– Openness to new technologies - Analysis of Video Assistant Referee (VAR) in football

5.3. C

ORRELATIONAL

A

NALYSIS

Named after the English psychologist Charles Spearman, Spearman's rank correlation coefficient is a nonparametric method for evaluating rank correlation (statistical dependence between the rankings of two variables). It evaluates how well a monotonic function can characterize the relationship between two variables (Artusi et al., 2002)

This coefficient is normally represented by the Greek letter ρ, and it only assumes values between -1 and 1.

ρ = 1: means there is a perfect positive correlation between the two variables.

ρ= -1: means there is a perfect negative correlation between the two variables (if one increases, the other will always decrease).

ρ= 0: means that the two variables are not linearly dependent on each other. However, there may be a non-linear dependency. Thus, the result ρ=0 must be investigated by other means.

A Spearman correlation analysis was conducted in SPSS comparing the answers from “The VAR is a transparent tool” and eleven other variables regarding the perception of VAR use. Cohen's standard was used to evaluate the strength of the relationships, where correlation coefficients between 0.10 and 0.29 represent a small association, correlation coefficients between 0.30 and 0.49 represent a moderate association, and correlation coefficients above 0.50 indicate a large association or relationship (Cohen, 1998).

27 5.3.1. The VAR is a transparent tool - Perception and Impact

Table 2 reflects the positive correlation of the variable X with variables U, V, W, Y, Z. In this table we can observe several relevant correlations to the study.

There is a significant positive correlation between variables X and U with a value of 0.464 and variables X and W with a value of 0.341, indicating a moderate association, this suggests that when the belief that VAR is a transparent tool increases, the belief that the VAR has successfully reduced referee bias in football and that the VAR has helped improve the decisions of on-field referees also increases.

Regarding variables X and V and X and Z, the correlations with the value of 0.707 and 0.532, respectively, imply that there is a large association between both. This denotes that, when the belief that the VAR is a transparent tool increases the trust in the VAR also tends to increase and the same can be said regarding the agreeability with the decisions made by the VAR.

On the other hand, the belief that the VAR is a transparent tool is not related with the variable Y, “The VAR shifted the focus of post-match discussion from on-field referees to the video room.”

Table 2 – The VAR is a transparent tool - Perception and Impact

Spearman's correlation coefficient results

Variable U Variable V Variable W Variable Y Variable Z

The VAR has successfully reduced referee

bias in football.

I trust the VAR.

The VAR has helped improve the decisions

of on-field referees.

The VAR shifted the focus of post-match discussion from on-field referees to the

video room.

I tend to agree with the decisions made by the

VAR.

Variable X

The VAR is a transparent

tool.

0.464 0.707 0.341 0.004 0.532

28 5.3.2. The VAR is a transparent tool - Fan experience

In table 3 we can discern that there is no correlation between variable X, “The VAR is a transparent tool” with variables W, Y and Z, “VAR stops negatively affect the experience of watching a game”, “VAR decisions should be broadcasted live in stadiums”, “VAR stops should have a maximum duration”.

Table 3 – The VAR is a transparent tool – Fan experience

Spearman's correlation coefficient results

Variable W Variable Y Variable Z

VAR stops negatively affect the experience of watching a game.

VAR decisions should be broadcasted live

in stadiums.

VAR stops should have a maximum duration.

Variable X

The VAR is a transparent

tool.

0.069 -0.013 0.075

5.3.3. The VAR is a transparent tool - Openness to the introduction of new technologies in football

As seen in Table 4 significant positive correlation was observed between variable X, “The VAR is a Transparent tool” and variables W, Y and Z, “I was in favour of the introduction of the goal line technology and VAR in football”, “I am open to the introduction of new technologies for fairness in football”, “I am in favour of the introduction of AI technologies in football to help referees make decisions”.

However, it is important to note that these 3 correlations have a small association according to Cohen’s standard.

Table 4 – The VAR is a transparent tool – Openness to new technologies

Spearman's correlation coefficient results

Variable W Variable Y Variable Z

I was in favour of the introduction

of the goal line technology and VAR in football.

I am open to the introduction of new technologies

for fairness in football.

I am in favour of the introduction of AI

technologies in football to help referees make

decisions.

Variable X

The VAR is a transparent

tool.

0.14 0.173 0.134

5.4. A

SSOCIATION

R

ULES

A

NALYSIS

The analysis of association rules was carried out using IBM’s SPSS Modeler. For this analysis, the a priori algorithm was used targeting the belief that the VAR is a transparent tool.

For the analysis, the following variables were defined as consequent and antecedents:

• Consequent: “The VAR is a transparent tool”.

• Antecedents:

1. “The VAR has successfully reduced referee bias in football”

2. “I trust the VAR”;

3. “The VAR has helped improve the decisions of on-field referees”;

4. “The VAR shifted the focus of post-match discussion from on-field referees to the video room”;

5. “I tend to agree with the decisions made by the VAR.

Table 5 – The VAR is a transparent tool – A priori algorithm

In the analysis carried out in Table 5 we can see that there is 16.384% of support relationships for 100% of confidence, meaning that we can not conclude that the belief that the VAR is a transparent tool occurs together with “The VAR has successfully reduced referee bias in football”, “I trust the VAR”, “The VAR has helped improve the decisions of on-field referees”, “The VAR shifted the focus of post-match discussion from on-field referees to the video room”, “I tend to agree with the decisions made by the VAR”.

Consequent Antecedent Support Confidence

The VAR is a transparent tool.

The VAR has successfully reduced referee bias in football.

16.384 100%

I trust the VAR.

The VAR has helped improve the decisions of on-field referees.

The VAR shifted the focus of post-match discussion from on-field referees to the video

room.

I tend to agree with the decisions made by the VAR.

5.5. D

ISCUSSION

Based on the analyses that were carried out in points 5.2, 5.3 and 5.4 it is possible to conclude that the average football fan was in favour of the introduction of the VAR and is moderately happy with it. There seems to be a general openness to the introduction of new technologies for fairness.

In order to meet the objectives that were set in point 1.3, we conducted a descriptive analysis, a correlational analysis and an association rules analysis.

After conducting these analyses, we can take several conclusions regarding the impact of the VAR and it’s perception by football fans. Regarding the perception of fans and the impact they think VAR has had on the game, we can gather that:

• The general fan is not aware on the amount of games that the VAR impacts;

• Fans believe that the VAR has improved fairness in football in general, they believe that the VAR has reduced referee bias, that it improved the decisions of on field referees and that it successfully shifted the focus of post-match discussion to the video room;

• Fans tend to trust the VAR and agree with its decisions but not fully;

• VAR stops somewhat negatively affect the experience of watching a game;

• Fans attending games in stadiums believe that VAR decisions should be broadcasted live in stadiums;

• The vast majority of fans were in favour of the introduction of the goal line technology and the VAR;

• Most fans are open to the introduction of AI technologies in football to help improve fairness;

• There is still some apprehension regarding the use of AI in football for fairness since there are more fans in favour of the introduction of new technologies than fans in favour of the introduction of AI based technologies.

• When the belief that VAR is a transparent tool increases, the belief that the VAR has successfully reduced referee bias in football and that the VAR has helped improve the decisions of on-field referees also increases, the same can be said for the trust in the VAR and fans agreeability with the decisions made by the VAR.

6. CONCLUSIONS

This chapter aims to summarize the work that was carried out, present its limitations and future work.

6.1. S

YNTHESIS OF THE

D

EVELOPED

W

ORK

The main goal of this thesis was to identify the shortcoming of the VAR, to access how football fains perceive the impact of the VAR, to analyse fans general satisfaction with VAR and their openness to the introduction of new technologies for fairness and AI based technologies specifically.

In order to meet the abovementioned objectives, a literature review was carried out which is composed of the following subtopics: Football, Technology in Sports and VAR (points 3.1, 3.2 and 3.3, respectively), with this literature review we were able to discern the research already previously made, including research regarding technologies that are used in other sports, this was a great instrument since there are sports that have adopted technologies for fairness decades before football.

After the literature review was carried out, a questionnaire was prepared targeting football fans in order to access their perception on the impact of the VAR, their opinion on the VAR and their openness to new technologies for fairness in football.

Following the collection of responses, a descriptive, correlation and association rules analysis was carried out and we were able to make some conclusions based on these analyses.

6.2. L

IMITATIONS

Seeing that most of the survey respondents are Portuguese and between the age of 18 and 34 years old, we cannot assess whether people from other countries or ages have the same perceptions regarding the VAR. It should also be noted that the sample size used only contains 175 respondents.

6.3. F

UTURE

W

ORK

Regarding future work, I recommend performing a worldwide study regarding fans perceptions of the VAR and their openness to new technologies. Additionally, the openness to the use of different AI based technologies that are being tested or already in use for fairness in other sports could be studied for football.

BIBLIOGRAPHY

Bal, B., & Dureja, G. (2012). Hawk Eye: A Logical Innovative Technology Use in Sports for Effective Decision Making. Sport Science Review, 21(1–2), 107–119. https://doi.org/10.2478/v10237-012-0006-6 Beal, R., Chalkiadakis, G., Norman, T. J., & Ramchurn, S. D. (2020). Optimising Game Tactics for Football.

http://arxiv.org/abs/2003.10294

Beal, R., Changder, N., Norman, T. J., & Ramchurn, S. D. (2020). Learning the Value of Teamwork to Form Efficient Teams. www.aaai.org

Boden, M. (2016). AI Its Nature and Future.

Buraimo, B., Simmons, R., & Maciaszczyk, M. (2012). Favoritism and referee bias in european soccer:

Evidence from the spanish league and the uefa champions league. Contemporary Economic Policy, 30(3), 329–343. https://doi.org/10.1111/j.1465-7287.2011.00295.x

Carboch, J., Vejvodova, K., & Suss, V. (2016). Analysis of errors made by line umpires on ATP tournaments.

International Journal of Performance Analysis in Sport, 16(1), 264–275.

https://doi.org/10.1080/24748668.2016.11868885

Carlos, L. P., Ezequiel, R., & Anton, K. (2019). How does Video Assistant Referee (VAR) modify the game in elite soccer? International Journal of Performance Analysis in Sport, 19(4), 646–653.

https://doi.org/10.1080/24748668.2019.1646521

Chen, R., & Davidson, N. P. (2021). English Premier League manager perceptions of video assistant referee (VAR) decisions during the 2019-2020 season. Soccer and Society.

https://doi.org/10.1080/14660970.2021.1918680

Cokins, G., & Schrader, D. (2017). The Sports Analytics Explosion Opportunities for research: drilling deeper into team sports. https://doi.org/10.1287/orms.2017.01.11/full/1/13

Cui, J., Liu, Z., & Xu, L. (2017). Modelling and simulation for table tennis referee regulation based on finite state machine. Journal of Sports Sciences, 35(19), 1888–1896.

https://doi.org/10.1080/02640414.2016.1241417

Decroos, T., van Haaren, J., Bransen, L., & Davis, J. (2019). Actions speak louder than goals: Valuing player actions in soccer. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1851–1861. https://doi.org/10.1145/3292500.3330758

Deloitte. (2018). Internet of Things (IoT) in Sports Bringing IoT to Sports Analytics, Player Safety, and Fan Engagement.

Dimitropoulos, P., Leventis, S., & Dedoulis, E. (2016). Managing the European football industry: UEFA’s regulatory intervention and the impact on accounting quality. European Sport Management Quarterly, 16(4), 459–486. https://doi.org/10.1080/16184742.2016.1164213

Dohmen, T. J. (2008). The influence of social forces: Evidence from the behavior of football referees.

Economic Inquiry, 46(3), 411–424. https://doi.org/10.1111/j.1465-7295.2007.00112.x Dohmen, T., & Sauermann, J. (2016). REFEREE BIAS. Journal of Economic Surveys, 30(4), 679–695.

https://doi.org/10.1111/joes.12106

33 FIFA. (2021). Implementation Assistance and Approval Programme for VAR technology (IAAP). FIFA.

https://www.fifa.com/technical/football-technology/standards/video-assistant-referee/var-iaap-technology

Galariotis, E., Germain, C., & Zopounidis, C. (2018). A combined methodology for the concurrent evaluation of the business, financial and sports performance of football clubs: the case of France.

Annals of Operations Research, 266(1–2), 589–612. https://doi.org/10.1007/s10479-017-2631-z Gammelsæter, H. (2010). Institutional pluralism and governance in “commercialized” sport clubs.

European Sport Management Quarterly, 10(5), 569–594.

https://doi.org/10.1080/16184742.2010.524241

Garicano, L., Palacios, I., & Prendergast, C. (2001). Favoritism Under Social Pressure. NBER Working Paper No. W8376.

Goossens, D. R., Beliën, J., & Spieksma, F. C. R. (2012). Comparing league formats with respect to match importance in Belgian football. Annals of Operations Research, 194(1), 223–240.

https://doi.org/10.1007/s10479-010-0764-4

Grant Jarvie, & James Thornton. (2012). Sport, culture and society: An Introduction (2nd ed.). Routledge.

Han, B., Chen, Q., Lago-Peñas, C., Wang, C., & Liu, T. (2020). The influence of the video assistant referee on the Chinese Super League. International Journal of Sports Science and Coaching, 15(5–6), 662–668.

https://doi.org/10.1177/1747954120938984

International Football Association Board. (2018). Laws of the Game.

International Football Association Board. (2020). Laws of the Game. www.theifab.com

International Football Association Board. (2021). Laws of the Game. https://www.theifab.com/

Johansen, B. T. (2015). Reasons for officiating soccer: The role of passion-based motivations among Norwegian elite and non-elite referees. Movement and Sports Sciences - Science et Motricite, 87, 23–

30. https://doi.org/10.1051/sm/2014012

Johnson, D. (2020). How VAR decisions affected every Premier League club in 2019-20. ESPN.

https://www.espn.com/soccer/english-premier-league/story/3929823/how-var-decisions-have-affected-every-premier-league-club

Kent, R. A., Caudill, S. B., & Mixon, F. G. (2013). Rules changes and competitive balance in european professional soccer:Evidence from an event study approach. Applied Economics Letters, 20(11), 1109–1112. https://doi.org/10.1080/13504851.2013.791010

KNVB. (n.d.). VIDEO ASSISTANT REFEREE (VAR). Https://Www.Knvb.Nl/. Retrieved January 27, 2022, from https://www.knvb.nl/themas/sportiviteit-en-respect/video-assistant-referee-var

Kolbinger, O., & Knopp, M. (2020a). Video kills the sentiment—Exploring fans’ reception of the video assistant referee in the English premier league using Twitter data. PLoS ONE, 15(12 December).

https://doi.org/10.1371/journal.pone.0242728

Kolbinger, O., & Knopp, M. (2020b). Video kills the sentiment—Exploring fans’ reception of the video assistant referee in the English premier league using Twitter data. PLoS ONE, 15(12 December).

https://doi.org/10.1371/journal.pone.0242728

34 Lex, H., Pizzera, A., Kurtes, M., & Schack, T. (2015). Influence of players’ vocalisations on soccer referees’

decisions. European Journal of Sport Science, 15(5), 424–428.

https://doi.org/10.1080/17461391.2014.962620

Li, R. T., Kling, S. R., Salata, M. J., Cupp, S. A., Sheehan, J., & Voos, J. E. (2016). Wearable Performance Devices in Sports Medicine. In Sports Health (Vol. 8, Issue 1, pp. 74–78). SAGE Publications Inc.

https://doi.org/10.1177/1941738115616917

McCullagh, J., & Whitfort, T. (2013). An investigation into the application of artificial neural. International Journal of Sport and Health Sciences.

Mellick, M. C., Fleming, S., Bull, P., & Laugharne, E. J. (2011). Identifying Best Practice for Referee Decision Communication in Association and Rugby Union Football.

Nafziger, J. A. R. (2004). Marquette Sports Law Review Avoiding and Resolving Disputes During Sports Competition: Of Cameras and Computers AVOIDING AND RESOLVING DISPUTES DURING SPORTS COMPETITION: OF CAMERAS AND COMPUTERS.

http://scholarship.law.marquette.edu/sportslawhttp://scholarship.law.marquette.edu/sportslaw/vol 15/iss1/4

Nielsen Sports. (2018). WORLD FOOTBALL REPORT 2018.

Novatchkov, H., & Baca, A. (2013). Artificial Intelligence in Sports on the Example of Weight Training. In

Papataxiarhis, V., Tsetsos, V., Karali, I., Stamatopoulos, P., & Hadjiefthymiades, S. (2009). i-footman: A Knowledge-Based Framework for Football Managers. http://www.di.uoa.gr/~vpap/i-footman/

Penrose, C. (2022). How IoT is transforming the business of sports.

Perl, J. (2001). Artificial Neural Networks in Sports: New Concepts and Approaches. International Journal of Performance Analysis in Sport, 1(1), 106–121. https://doi.org/10.1080/24748668.2001.11868253 Pettersson-Lidbom, P., & Priks, M. (2010). Behavior under social pressure: Empty Italian stadiums and

referee bias. Economics Letters, 108(2), 212–214. https://doi.org/10.1016/j.econlet.2010.04.023 Petty, L. (2018, June 14). Analysing VAR: Could VAR affect home advantage?

Https://Www.Pinnacle.Com/En/Betting-Articles/Soccer/Var-Home-Advantage/U6N27PEZMNKJU9RB.

https://www.pinnacle.com/en/betting-articles/Soccer/var-home-advantage/U6N27PEZMNKJU9RB Pires, M., & Santos, V. (2018). Assessing the Impact of Internet of Everything Technologies in Football.

Journal of Sports Science, 6(1). https://doi.org/10.17265/2332-7839/2018.01.005

Rohde, M., & Breuer, C. (2017). The market for football club investors: a review of theory and empirical evidence from professional European football. In European Sport Management Quarterly (Vol. 17, Issue 3, pp. 265–289). Routledge. https://doi.org/10.1080/16184742.2017.1279203

Ryall, E. (2012). Are there any good arguments against goal-line technology? Sport, Ethics and Philosophy, 6(4), 439–450. https://doi.org/10.1080/17511321.2012.737010

Spitz, J., Wagemans, J., Memmert, D., Williams, A. M., & Helsen, W. F. (2021). Video assistant referees (VAR): The impact of technology on decision making in association football referees. Journal of Sports Sciences, 39(2), 147–153. https://doi.org/10.1080/02640414.2020.1809163

35 Stoney, E., & Fletcher, T. (2021). “Are Fans in the Stands an Afterthought?”: Sports Events, Decision-Aid

Technologies, and the Television Match Official in Rugby Union. Communication and Sport, 9(6), 1008–1029. https://doi.org/10.1177/2167479520903405

Tamir, I., & Bar-eli, M. (2021). The Moral Gatekeeper: Soccer and Technology, the Case of Video Assistant Referee (VAR). Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.613469

Wicker, P., & Frick, B. (2016). Recruitment and retention of referees in nonprofit sport organizations: The trickle-down effect of role models. Voluntas, 27(3), 1304–1322. https://doi.org/10.1007/s11266-016-9705-4

Wilkerson, G. B., Gupta, A., & Colston, M. A. (2018). Mitigating Sports Injury Risks Using Internet of Things and Analytics Approaches. Risk Analysis, 38(7), 1348–1360. https://doi.org/10.1111/risa.12984 Xu, J., Zhang, Y., Ye, A., & Dai, F. (2021). Real-time detection of game handball foul based on target

detection and skeleton extraction. 2021 IEEE International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology, CEI 2021, 41–46.

https://doi.org/10.1109/CEI52496.2021.9574504

Yunwei, L. I., & Shiwei, J. (2019). Video Analysis Technology and Its Application in Badminton Sports Training. Journal of Physics: Conference Series, 1213(2).

https://doi.org/10.1088/1742-6596/1213/2/022009

Zhan, K. (2021). Sports and health big data system based on 5G network and Internet of Things system.

Microprocessors and Microsystems, 80. https://doi.org/10.1016/j.micpro.2020.103363

ANNEX

No documento Analysis of Video Assistant Referee (VAR) in football (páginas 32-47)