Hartif - Franc, Philip --- "Big-Data, Surveillance, Sports and the Law" [2016] UNSWLawJlStuS 3; (2016) UNSWLJ Student Series No 16-03

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BIG-DATA, SURVEILLANCE, SPORTS AND THE LAW

PHILIP HARTIG-FRANC

The capture and analysis of data has experienced unprecedented growth in recent times namely due to advancements in technology and the subsequent development of capable engines and computers able to assess, interpret and understand big-data in a variety of fields, professions and contexts. In a modern contextual setting, big-data and the subsequent analysis of that which is collected can play crucial roles in terms of security, surveillance and law enforcement, via predictive policing techniques, in a healthcare context, via the digitalising of medical records and pre-emptive measures in dealing with potential viral outbreaks for instance. Furthermore in a commercial context, big-data analysis is crucial for interpreting market trends and patterns, including creating a better picture of whom and what a potential customer base is. Along with these areas, big-data collection and analysis has proven to be an absolutely essential component in recent times, in the multi-billion dollar world-wide industry that is modern day sports. Data analysis can come in many forms in a sporting context, but generally is being increasingly utilised by all the major sporting teams in competitions around the world and across a variety of countries. The English Premier League football competition(EPL), the National Ice Hockey League (NHL) competition and the National Football League(NFL) competition are just some clear examples of where millions of dollars are spent each year to gather, utilise and analyse big-data and will be the primary subject of this essay, but sports such as cricket, golf, rugby and tennis also heavily rely on those same practices and principles and will also be investigated in this paper, as well as whether the analysis of big data has proven beneficial and warranted in these contexts. Scholars, scientists, analysts, coaches and players alike can seemingly benefit and profit from advancements in technology which have allowed masses of data to be collected and interpreted in order to let players take their game ‘to the next level’ and give coaches an insight into their team and their players’ potential performance, arguably like never before. Having said that, claims have also been presented, for instance by scientists and sports experts, such as Wayne Goldsmith, whom have argued that over analysis and big-data in a sporting context has the potential to have a negative outcome and inadvertently have a ‘destructive’^[1] effect in this context, which will also be expanded later in this paper.

Firstly this paper will discuss the various sports which use big-data analysis in interesting and ever changing methods for a variety of purposes, be it athlete performance both on and off the pitch or for enhanced coaching and fan interaction with strategies and statistical analysis of teams. The next part of the paper will deal with the moral and conceptual positives and negatives of analysing big data in a sporting context as well as the claims that is should not be used by various sources, while the final component of the paper will look into examining the legal ramifications and aspects which analysis of big data-can have as well as the intrusive nature it can incur on an athletes’ right to privacy in a modern contextual setting.

‘Sports’ as it were is not a single brand, product or phenomenon which can be easily analysed in itself. For one thing, ‘sports’ are participated in all over the world, virtually in every country and to varying degrees. However that being said, there is no argument that ‘sports’ is an industry which is worth mega-dollars, billions in fact. For instance, the EPL in England, is estimated to be worth roughly 1.3 billion pounds as assessed via income tax and its national insurance contribution^[2] to the British government each and every year. While in 2014, it was estimated that on average each NHL team was worth roughly $490 million dollars US each, while three teams, two from Canada and one from the United States are worth over $1billion dollars each^[3], while the combined value of all the teams in the American NFL are estimated to be valued at a total of $45 billion dollars US.^[4] Interesting figures have recently shown that in the Major League Baseball(MLB) competition in America and the National basketball Association (NBA)competition in the same country, it was estimated that 97% of MLB teams and 80% of NBA teams employ analytics professionals.^[5] In the NBA, all 30 arenas used for competitive games are equipped with the latest ‘up-to-date’ tracking technology, as supplied by the company STATS SportVU, which consists of specifically placing 6 motion-detecting cameras around various spots to closely follow player movement.^[6] With figures such as these, it is plausible to suggest that each and every team, their players, coaches, staff, marketing departments, owners and special strategy coaches are always looking for new ways to give their team an edge in the competitive stakes, much of which can mainly be conducted in a modern contextual setting through the collection and analysis of big-data sets. These sets would have been too large to even be fathomed to be analysed in the past, but today have proven to be invaluable to the success of not only each team which uses them, but the competition in which they play for. In relation to the ever expanding use of big-data in sports, expert Bernard Marr has commented on the positive effect that advancements in technology and analysis has had in differing sporting arenas, stating that ‘development of data approaches to sports has continued to grow and evolve’^[7], while the coach of the Dallas Mavericks, a basketball team playing in the National Basketball Association (NBA) in America has given a definite response that as analytics continues to develop within a modern contextual setting, especially within their team, the results can only be beneficial. Mr Carlisle concluded ‘we’re going to be a better team this year- we know that by the analytics.’^[8]

Looking back over the years, decades and even centuries, methods of data keeping and analysis have always been present in differing sports, but even according to the different experts in their fields, the current level of insight one can gain from the analysis of big-data in a sporting context has proven to be unprecedented. According to expert Bernard Marr, ‘teams and the analytics providers have come up with increasingly sophisticated ways of monitoring and capturing ever-growing volumes of data.’^[9] This is important because it has meant that athletes have been able to push their bodies to the limits of what is humanly possible, as aided by science and mathematics, allowing for greater performances and a greater demand that arguably will continue into the future. In the past, for instance, coaches in the NHL, cricket and other sports, could easily conduct gathering data via having specialists taking in-match notes and statistical figures, such as which player has scored a number of analysis outcomes, an example being such as how many shots had been taken during the match, how many penalty-minutes they took and how long players had been on the ice. While in cricket, coaches could track how many balls each batsman had faced, how many runs they scored and in what areas of the field they played each shot, including whether it was an attacking stroke being played or a defensive one. This was done through human tracking and marking procedures, done without the aides of technology, financial backing, sports scientists and analytical mathematicians or electronic programmes. Recently, during the ‘Asian Cup 2015’ football competition, a Chinese television station was mocked and questioned about their use of ‘old-school’ data-analysis methods when discussing a number of components relating to the competition.^[10] In a recent article written by Eurosport, the largest sporting provider in Europe, they commented on the matter stating, ‘technological advances has seen coverage of sporting events change completely over the past few years, with broadcasters bringing the latest gadgets and inventions to the forefront of the industry.’^[11] Unlike, for instance during broadcasts of the EPL, where presenters have touch screens which automatically have analysed data on every player in the match, in this instance the Chinese presenters used a whiteboard with stickers, demonstrating just how far technology had actually come and how much of a demand there is within the public sphere to have up to date surveillance technologies in place and tools to analyse available data.

At the recent 2014 FIFA World Cup in Brazil, the German National Football team were noted to come out and openly state that they were effectively employing the services of German software giant SAP AG to ‘gain a competitive edge, by having big data on its side.’^[12] Most importantly about the software the German team were incorporating in this instance, is that unlike in the past, their coach was able to receive up to the second analysis of big-data, which was being relayed from SAP’s main database, delivering the German coaches target performance metrics for specific players, up-to-the-second, via sending them to a mobile device.^[13] The Vice-President of SAP Group, Christ Burton, stated that the software allowed the German team and coaches ‘to crawl through complex video and make it simple for them to know what they need to win,’^[14] being sent instantaneously from the German database to the live event in Brazil. Interestingly, Germany competed above their expected result at the tournament and effectively appeared to be playing, arguably, at a level above their opponents, beating Brazil 7-1 in the Semi Final and then going on to convincingly win the final. In this instance, the specific technologically used by SAP focussed on capturing thousands of data points per second, due to the placement of various on-field video cameras, which then relayed instantaneous information to the coach regarding each German player’s pass percentage, shot statistics, movement, ball-handling and dynamics.^[15] It could be plausible to suggest that as Germany were the only team to effectively implement a major company to utilise big-data at the World cup, it is arguably only fair to assume that in the future, other teams will look to use similar technologies in other competitions, to not only gain a competitive edge, but to merely stay ‘up to speed’ with the rest of the competing nations. Finally, SAP vice-president, Burton, commented on the issue that ‘after this we’ll want to maximize what we think is a credible tool for sport’^[16] arguably indicating his belief that the technology has a viable spot in the future, not just in football but sports as a whole.

The Arsenal football team competing in the English Premier League, arguably has some of the most advanced big-data capturing mechanisms in the world, dwarfing those of other multi-million dollar teams in the same or similar competitions. For instance, at the Emirates Stadium in England, which is the home ground for Arsenal when they compete, 8 cameras are installed around the pitch with the specific purpose of capturing big data, which has the effect of tracking every player and their interactions.^[17] This data is then run through an analytical system called ‘Prozone’ which effectively analyses 10 data points per second for each and every player on the pitch, creating a total of roughly 1.4 million data points by the end of the game.^[18] These points are then analysed and compared to roughly 12000 other soccer games from around the world which are already stored in the database. The company, ‘Prozone’ which supplies Arsenal with this cutting edge technology have stated that their main goals and objectives are to ‘Discover the Nature of Performance’^[19] which is an interesting proposition, as a number of sports commentators have recently come out to argue that sports analytics such as these and other measures, are in fact detrimental to the very foundations which sports as a competition is based on, which is hard work and ‘natural talent’ as opposed to ‘nature of performance’, which will be discussed later in this essay.

As well as having surveillance measures which can track athletes actions and movements to create big-data, such as camera’s and GPS monitors, sensory technology within the actual sporting equipment itself is also proving to be invaluable in giving coaches and teams an insight into just who their best and brightest players are. Scholar Bernard Marr, in his literary work entitled ‘Big Data: Using SMART data analytics and metrics to make better decisions and improve performance’^[20] presented the argument that sports scientists are becoming smarter and more cunning in the ways they are gathering and analysing big-data from players.^[21] For instance, he commented, ‘in competitive sport, when a fraction of a second can make all the difference...data analytics are transforming performance.’^[22] He made the argument that athletes are being tracked, via wearable devices, which are constantly gathering data to establish not only their own physical reactions to certain situations, but also their reactions in differing environments. He commented, ‘calorie intake, sleep quality, air quality, heart rate etc... is gathered.. combining and analysing this treasure trove of data undoubtedly helped to make incremental improvements.’^[23]

Predicting and avoiding athlete injuries using big data and analysis, is arguably the most crucial and important role leading into the future for ‘sports scientists’ and mathematicians, along with improving athlete performance. Scholar Travir Nath noted in his article entitled, ‘How Big-Data has changed sports’, that such insights play a vital role in a number of crucial areas, stating that, ‘the wealth of information gathered by wearable technology will eventually provide insight on how activities affect health and predict injuries.’^[24] For instance, football player and Real Madrid star, Cristiano Ronaldo, is currently paid a salary by the Spanish club estimated to be valued at roughly $52 million US dollars a year.^[25] It is plausible to suggest that clubs are desperate to keep their stars on the pitch, injury free and winning matches for their team, which subsequently brings in more fans which ultimately raises more revenue. An interesting case study relates to the Arsenal star, Abou Diaby, who was touted to have a long and prosperous career when signing for the EPL powerhouse team. But since arriving at the club in 2006, the footballer has suffered from 42 injuries, missing a total of 1554 days of potential practice and playing time, being subject to match related concussions, back injuries, knee injuries, thigh injuries, hamstring injuries, sprains, strains and many others, costing the club millions of dollars.^[26] As of 2012, the athlete was signed to a contract of 2.6 million pounds per season, roughly $4 million US dollars, which is important for clubs to consider, especially when athletes still get paid during all of their rehabilitation, and whilst they are sitting out of each and every match. This suggests that teams in the future might shy away from signing athletes to large contracts whom their big-data analysis has indicated are more likely to get injured. Having said that, as noted in the scholarly work by Polonetsky and Tene entitled ‘Privacy and Big Data: Making Ends Meet’, they made the suggestion that within institutions, they must find ‘the right balance between privacy risks and big data rewards.’^[27] This is an interesting concept because it brings up the argument that could be presented in a sporting context, namely that clubs should also be respectful in their surveillance methods of their current and potential player’s privacy in terms of certain medical components of their health and well-being. Conversely, other scholars, such as Almeida et al, have stated that coaches should be ‘encouraging the use of big-data analysis... for improving predication’^[28] in the area of injuries.

The psychological impact of big-data in a sporting context and predicting player injuries is an interesting phenomenon and arguably one which can undermine a player’s confidence and even render them a liability before they have ever set foot onto the playing field. For instance, in most elite sporting teams, players will have to undertake a fitness test before they can be contractually signed up to that club. The case of Loic Remy, a French footballer, demonstrated one instance whereby big-data sets and the analysis of those sets essentially limited the athlete and the potential they had had to sign for a new club and in doing so cost the French striker millions of potential dollars. It was determined through the analysis of sets of information gathered and by surveying the player at his previous teams, that upon further investigation of previous data sets relating to heart rates and medical records for Remy, they ‘had discovered “an anomaly” on the wall of his heart.’^[29] This is arguably important, because, in this instance, Remy was not denied a contract with the Liverpool football team because he was an unfit player or because he had been injured, he was denied a contract purely because, due to vast data-sets and the interpretation of that data, it was discovered that he had a higher chance to potentially have complications down the line relating to a pre-existing conditions which would never have been discovered if not for modern surveillance mechanisms and practices. Furthermore, another controversial issue relating to this case, was that Marseille leader Jean-Claude Dassier, disclosed the information relating to Remy and his potential heart condition in a press conference, stating that Remy had a ‘feasible heart flaw’ and that that flaw could be ‘career threatening.’^[30] It was interesting to observe that such intimate details about an athlete were merely disclosed in a public forum, arguably not paying proper heed and attention to any sort of privacy the athlete might wish to preserve, regarding the issue. Furthermore at a later date, heart experts and physicians appointed by the club went on to state that the condition faced by Remy would subsequently ‘not prevent him from playing at the top level.’^[31]

Scholar Jay Liebowitz is just one of many, who have made the claim that over analysis of sporting teams, players, trends and big-data can in fact have negative outcomes on performances, not just in a sporting context, but primarily in decision-making scenarios. For instance, in his scholarly work entitled, ‘Bursting the Big Data Bubble: The Case for Intuition-Based Decision Making’^[32] Mr Liebowitz makes the argument that in a decision making context, over analysis of big-data can actually have ‘negative consequences.’^[33] Before this point is expanded further, it is important to note that essentially sports and competition, for players and coaches alike, is often comprised of millions of split second decisions, having to be made under intense pressure and scrutiny. Mr Liebowitz continues to state that in this case, intuition, as is done during these pressure filled moments in sports, but also in a business context, is not always correct and is not ‘foolproof’, but can mitigate certain consequences which may arise as a result of decisions which are formulated and based purely on data, as opposed to ‘the analysis of trusted advisors or experts.’^[34] Furthermore, scholar and performance scientist Wayne Goldsmith, has stated that big-data analysis in sports detracts from a number of components which have been done successfully for decades without the aid of such modern technological techniques. For instance Goldsmith argues ‘coaches spend more time behind a desk [analysing data]...than they do actually working and communicating with athletes and staff.’^[35] This is an interesting argument in that Goldsmith is stating that essentially big data analysis is detracting from the ‘human’ element involved in sports and coaching, instead replacing roles filled by experts and experienced, qualified coaches, with analysts reading off a computer screen. Goldsmith concludes by stating, ‘the problem with all this analysis is that analysis by its nature is destructive... the biggest challenge in the analysis era is to learn to use what is ostensibly a destructive activity for a constructive purpose- the enhancement of performance.’^[36]

The issue of surveillance and how new methods of watching and surveying athletes and fans has drastically changed in recent years, has created the argument that athletes are being monitored and scrutinised to a disproportionately high standard, as compared to the rest of the populace. For example, English scholars Andrew Manley and Shaun Williams, have made the argument that newly developed surveillance technologies have allowed coaches of elite sporting teams to essentially act in a ‘big-brother’ manner towards members in their teams, having an impact into various and important parts of their lives, especially those which may affect their sporting abilities and performances.^[37] For instance, they concluded that, ‘coaches are increasingly turning to technology in attempts to zoom in on the slightest deficiencies perceived to be thwarting the performance of their sports teams’^[38] which has arrived by the ‘win-at-all-cost’ mentality, surfacing in recent decades.^[39] Some have argued that it is this exact mentality which detracts from the very essence of sports and natural talent. Such methods being employed by coaches, as what these two scholars termed as ‘Big-Brother surveillance’^[40] is being undertaken through a number of means and avenues, most of which were incapable of being used in the past and have created better sporting endeavours from athletes as they strive to achieve the demands of the public spectators. In this instance, the ‘big-brother’ surveillance measures may range from integrated GPS devices to the cameras being placed stadium-side, pitch-side, in the change rooms, in the gym and in the cafeteria, among others, to heart-rate monitors being placed on the athlete both in-game and outside during leisurely time.

The legalities of some of these measures have been questioned in the past, as it appears plausible to suggest that their highly intrusive nature fully and completely erodes any concept of privacy an athlete, especially those at an elite level, may have. Scholars Manley and Williams argued that, ‘these data management strategies are often deployed without question and are indeed extremely coercive in ensuring that players quickly fall into line with institutional objectives.’^[41] While scholar Bernard Marr made the astonishing argument in his literary work^[42] that surveillance of athletes lives, especially in elite sports, is pervading much more than just inside the actual sporting arena and is having significant impacts into their life in a wider social context too. He commented, ‘teams also track athletes outside of the sporting environment- using smart technology to track nutrition and sleep as well as social media conversations to monitor emotional well-being.’^[43] This leads to the interesting legal observation as to just what extent athletes have right to their own privacy, as opposed to the contractual obligations they have agreed to and their club have factored in. In 2011 a statutory cause of action was submitted by the Australian Athletes’ Alliance Inc. for issues relating to serious invasion of privacy breaches.^[44] In the official submission made by the Alliance, the argument was presented that athletes are held to a too high standard in terms of their contractual obligations and breaches of individual privacy, stating ‘there is no doubt that recent technological developments have increased the need for the law to respond in this area.’^[45] It seems plausible to suggest, as highlighted in the dossier, that the main concern of a number of athletes in a modern contextual setting, it that although they make significant financial gains from their position as an elite sporting identity, newly introduced surveillance methods and mechanisms are eroding any sense of privacy within their lives, both in a sporting manner and away in a more social scenario. According to the paper, ‘recent developments in technology make this an issue of growing concern... professional athletes and other individuals with a public profile should still be entitled to lead their private lives with dignity, free from unreasonable interference into their personal space and from the substantial distress which may be caused by the dissemination of private information or other material.’^[46] Finally, the 2011 case sought to provide athletes with an avenue to sue for damages, when there had been a breach in the ‘suitable privacy standards’ of each athlete.

The Sochi 2014 Winter Olympic Games provided arguably the perfect example of security, surveillance, sports and audience in one interesting case study, leading to the question of whether ‘over-surveillance’ can be beneficial in a sporting context, to maintain security and safety in a wider contextual setting. According to research undertaken by a Russian scientist by the name of Andrei Soldatov prior to the commencement of the Winter Games, he stated that in relation to security services, the Games will be in essence, covered by ‘near-total surveillance.’^[47] Interestingly, it was stated that through-out the city of Sochi for the Games, free internet and wifi will be offered to all visitors and athletes, which will then in turn be gathered with ‘full and unimpeded access.’^[48] This not only related to internet access, but also telephone conversations and other communication providers, which will then use that data gathered to ‘build networks.’^[49] In this particular context, it appears the data which has been collected was not only for a security purpose, but to also create a form of ‘live’ reporting and a live feed into which buzz words which were most commonly being used by people within the city of Sochi at any given time, were then analysed to allow Russian authorities to gain an insight into which were the most popular aspects of the Olympics and which components had ‘people talking the most.’ In this instance, the big-data collected from these various avenues, was then ‘aided by software that helps identify key words and phrases of interest being used in electronic communications’^[50] to do exactly that, allow authorities to know what is being spoken about by people watching the Games and when, where and between who it is being done.

A second interesting concept relating to the 2014 Sochi Winter Olympics, was something which actually happened prior to the tournament even commencing. Due to extensive analysis of big-data, performances of each competing country, outcomes were able to be predicted at the Games before a single event even took place, giving bold, yet surprisingly accurate predictions as to final medal counts and national success at the games. In this sense, company ‘Torque Data’ devised an analytical approach to coming up with five key areas to assess potential medal success for all companies competing at the Games. These key areas included the annual temperatures of each competing country, the previous records of each country, the number of ski resorts per capita, Gross Domestic Profit, population as well as location.^[51] Another variable measured was total number of medals won in each Winter Olympics since 1924. These variables arguably represent just another way in which big-data can play an interesting and important role in a sporting context. However it should be noted that while these massive sets of data can offer a prediction, they can also become skewed and give disproportionate representations. For instance, countries such as Australia, Norway and the UK underperformed in the latest Winter Olympics as compared to how they were predicted to go via the analysis of those big-data criteria, with Australia predicted to win 6 medals, while only winning 3 and Norway for instance expected to win 38, whilst only winning 25.^[52] This was explained via the reasoning that, using Australia as an example, the nation has a relatively high GDP and has spent millions of dollars to create and upkeep ski-fields which are of Olympic quality.^[53] Retrospectively, Germany did much better than the prediction suggested, namely due to the fact that the big-data analysis took into consideration each countries ski-slopes, which is an area the German team tend to focus much less energy and resources on winning, instead excelling in the biathlon event which doesn’t require ski slopes, rather cross country skiing which is not assessed.^[54]

It could also be argued that big-data has made a tremendous change for fan and audience participation in match-day festivities, creating a more interesting and better all-round experience. For instance, game-day analysis and pre-match predictions based on big-data can give the fans an insight into the actual athletes who are participating, weather patterns which may affect the outcome of the game and other factors such as external and internal match conditions, such as pitch quality(highly appropriate in football) and even background information on referees and their previous decisions, such as how likely they are to call fouls, give red cards etc, which can all be of crucial importance. For instance in NFL football, ‘NFL teams use data to pinpoint success rates of plays in different areas of the field, allowing them to adjust plans on-the-fly based on-field position. Additionally, all plays are recorded, time-stamped and tagged with metadata to allow coaches and players to easily analyse them later’^[55],according to sports analyst Thor Olavsrud. This essentially means that not only can coaches have pre-game strategies, but fans can too understand what exactly it is that their team needs to do to win, allowing them a more enjoyable experience following and watching the game. While from a fan and audience perspective, big-data analysis arguably has taken interaction from the living room into the arena unlike ever before, with Olavsrud continuing to state, ‘data and analytics have long been at the centre of broadcast sports production, providing commentators with relevant, real-time data — replays, game data facts, etc. — that helps spectators engage with the event...This includes things like hockey puck tracking to make following the puck easier, or using computer graphics.’^[56]

Big-data has proven to be a highly important tool both during sporting competitions, actually in game and out of it, but also for sports manufacturers who design and produce digital ‘avatars’ which are then used to improve athlete performance, based on copious amounts of meta-data to replicate their opponents. This form of technology has already been implemented in the United States, but was used to great effect recently in Australia during the latest ‘Ashes’ cricketing competition, contested between England and the home-nation of Australia. The fascinating ‘Probatter’ bowling machine combines cutting edge technology, the analysis of copious amount of big-data gathered from censors and surveillance of opposition players combined with an actual bowling machine to produce both a virtual and ‘real’ combination of the two.^[57] According to Australian sporting icon and reporter Robert Craddock, ‘Australia is playing catch-up with a new space-age coaching device that has taken cricket to the cinema.’^[58] Expanding this notion further, essentially the ‘Probatter’ coaching machine uses real life footage and has a projector screen placed in front of the batsman as he is training in the practice nets. Then as the ‘digital bowler’ runs towards the batsman, a ‘sophisticated bowling machine’^[59] based on programming and analysis of massive sets of big-data of each opposition bowler, shoots a ball through a hole representing where the release of the ball would have been from the bowlers hand. This technology was unveiled at Australia’s Centre of Excellence and has been touted as an ingenious piece of technology which allows batsman to face opposing bowlers and their individual ‘bowling styles’ including where they are likely to bowl and closely mimicking their tendencies, to allow batsman to practice in real-match situations.^[60] According to respected sport scientist Marc Portus, ‘the elite guys get so much information from players before a ball is released. A standard ball machine just does not give you that information...The machine can replicate trajectories and outswingers and inswingers, yorkers and bouncers and good length.’

In terms of further legal questions relating to big-data collection and analysis of sporting events and athletes as well as enhanced security, the claim has been made that athletes should both be accepting of the heightened security due to the position as an elite athlete, while it could also be argued that the privacy of athletes has been eroded so much that legal changes should be drawn into their contracts to protect them, to a degree. That being said, the argument has also been presented that due to enhanced surveillance, audience members are also having their privacy eroded in a modern contextual setting. Scholars Payton and Claypoole noted in their book entitled ‘Privacy in the Age of Big-Data’^[61] audience members should be just as aware that most likely every single one of their actions and interactions is being recorded by surveillance and can be used by police at any time during an event and after an event to identify them. This could be for further questioning if some sort of anti-social behaviour occurred, such as a fight, or to possibly serve them with fines or bans. The above scholars noted that if you are ‘catching a professional sports event this weekend...There may be as many cameras in the stadium watching you as recording the game.’^[62] This is arguably an interesting proposition as it suggests that fans, upon purchasing their tickets, have given security and surveillance authorities full rights to take their picture and conduct video recordings at all times during the sporting event. These can then later be relayed on television sets or printed in newspapers for a potential national and international audience base. Payton and Claypoole also made the interesting proposition that ‘security from added surveillance comes at a price beyond your wallet...Surveillance cameras watch innocent civilians as well as criminals [and] data [can be] stored indefinitely.’^[63] Looking at the privacy statement of the Australian branch of SAP for instance, the company that was employed to analyse big-data for Germany in the FIFA World Cup, a number of interesting conclusions can be drawn, namely referring to the collection and distribution of personal information and statistics gathered by the company. If you are an Australian athlete employing SAP to gather and analyse your big-data, the company’s privacy statement has stated that your data will not be held for longer than necessary to conduct activities for which it was collected. Looking at the Australian Privacy Act (2014), it appears plausible to suggest that most big-data analytics companies in Australia, relating to a sporting context, often abide by some specifications laid out in the Act, for instance to have a clear and readily available privacy policy, but will often use ambiguous terms and will, if necessary, such as in a legal context, release your personal information if required.

In conclusion, it is clearly evident that big-data and the analysis of said data has dramatically developed in recent times, as technology has advanced, the need to utilise this invaluable information is becoming apparent in a variety of contexts. Not only has the collection and analysis of big data proven to be vitally important in online sense, relating to predicting policing in a crime, law and order context, for predicting health trends in a medical context or understanding financial aspects in an economic context, big data is becoming invaluable. The industry of ‘sports’ as a whole is big-business. Billions of dollars are spent annually around the world by clubs all with the common goal of getting the best elite athletes, winning matches and ultimately raising revenue, while creating long-lasting club success. Big-data, like in policing, medicine and economics is proving to be an immensely valuable tool in a sporting contexts, with an increasing number of teams in a varying number of sports investing vast amounts of time and money into developing and employing cutting edge analytics software to gather and make sense of magnitudes of data which would in the past have gone completely un-investigated. Not only can big-data be used in analysing a vast amount of information essentially pertaining to every on field aspect of a team and their players during competition, it can also be effectively used to predict injuries in current and future players, while also plays a vital role in a number of off-field components of an athlete in order to improve performance. These surveillance components include heart-rate and sleep monitoring of an athlete, Facebook ‘monitoring’ to check on their emotional state, as well as being used to gain insights into their diet. However, the claim has been made that the over-surveillance of athletes is detracting from the very essence which sports is based on, which is hard work and natural talent, instead picking players based on computer data and predictive algorithms. This has lead to a number of interesting legal and ethical questions which this essay has aimed to address.

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^[1] Wayne Goldsmith, ‘Sport Analysis and the Era of Negativity’, (2014) wgcoaching, <http://www.wgcoaching.com/sport-analysis-and-the-era-of-negativity/>

^[2] Simon Chadwick, ‘Hard Evidence: how much is the premier league worth?’(15 August 2014) The Conversation <https://theconversation.com/hard-evidence-how-much-is-the-premier-league-worth-29863>

^[3] Luke Fox, ‘Forbes: Three NHL teams now worth $1 billion’, (25 November 2014) Forbes <http://www. sportsnet.ca/hockey/nhl/nhl-richest-teams-forbes-toronto-maple-leafs-montreal-canadiens-new-york-rangers-1-billion/>

^[4] Terry Keenan, ‘The $45 Billion reason the NFL ignores despicable behaviour’,(13 September 2014) New York Post, <http://nypost.com/2014/09/13/the-business-behind-the-nfls-blind-side/>

^[5] Trevir Nath, ‘How Big Data Has Changed Sports’, (27 April 2015) Investopedia, <http://www. investopedia.com/articles/investing/042715/how-big-data-has-changed-sports.asp>

^[6] Ibid.

^[7] Bernard Marr, ‘Big Data: The Winning Formula in Sports’, (25 March 2015) Forbes <http://www.forbes.com/sites/bernardmarr/2015/03/25/big-data-the-winning-formula-in-sports/>

^[8] Ibid.

^[9] Bernard Marr, ‘Big Data: The Winning Formula in Sports’, (25 March 2015) Forbes <http://www.forbes.com/sites/bernardmarr/2015/03/25/big-data-the-winning-formula-in-sports/>

^[10] Eurosport, ‘Chinese TV station CCTV provide ‘old-school’ analysis of AFC Asian Cup match’ (22 January 2015) Eurosport.com < https://uk.eurosport.yahoo.com/blogs/early-doors/chinese-tv-station-cctv-provide--old-school--analysis-of-afc-asian-cup-match-133815624.html>

^[11] Ibid.

^[12] Steven Norton, ‘Germany’s 12^th Man at the World Cup: Big Data’, The Wall Street Journal (10 July 2014) <http://blogs.wsj.com/cio/2014/07/10/germanys-12th-man-at-the-world-cup-big-data/>

^[13] Steven Norton, ‘Germany’s 12^th Man at the World Cup: Big Data’, The Wall Street Journal (10 July 2014) <http://blogs.wsj.com/cio/2014/07/10/germanys-12th-man-at-the-world-cup-big-data/>

^[14] Steven Norton, ‘Germany’s 12^th Man at the World Cup: Big Data’, The Wall Street Journal (10 July 2014) <http://blogs.wsj.com/cio/2014/07/10/germanys-12th-man-at-the-world-cup-big-data/>

^[15] Steven Norton, ‘Germany’s 12^th Man at the World Cup: Big Data’, The Wall Street Journal (10 July 2014) <http://blogs.wsj.com/cio/2014/07/10/germanys-12th-man-at-the-world-cup-big-data/>

^[16] Steven Norton, ‘Germany’s 12^th Man at the World Cup: Big Data’, The Wall Street Journal (10 July 2014) <http://blogs.wsj.com/cio/2014/07/10/germanys-12th-man-at-the-world-cup-big-data/>

^[17] Bernard Marr, ‘Big Data: The Winning Formula in Sports’, (25 March 2015) Forbes <http://www.forbes.com/sites/bernardmarr/2015/03/25/big-data-the-winning-formula-in-sports/>

^[18] Bernard Marr, Big Data: The Winning Formula in Sports’, (25 March 2015) Forbes <http://www.forbes.com/sites/bernardmarr/2015/03/25/big-data-the-winning-formula-in-sports/>

^[19] Prozone, (2015) <http://www.prozonesports.com/subsector/football/#765>

^[20] Bernard Marr, Big Data: Using SMART data analytics and metrics to make better decisions and improve performance’, (Wiley Publishers, 2015) 213-215.

^[21] Ibid.

^[22] Ibid.

^[23] Bernard Marr, Big Data: Using SMART data analytics and metrics to make better decisions and improve performance’, (Wiley Publishers, 2015) 213-215.

^[24] Trevir Nath, ‘How Big Data Has Changed Sports’, (27 April 2015) Investopedia, <http://www. investopedia.com/articles/investing/042715/how-big-data-has-changed-sports.asp>

^[25] Forbes, ‘Cristiano Ronaldo’, Forbes (2015) <http://www.forbes.com/pictures/femd45edlfh/2-cristiano-ronaldo/>

^[26] Matt Morlidge, ‘Abou Diaby set to be released by Arsenal after 42 injuries during a nine-year career’, Mail Online, (8 March 2015) <http://www.dailymail.co.uk/sport/football/article-2982592/Abou-Diaby-set-released-Arsenal-42-injuries-nine-year-career.html>

^[27] Jules Polonetsky and Omer Tene, ‘Privacy and Big Data: Making Ends Meet’,(2013) Stanford Law Review SLR ONLINE SLS, <http://www.stanfordlawreview.org/online/privacy-and-big-data/privacy-and-big-data>

^[28] Pedro L. Almedia et al, ‘Psychology in the realm of sport: What it is all about’, (2014) University of Barcelona, 398, <http://repositorio.ispa.pt/bitstream/10400.12/3194/1/RPD_23_395-400.pdf>

^[29] Andre Collins, ‘Loic Remy’s transfer to Chelsea and the medical mystery at Liverpool’ (31 August 2014) The Independent <http://www.independent.co.uk/sport/football/transfers/loic-remys-transfer-to-chelsea-and-the-medical-mystery-at-liverpool-9701710.html>

^[30] Robin Bairner, ‘Olympic De Marseille Confirms Loic Remy has a heart problem’, (20 August 2010) GOAL, <http://www.goal.com/en/news/90/french-football/2010/08/20/2079639/olympique-de-marseille-president-confirms-loic-remy-has-a>

^[31] Simon Yeend, ‘Harry Redknapp shock at Loic Remy’s Liverpool medical mystery’, (29 July 2014) EXPRESS, <http://www.express.co.uk/sport/football/493019/Harry-Redknapp-s-shock-at-Loic-Remy-s-medical-mystery>

^[32] Jay Liebowitz, ‘Bursting the Big Data Bubble: The Case for Intuition-Based Decision Making’, (CRC Press, 2015) 126.

^[33] Jay Liebowitz, ‘Bursting the Big Data Bubble: The Case for Intuition-Based Decision Making’, (CRC Press, 2015) 126.

^[34] Ibid.

^[35] Wayne Goldsmith, ‘Sport Analysis and the Era of Negativity’, (2014) wgcoaching, <http://www.wgcoaching.com/sport-analysis-and-the-era-of-negativity/>

^[36] Ibid.

^[37] Andrew Manley and Shaun Williams, ‘Big Brother’ surveillance in elite sports is pushing a culture with a machine mentality’, (4 December 2014) The Conversation <https://theconversation.com/big-brother-surveillance-in-elite-sport-is-pushing-a-culture-with-a-machine-mentality-34214>

^[38] Ibid.

^[39] Ibid.

^[40] Ibid.

^[41] Andrew Manley and Shaun Williams, ‘Big Brother’ surveillance in elite sports is pushing a culture with a machine mentality’, (4 December 2014) The Conversation <https://theconversation.com/big-brother-surveillance-in-elite-sport-is-pushing-a-culture-with-a-machine-mentality-34214>

^[42] Bernard Marr, Big Data: Using SMART data analytics and metrics to make better decisions and improve performance’, (Wiley Publishers, 2015) 213-215.

^[43] Bernard Marr, Big Data: Using SMART data analytics and metrics to make better decisions and improve performance’, (Wiley Publishers, 2015) 213-215.

^[44] Australian Athletes’ Alliance, ‘Department of Prime Minister and Cabinet, Issues Paper, September 2011, A Commonwealth Statutory Cause Of Action For Serious Invasion Of Privacy’, (2011) Submission of Australia Athletes’ Alliance Inc. < https://www.ag.gov.au/Consultations/Documents/Rightto sueforseriousinvasionofpersonalprivacy-issuespaper/38%20Australian%20Athletes%20Alliance.PDF >

^[45] Ibid.

^[46] Australian Athletes’ Alliance, ‘Department of Prime Minister and Cabinet, Issues Paper, September 2011, A Commonwealth Statutory Cause Of Action For Serious Invasion Of Privacy’, (2011) Submission of Australia Athletes’ Alliance Inc. < https://www.ag.gov.au/Consultations/Documents/Rightto sueforseriousinvasionofpersonalprivacy-issuespaper/38%20Australian%20Athletes%20Alliance.PDF >

^[47] Roland Oliphant, ‘Russia planning ‘neat total surveillance’ of visitors, athletes at Sochi Winter Games’, (6 October 2013) The Telegraph <http://www.telegraph.co.uk/news/worldnews/europe/russia/ 10359587/Russia-planning-near-total-surveillance-of-visitors-athletes-at-Sochi-Winter-Olympics.html>

^[48] Ibid.

^[49] Ibid.

^[50] Ibid.

^[51] M. Allwright, ‘Could a big data model predict performance at the Winter Olympics’, (2014) Torque Data <http://torquedata.com.au/could-a-big-data-model-predict-performance-at-the-winter-olympics/>

^[52] Ibid.

^[53] Ibid.

^[54] Ibid.

^[55] Thor Olavsrud, ’10 Ways Big Data is Changing the Business of Sports’, (23 September 2014) CIO, Slides 1-10 <http://www.cio.com/article/2687035/big-data/164523-10-Ways-Big-Data-Is-Changing-the-Business-of-Sports.html#slide2>

^[56] Thor Olavsrud, ’10 Ways Big Data is Changing the Business of Sports’, (23 September 2014) CIO, Slides 1-10 <http://www.cio.com/article/2687035/big-data/164523-10-Ways-Big-Data-Is-Changing-the-Business-of-Sports.html#slide2>

^[57] Robert Craddock, ‘Rise of the Probatter machine’, (17 November 2010) Herald Sun, <http://www.heraldsun.com.au/sport/cricket/rise-of-the-probatter-machine/story-e6frfg8o-1225955212876>

^[58] Ibid.

^[59] Robert Craddock, ‘Rise of the Probatter machine’, (17 November 2010) Herald Sun, <http://www.heraldsun.com.au/sport/cricket/rise-of-the-probatter-machine/story-e6frfg8o-1225955212876>

^[60] Ibid.

^[61] Theresa Payton and Ted Claypoole, ‘Privacy in the Age of Big Data: Recognizing Threats, Defending Your Rights, And Protecting Your Family’, (Rowman & Littlefield, 2014) 113.

^[62] Ibid.

^[63] Theresa Payton and Ted Claypoole, ‘Privacy in the Age of Big Data: Recognizing Threats, Defending Your Rights, And Protecting Your Family’, (Rowman & Littlefield, 2014) 113.