. Economic Themes, 54(4), 563-586.
  • Moura, F. A., Martins, L. E. B., & Cunha, S. A. (2014). Analysis of football game-related statistics using multivariate techniques. Journal of sports sciences, 32(20), 1881-1887.
  • O’Donoghue, P. (2013). Sports performance profiling. In Routledge Handbook of sports performance analysis (pp. 127-139). Routledge.
  • Oberstone, J. (2009). Differentiating the top English premier league football clubs from the rest of the pack: Identifying the keys to success. Journal of Quantitative Analysis in Sports, 5(3).
  • Oberstone, J. (2011). Comparing team performance of the English premier league, Serie A, and La Liga for the 2008-2009 season. Journal of Quantitative Analysis in Sports, 7(1). https://doi.org/10.2202/1559-0410.1280.
  • Özçilingir, Ö. M., & Bozdoğan, T. (2021). Futbolda İç Saha ve Dış Saha Bakımından Galibiyeti Etkileyen Analiz Parametrelerinin İncelenmesi. Spor Eğitim Dergisi, 5(3), 153-160.
  • Özdamar, K. (2010), Paket Programlar ile İstatistiksel Veri Analizi. (2nd Ed.). Eskişehir: Nisan Kitabevi.
  • Papahristodoulou, C. (2008): An analysis of UEFA Champions League match statistics. Int. J. Applied Sports Sci., 20(1), 67 - 93.
  • Pollard, R. (1986). Home advantage in soccer: A retrospective analysis. Journal of sports sciences, 4(3), 237-248.
  • Pollard, R., Silva, C. D., & Medeiros, N. C. (2008). Home advantage in football in Brazil: differences between teams and the effects of distance traveled. Revista Brasileira de Futebol (The Brazilian Journal of Soccer Science), 1(1), 3-10.
  • Poulter, D. R. (2009). Home advantage and player nationality in international club football. Journal of sports sciences, 27(8), 797-805.
  • Pratas, J. M., Volossovitch, A., & Carita AI. (2016). The effect of performance ındicators on the time the first goal is scored in football matches. International Journal of Performance Analysis in Sport, (16), 347-354.
  • Rampinini, E., Impellizzeri, F. M., Castagna, C., Coutts, A. J., & Wisløff, U. (2009). Technical performance during soccer matches of the Italian Serie A league: Effect of fatigue and competitive level. Journal of science and medicine in sport, 12(1), 227-233.
  • Ruiz-Ruiz, C., Fradua, L., Fernández-GarcÍa, Á., & Zubillaga, A. (2013). Analysis of entries into the penalty area as a performance indicator in soccer. European Journal of Sport Science, 13(3), 241-248.
  • Saavedra García, M., Gutiérrez Aguilar, O., Fernández Romero, J. J., & Sa Marques, P. (2015). Ventaja De Jugar En Casa En El Fútbol Español (1928-2011). Revista Internacional de Medicina y Ciencias de la Actividad Física y el Deporte, 15(57), 181-194.
  • Sarmento, H., Marcelino, R., Anguera, M. T., CampaniÇo, J., Matos, N., & LeitÃo, J. C. (2014). Match analysis in football: a systematic review. Journal of sports sciences, 32(20), 1831-1843.
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  • Taylor, B. J., Mellalieu, D. S., James, N., & Barter, P. (2010). Situation variable effects and tactical performance in professional association football. International Journal of Performance Analysis in Sport, 10(3), 255-269.
  • Taylor, J. B., Mellalieu, S. D., James, N., & Shearer, D. A. (2008). The influence of match location, quality of opposition, and match status on technical performance in professional association football. Journal of sports sciences, 26(9), 885-895.
  • Tenga, A. (2012). First goal and home advantage at different levels of play in professional soccer. World Congress of Performance Analysis of Sport IX, London & New York: Routledge Taylor & Francis Group, Editors: D. Peters, P. G. O’Donoghue, (s:47-51).
  • Torgler, B. (2004). The economics of the FIFA Football Worldcup. Kyklos, 57(2), 287-300.
  • Tucker, W., Mellalieu, D. S., James, N., & Taylor, B. J. (2005). Profesyonel futbolda oyun konumu etkileri: Bir vaka çalışması. Uluslararası Sporda Performans Analizi Dergisi, 5(2), 23-35.
  • Tunaru, R. S., & Viney, H. P. (2010). Valuations of soccer players from statistical performance data. Journal of Quantitative Analysis in Sports, 6(2). https://doi.org/10.2202/1559-0410.1238.
  • Tütüncü, O., & Yolgörmez, A. C. (2021). Futbolda Ev Avantajı mı, Deplasman Dezavantajı mı? COVID-19 Pandemi Süreci Örneği. Gazi Beden Eğitimi ve Spor Bilimleri Dergisi, 26(1), 137-149.
  • Vilar, L., Araújo, D., Davids, K., & Button, C. (2012). The role of ecological dynamics in analysing performance in team sports. Sports Medicine, 42, 1-10.
  • Vogelbein, M., Nopp, S., & Hökelmann, A. (2014). Defensive transition in soccer–are prompt possession regains a measure of success? A quantitative analysis of German Fußball-Bundesliga 2010/2011. Journal of sports sciences, 32(11), 1076-1083.
  • Yadev, S. K., & Pal, S. (2012). Data mining: A prediction for performance improvement of engineering students using classification. World Computer Science and Information Technology Journal, 2, 51–56.
  • Zambom-Ferraresi, F., Rios, V., & Lera-López, F. (2018). Determinants of sport performance in European football: What can we learn from the data? Decision Support Systems, 114, 18-28.
Toplam 83 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Egzersiz ve Spor Bilimleri (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Alp Kaan Kilci 0000-0001-6445-6400

Serhat Yalçıner 0000-0002-9888-4777

Nahit Özdayı 0000-0002-5534-3153

Gökhan Aydın 0000-0001-5575-3200

Gönderilme Tarihi 13 Ekim 2024
Kabul Tarihi 21 Ağustos 2025
Yayımlanma Tarihi 16 Aralık 2025
DOI https://doi.org/10.31795/baunsobed.1566318
IZ https://izlik.org/JA46MW34AC
Yayımlandığı Sayı Yıl 2025 Cilt: 28 Sayı: 54

Kaynak Göster

APA Kilci, A. K., Yalçıner, S., Özdayı, N., & Aydın, G. (2025). Road to the round of 16 in UEFA Champions League: Key in-game statistics for advancing from the group stages. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 28(54), 853-868. https://doi.org/10.31795/baunsobed.1566318

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