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Sports as we know it today has come a long way. There were times when watching sports on television was considered a massive step forward in terms of technology. Fast forward 60 years, watching sports on television has become the most basic thing. Today we watch sports on the go on our mobile phones or any device with a screen and internet connectivity. Proud of how far we've come, aren't we? Hopefully I can change your opinion on that by the end of this article.

What is sports all about? Sports is a bunch of people getting together to play a game with pre defined rules and a referee to ensure that these rules are adhered to during the passage of play. I am a sport lover and play sports all time. My love for tennis and soccer in particular cannot be defined. My issue when it came to technology and advanced analytics was with the game of soccer in particular. Soccer is such a beautiful game. The strategies that the coaching staff come up with and the way it is executed on field by the players, it actually is a thing of beauty. I was a soccer player myself (just an average one at that) and have been part of various teams. I know firsthand how strategies are built, how much thought goes into one single run of play.

Enter -> Advanced Analytics

Most of you would've seen the movie Moneyball. The movie was based on the book Michael Lewis wrote in 2003. It talks about how a jock turned luminary uses advanced statistics to gain a competitive edge over his better funded opponents. This book brought about a revolution is sports. Fans and boards of soccer clubs didn't want to settle for subpar statistics or analytics anymore. What Moneyball did is, it took an old cliché - "sports are businesses" and made us move on to the next logical question - "how do we do things smarter?"

Now let's talk about advanced analytics. Advanced analytics in today's world plays a massive role in every business sector. Advanced analytics has been a boon for us. Moving from descriptive analytics to prescriptive analytics, we actually have come a long way. In various businesses, where the requirement is demanding, advanced analytics are of utmost importance.

When we look at soccer, its a game that does not require too much machine intelligence, it is a game that needs the human element. When you bring in analytics and technology and try to reduce the human element in the sports, it simply just crushes the spirit of the game.

Relying on analytics heavily killed the Premier Leagues long ball game and brought in the pressing, continual passing tiki-taka. Each league for that matter had its own style of play. The Premier League had the brash and brazen style of football that was termed "The way real men play football". There were beautiful long balls, harsh tackles but all the players just sucked it up, walked it off and it was all up to the referee on the pitch to penalize the offender or not. There were arguments and fights, the passion from the fans was crazy, that was the football that screamed of passion, when players got in the face of other players not fearing punishment. The Eric Cantona's, the Ivan Genaro Gattuso's, the Jaap Stam's of the football world went missing soon enough and the diving and the biting began. Then there was the tiki-taka style of football that was played in the Spanish La Liga, the silky style of play that caught everyone off guard. The legendary Pep Guardiola and his army at Barcelona were the masters of the tiki-taka. There was Real Madrid who were always a star studded line-up with excessive parts of their play relying on lightning quick counters which most often than not left the opponents stunned. There was Manchester United who had their own brand of football being managed by the legendary Sir Alex Ferguson. That United team was a team of sheer grit and character. Each of these leagues had their own beauty and the teams had their own style of play.

When you bring in excessive technology and analytics, there emerge sorry technologies like VAR (Video Assistant Referees).

There are 3 stages as to how the VAR works:

Step 1

Incident occurs

The referee informs the VAR, or the VAR recommends to the referee that a decision/incident should be reviewed.

Step 2

Review and advice by the VAR

The video footage is reviewed by the VAR, who advises the referee via headset what the video shows.

Step 3

Decision or action is taken

The referee decides to review the video footage on the side of the field of play before taking the appropriate action/decision, or the referee accepts the information from the VAR and takes the appropriate action/decision.

Now the referee can consult with VAR for basically any doubts he wants clarified. What does this do?

• Removes the human element from the game.

• Takes up excess time and brings too many stoppages within the game, a game that was previously free flowing and continuous.

This makes it similar to Formula 1 racing. The analytics which brought about the fuel weight management systems and the numerous pit stops took the continuity out of the race and viewership reduced with the increase in technology. A pretty similar trend might occur in football if this implementation becomes mandatory.

The Positive Side of Advanced Analytics in Soccer:

Analytics are not all that bad in football. Let's take the case of when Simon Wilson joined Manchester City in 2006. Simon Wilson was a consultant for an analytics startup called Prozone initially. He joined City to start a department of analytics and hired the best data analysts under him. He wanted to change the way how data was used by football teams. He saw that, after a defeat there was no introspection as to why they had lost and what needed to be done next time. City were a mid table club at that time. In September 2008, when the club was acquired by the Abu Dhabi United Group for Development and Investment, a private-equity outfit owned by a member of the Abu Dhabi royal family, the team suddenly found itself with the resources necessary to mount a challenge for the Premier League. Today, Wilson is Manchester City's manager of strategic performance analysis. He has five departments under him, including the team of performance analysis, which is now led by a sports scientist named Ed Sulley.

After each match, the team's performance data would be examined. The list is extensive. Line breaks (a rugby term), ball possession, pass success rates, ball win/loss time ratio were what used to be analyzed. "Instead of looking at a list of 50 variables we want to find five, say, that really matter for our style of play," says Pedro Marques, a match analyst at Manchester City.

"With the right data-feeds, the algorithms will output the statistics that have a strong relationship with winning and losing." Wilson recalls one particular period when Manchester City hadn't scored from corners in over 22 games, so his team decided to analyze over 400 goals that were scored from corners. It was noticed that about 75 percent resulted from in-swinging corners, the type where the ball curves towards the goal. The next 12 games of the next season saw City score nine goals from corner.

Teams are investing heavily in analytics today and it is working in their favor. Look at where Manchester City are today, sitting atop the Premier League table and not being threatened at all. Look at Manchester United this season, their game has been such where their possession percentages are low but their goal conversions are high. The Manchester Derby on 7th April 2018 saw United have only 35% of the possession but they managed to trump City 3-2. Each team has their set of analysts who provide inputs as per the strength of the team.

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All serious coaches and sports athletes understand that winning is in the details. That's why performance analysis is an important tool for outdoor sports: there is certainly no greater technique to attain precise insight into each and every aspect of a game, whether it's a community youth match or the big final for an elite team.

By accumulating statistics concerning athletes, games and even seasons and displaying performance measurements in easily understood stats and visuals, performance analysis applications for outdoor sports allow coaches and players to take their game to the next level.

Currently there are a variety of differing methods of monitoring and aggregating data for sport performance analysis. Some analytics tools have their foundations in video, and employ cameras positioned around the field to record every moment of the match. The videos are then analysed to identify successful techniques and strategies.

Various other applications permit users to carry out observational analysis for the duration of the match: making use of sport analysis software interfaces such as iPad apps, athletes are tagged and their moves are tracked manually. When data is eventually collected, in depth statistics as well as dynamic reports can be created.

However, sports performance analytics tools which use localisation or "tracking" technologies, such as GPS (which has minimal accuracy and precision), COPS (Centimetric Outdoor Precision System) and other positioning solutions are of the most dynamic and widely applicable on the market. As a result of monitoring each athlete's position continually, a wide range of information can be compiled, resulting in unique and varied insight into game dynamics.

The info is reliable and is often accurate up to the centimeter. Examination can be performed and assessed in real-time. Localisation doesn't simply capture the highlights. Sports performance analysis tools that utilize hyper-precise localisation technology are uniquely advantageous as they keep track of several KPIs for all athletes throughout the whole practice, training session or game.

Lots of sport analysis tools automatically compile data, perform motion analysis and clearly present overall performance metrics in a variety of user-friendly ways. Graphs and charts are widely used to detail specific stats and relative team overviews. Together with play-by-play breakdowns, historical data and (spatial) trend patterns, sports performance analysis lets coaches and athletes to really focus in on the most significant details.

As a result of tracking measurements like position, speed, distance, acceleration/deceleration, heart beat rate and
strength, performance analytics tools provide numerous advantages for athletes: pinpoint data illustrates both the
strengths and weak spots of each specific athlete. Positional data also illuminates how each athlete interacts with
the team by using sport movement analysis. These particular objective measures help athletes focus in on aspects
that require development, focus on goals and eventually improve sport performance.

But sports performance analytics isn't only useful for athletes: analytics tools provide coaches with the insight they need to make informed decisions that lead to successful tactics and winning strategies. Coaches are able to use performance metrics in order to gain insight into every second of the game, permitting them to review strategies before and after each match. The data collected through sports performance analytics provides coaches an objective measure of each athlete's potential, so that they're placed in the best position with the most appropriate teammates. It can even assist with the recruitment of new players with specific skills.

Sports performance analytics is also invaluable for broadcasting and sports reporting, and can provide avid audiences unmatched insight into the game! Making use of the sport data collected, real-life graphics, infographic feeds and more can add spice to game playbacks and overviews. On the spot statistics can inform on-the-spot insight into different players and teams, and trend patterns can inform discussions about future matches.



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Artificial Intelligence And Sports Bettings Help

Artificial Intelligence And Sports Bettings Help