Soccer tactics, pre-match and in-play strategies, match events, knowledge and myths – part 1

Nowadays, all teams employ analysis staff, specialists in data collection and interpretation who use all the information they can get to plan training sessions, design playing systems, improve and find talents and plot transfers. What a manager does is attempt to increase the index of probability when it comes to winning a match. Data, analysts, tactics and chances are crucial in managers’ attempts at winning games. In this article we will cover, the importance of match analysts and how we should line up with them; a short story for Opta data and how it progressed as a data service; chances, favourites, tactics and myths.

Managers’ match analysts and their daily

As mentioned in our previous article about the important steps before placing a bet, match analysis is one of the crucial parts. It is vital to understand that teams employ people who specialize in match analysis in order to help the manager make the necessary adjustments.

It is important to understand what they do and their step-by-step process before making your own analysis of a match.

Match analysts, hired by teams, spend hours preparing and auditing matches in meticulous detail, examining the attack and defense of their own players and the opposition and preparing background materials on each player’s opponent. Before a match, they will examine at least five of the opposition’s previous matches, combining scouting reports and combining them with statistical data from companies such as OPTA. Using these data and video, they look at style approach, strengths, weaknesses and positional organization. All of that is summed up and presented to the manager, who summarizes further and delivers the assessment to his squad. Some analysts also work one-on-one with individual players. They will sit with them before the match to do some homework and go through their direct opponent’s patterns of play. As soon as the match is over, analysts will go through the game a number of times, along with the coaches, and summarize and review what worked and what didn’t.

Opta and satisfying analysts’ appetite

Since the first football analysts, a whole industry of data providers has emerged.

The first one was Opta Sports, started by a group of management consultants whom in the 1990s, decided to create an index of player performance in football. Opta sports contacted the Premiership and they were given funding by Carling, who sponsored the league at that time, and former Arsenal and England coach Don Howe come on board to provide football expertise. They launched the index in 1996 on Sky Sports and in the Observer newspaper, but soon discovered that the information they were collecting was far more valuable than the publicity the index brought the company.

When Opta started, each game’s events took about four hours to code, using a pen and paper and pressing stop/start on a video recorder. The actions they noted were basic: passes, shots, saves. The level of detail their analysis record now is a world away from those unassuming beginnings. As an example, we can take the 2010 Champions league Final between Bayern Munich and Inter Milan. That night, Opta’s team of three analysts logged a total of 2842 events, around on every two seconds of the match. One was designated to monitor Inter, one Bayern, each one an expert in their subjects – they had been following these teams all season, tracking all their actions and movements. These two guys were joined by a teammate in the role of overseer, pointing out mistakes and omissions.

There are many other companies working in the same data arena as Opta: Impire, Infostrada, StatDNA, STATS.

The market for such data is expanding seemingly without limit and there are coaches, players, executives, journalists, fans and even academics who have a growing appetite for football’s numbers and the video game manufactures, fantasy football leagues and the betting houses which use them to make money.

Betting syndicates and professional players, involved in assessing, managing and exploiting risk, build elaborate forecasting models based on that same data. You can read here about expected goals models.

Long Throw-Ins, one of football most underrated weapons.

The long throw-in is an important set play in soccer, particularly when used as an attacking play near the goal mount. The further a player can throw the ball and the flatter it is, the more dangerous the attacking play will be. To produce such quality throw-in with a good chance of confusing defenders, the player must find the optimum relation between release speed and release angle. It is important event for teams that possess height in their ranks and for this reason it is an attribute that needs to be evaluated and analyzed in regard to team tactics and performance.

Rory Delap’s long throw is the perfect example for the above mentioned. Stoke City’s 2008-09 season was influenced by Delap’s throw-ins. Of their first 13 goals, seven were credited as Delap assists. Every single time Stoke won a throw-in within a closing distance of the opposition box, Delap would move towards the touchline, dry the ball with his shirt or with a towel and proceed to throw it into the box, over and over again. To understand exactly what I mean, you can have a look at the following YouTube video here.

It was easy for Stoke to go with this tactic as they have height in their team and with Delap’s throw-ins, they could easily create chances out of nothing. Besides that, Rory Delap was the only one with the ability to throw long balls with a flat trajectory.

Another example is Aron Gunnarsson whose 2016 European Championship throws led to two goals. His technique is different to that of Delap’s. Gunnarsson prefers to go for height on his throws and to use the drop of the ball to create chances via second balls. It is important to mention that he was an excellent handball player in his youth and may well pursued a career in the sport.

Sam Muggleton is another interesting example. He is 22 years old who currently plays for Chesterfield as defender or midfielder. His throw is capable of reaching the box from basically anywhere in the opposition half. His throw has power, height but not so dangerous flat trajectory compared to Delap’s.

• up/down “facts”

Teams are most vulnerable just after they have scored. It is a statement found in football all over the world, and one born of the tricks played by our mind. Peter Ayton and Anna Braennberg analyzed 127 Premier League games that ended in a 1-1 draw and logged when the opening goal and the equalizer were scored. They divided the reminder of the game, after the first goal, into quarters. So, if a team took the lead in the tenth minute, the rest of the fixture would have four twenty-minute quarters. The analysis showed that it is immediately after a team has scored that it is least likely to concede.

This method can provide good information when in-play trading. Looking at past data for each team in a division, will provide you with information on how it performs when leading/losing with one goal and what is the general pattern that it follows. Moreover, scoring the first goal in a match has a big impact on the game and the chance of a team winning. It can put a top team at an enormous advantage, a mid-table team in a commanding position and a conceding team with low offensive rating at a distinct disadvantage.

The table above shows the Premier league data for 7 seasons and the percentages of team winning after scoring the first goal. All this is a courtesy of pinnacle sports.

We can spot from the above table that if a top 4 team goes ahead, they will win the match over 80% of the time.

Corners don’t have an impact on a team’s score.

Corners in the Premier League are seen as almost the next best thing to a goal, but stats show differently. The data do prove that corners and shots on goal go hand-in-hand – a team that shoots more will have more corners, and vice versa. However, teams that shoot more and get more corners do not score more goals. The total number of goals a team scores doesn’t increase with the number of corners it wins. The correlation is zero. You can have 2 corners or 12 corners per game and that has no significant impact on the goals you will score.

Correlation is used to test relationships between quantitative and categorical variables. The correlation analysis is useful, as we have seen above, because it can show you the relationship between variables and you can make predictions about future behavior. The correlation coefficient shows the relationship with a value and it is between -1,0,1, where 0 means that there is no relationship and -1,1 shows if there is perfect negative or positive relationship.

Based on data, when we combine the odds of corners generating a shot on goal plus the odds that these shots will find the back of the net, we can conclude that the average corner is worth about 0.022 goals – more simply – the average Premier League team scores a goal from a corner once every ten games.

In terms of in-play betting, more corners show us that the attacking team is creating shots and putting pressure on the defense. All this combines with a good shot-on-goal/ total shots ratio can be an indication that a goal might be coming for the attacking team.

Corner betting in-play is a popular market for the experienced in-running bettor with an eye for patterns and game reactions. There is a simple fact that favorites generate more corners when losing by one goal because they are trying to regain control of the score. Besides this, it has to be mentioned that teams win more corners when they are losing against average opponents. Also, top favorites win an average of 6 corners when they win and 8 corners when they lose.

Chances and uncommon occurrences

It doesn’t matter how well planned your trading strategy is during in-play or how solid your pre-match analysis is. All these can be scratched by an uncommon occurrence not just in football but in any other sports. These rare events will eventually happen because of Bernoulli’s basic rule: if we do something for long enough, every possible outcome will occur. That shouldn’t put you off your pre-defined betting plan and this kind of events need to be acknowledged as rare.

So, if a team has played football for a long time, they will eventually come back from three goals down or from four behind as Newcastle did against Arsenal in 2011 and as Arsenal did against Reading in 2012. There is no law other than that of chance preventing you from seeing a team going unbeaten for an entire season, or losing their first twelve games or even a beach ball settling a fixture. The latter is not a joke and that happened to Rafael Benitez’ Liverpool in October 2009 when his team played against Sunderland. During that match, Darren Bent took a shot from the edge of the area and Glen Johnson, a Liverpool defender, tried to block the effort, but failed. Instead the soccer ball clipped a large red beach ball that had drifted on to the pitch and into Pepe Reina’s box. The deflection wrong-footed the Spanish goalkeeper, and Liverpool were 1-0 down. Liverpool had 15 shots that day, compared to thirteen for the home side, and seven corners to one – and they lost to a goal scored by a beach ball. All this can be seen in the following Youtube video.

We do know that such event are statistical outliers. These are values that are numerically distant from most of the other data points in a set of data.

Other scientists have taken things further in their attempts to determine exactly how much of a role chance plays in any given match. One explanation is that the football data show that teams that have already scored one or two goals become more likely to score a third, a fourth or a fifth – that there is something that happens during the course of the game not captured by Poisson’s equation. Andreas Heuer and his team applied mathematical and statistical techniques to twenty years of games from the German Bundesliga as they attempted to discover whether ability and fitness, “match dynamics” – red cards, injuries, momentum – or what scientists call noise, the unpredictable actions of chance, were most significant when it came to understanding goal-scoring patters. The German team concluded that, mathematically speaking, a football match is a lot like two football teams flipping three coins each, where three heads in a row means a goal and “the number of attempts of both teams is fixed already at the beginning of the match, reflecting their respective fitness in that season”. In other words, the quality of your squad determines the number of shots and a given shot has a one in eight chance of hitting the back of the net.

Heuer and his team’s final results were conclusive. They found that fortune first and foremost, then skill and fitness, then things like momentum. That is a surprising finding to fans who believe a team’s skill entirely controls what happens on the pitch.

Are favourites really favourites?

A bookmaker’s career is built on chance and if matches were predictable, nobody would gamble. Team’s form, injuries match state and importance provide the basis for setting the odds and, more often than not, making one team the favourite. These odds tell us something about chance and predictability in sport.

The lower the odds, the more unlucky the favourite for any game has to be to lose, and the more their opponents have to rely on luck to win. When two teams are similar in quality, then luck and on-the-day form decides the contest and the two teams’ odds of winning in the eyes of bookmakers will be identical.

Based on examination of odds in football and other sports, in football a little over half of the favourites win their games. In handball, basketball and American football the favourites win around two-thirds of their games while in baseball it is a solid 60 per cent.  In handball, favourites almost always win, with median odds of 1.28; the NFL ( Perception vs Reality in NFL betting) and NBA have medians of 1.49 and 1.42, respectively. In basketball the spread of odds is most restricted: there are no overwhelming favourites, with the shortest odds being 1.24. But in football, the median odds for a favoured club to win are 1.95.

Bookmakers, in other words, pick favourites less successfully in football than in any other sports. Or, half the time in football, the favourite is not really much of a favourite. This is an import statement to have in mind when doing your match analysis and or your season long term betting strategy.

The favourite not really being a favourite can be explained with two factors – in football, goals are rare, and draws are common. That combination makes setting odds in football much more difficult and makes favourites less likely to win.

Conclusion

The discovery and communication of meaningful patterns in soccer data, such as the above-mentioned events and attributes is what analytics is all about. Managers, scouts, players and owners all want an advantage and knowledge provided by analytics is power.

Football is the most uncertain of the team sports. There are more beach balls and shots against the woodwork in football than in any other game. Almost half the time, the team that is not as well prepared – or has worse players, a raft of injuries or is just not as good – ends up winning.