let's start this video with a test based on these statistics which team do you think won this match the answer may surprise you but these statistics are from one of the most famous one-sided games of football ever played and that is Brazil won Germany 7 in the 2014 World Cup semi-final statistics can be quite misleading and for years now we've become accustomed to seeing the same possession shots and passing metrics after every match under the assumption that these numbers give us an accurate representation of how the game unfolded but the reality is that these numbers rarely paint the whole picture and give us limited insight into a team-specific style of play but in recent years football has undergone a massive revolution in data collection which has ushered in a new era of advanced metrics to get accustomed to and with the amount of data we now have available I believe it's time to upgrade the type of Statistics we use to analyze a match and in today's video we're going to be taking a look at some of the best new metrics to keep an eye on Welcome Back to Football meta if you want more insight into all of the advanced metrics we're going to be talking about today then make sure to check out our fantastic sponsors at soccerman with in-depth team and player metrics to help you improve your knowledge of the game the link will be in the description down below and make sure to check out the rest of the descriptions for some useful links to free websites I use daily so without wasting any more time let's start with a relatively controversial metric possession possession has been a go-to statistic since the dawn of football by some regarded as the most important percentage to keep an eye on by others a nonsense statistic of little value the truth arguably lies somewhere in the middle and throughout the years teams have made history based on their success with varying degrees of possession managers such as Pep Guardiola have achieved incredible results averaging over 65 possession while Lester captured our hearts in 2016 by winning the league with an average of only 42 percent however the main issue that seems to appear when talking about possession is that it gives you no indication of how a team played when they had the ball a team could end the match with 75 possession simply because they circulated the ball around the back line but with very little attacking threat while another team could swiftly counter-attack and win the game with few chances and limited possession and this is where our first Advanced metric comes into play and that is field tilt field tilt is a simple way of showing the territorial dominance of a team it does so by measuring the share of a team's possession but only when considering touches or passes in the opposition's final third so for example if team a has 70 passes in the opposition's final third and Team B has 30 then team a will have a field tale of 70 percent let's take the Premier League as an example Arsenal have been one of the surprise over performers this season and are averaging 58 possession per match the fifth highest in the league showing how they are a team that like to hold on to the ball for long periods of the game Now by including field in this analysis Arsenal move up to second place with 65.2 percent of their passes and touches being in the opposition's third compared to their opponent showing how they are a team that like to box in the opposition and hold the ball in dangerous positions for about two-thirds of the match another example is Tottenham who are averaging 50 possession per match however a field tilt of only 42 showing how they are slightly less dominant in the opposition's final third compared to their London rivals as with all the advanced statistics we're going to be talking about today none of them are meant to replace any other key metric and are to be used together to get a better understanding of a team's style of play so while field won't give us much information on the outcome of a match it can help us understand A team's territorial dominance more clearly and give us more insight into a team-specific type of possession moving on the next metric that needs an upgrade is total shots the amount of shots a team takes gives us little information on what types of shots a team are taking the first Advanced metric and one that is already widely used is expected goals I recently made a video on XG so you can check that out if you want more information but essentially XG allows us to measure shot quality over quantity but there are a number of different metrics we can use to analyze a team and a player's quality in front of goal the first metric to start considering is goal conversion percentage an extremely simple calculation but it gives us great insight into a team's quality in front of essentially it takes a team's total goals divided by the amount of shots taken in this area are Lazio ranks 17th for total shots at 243 but fifth for total goals giving them a goal conversion rate of 14.8 percent the best in the league similarly Brentford topped the charts in the Premier League converting 15.5 percent of their shots into a goal but what if we wanted more information on an individual player's ability to score well we can use the same XG and goal conversion percentage we used in our team analysis but more recent models also allow us to measure a player's shot quality post shot XG or XG on target takes into account the position from where the shot is taken and the coordinates of where the ball ends up in the goal here's an example let's take this strike from Daniel storage against Chelsea in 2018. this shot has an XG of 0.03 meaning the chances of scoring from here are incredibly low however the post shot model takes into account the finishing location of the shot in the top right corner making it incredibly hard to save giving the shot an XG on target of 0.5 a Players whose XG On Target is exceeding their XG are executing better quality shots these two values are combined into the so-called shooting goals added essentially calculating a player's ability to convert low XG chances into more goals the leading player in this metric across Europe's top five leagues is unsurprisingly Lionel Messi at 9.32 SGA with Spurs is Harry Kane taking second place these changes to how we view shots can certainly help us understand a team and a player's quality in front of God and take us one step further in our analysis but the next metric is one that I believe has had some of the biggest Innovations in recent years and that is metrics surrounding passing and dribbling total passes and dribbles are displayed in every post-match statistical analysis but once again tell us very little of how this affected the team and if it led to any dangerous opportunities once again some Advanced statistics such as expected assists are a now well-known metric for highlighting a player's ability to create goal scoring opportunities but the list doesn't end there and there are a lot of new metrics to get stuck into similarly to shots with recent developments in data collection it's now possible to analyze pass and dribble quality over quantity and that is done through what is referred to as expected threat essentially to calculate XT the pitch is divided into lots of small squares each with a value directly linked to the probability of scoring a goal from that specific location and thus the closer you get to the goal the higher the value of XT the further away the lower it is teams and players who consistently move the ball from areas of low XT value to areas of high XT are given a positive score on the other hand players who consistently move the ball from high XT areas into low XT are assigned a negative value as they directly limited the team's probability of scoring a goal it's a metric that can highlight A team's unsung hero or someone who potentially doesn't rack up a lot of goals and assists but can consistently move the ball into more dangerous positions and help the team gain grab unsurprisingly Leo Messi and Kevin De bruyne are once again at the top of this list in Europe but it's a metric that includes everything from midfielders fullbacks and Wingers and can give you good insight into which players help their team progress the ball furthermore a similar metric that highlights a player's ability to increase the likelihood of scoring a goal is expected offensive value added in simple terms players that receive passes with low expected assist value and convert these passes into either higher value expected assists or expected goals a given a positive X OVA score here's an example suppose player a receives a pass with an expected assist score of 0.03 the player then dribbles and puts his teammate through on goal with a pass that has an XA of 0.54 this net increase in XA is given to player a who with his move increased the chances of scoring a goal by 0.51 this metric is usually dominated by Playmakers Wingers and Strikers and gives us more information on which players directly create the most goal scoring opportunities for their team by using these metrics we can gain a deeper understanding of which players teams rely more heavily on and rather than simply counting the amount of passes and dribbles we can add some weight to each individual decision finally the last area that has had some substantial improvements in recent years a metric surrounding the high press and pressing intensity for years the go-to value for this type of statistic was passes per defensive action which essentially counts how many passes the defending team allows the opposition to make before winning the ball back however this is slightly Limited in the sense that if a team who has the ball kicks the ball out of play while under no significant pressure then this is regarded as a positive outcome for ppda essentially measuring pressing intent but not its outcome and this is where new Advanced metrics come into play the first is build up disruption percentage or bdp bdp quantifies the destructive effect of pressing on the opposition's past completion rate by comparing it to its average rate so if a team is successful in their press we should expect the opposition to complete fewer passes than they normally would let's clear things up with an example let's take two teams team a has an average pass completion rate of 86 percent across the season while Team B are known for their aggressive High Press in this game team a underperforms their past completion rate finishing the game at 78 this means Team B effectively reduced team A's past completion by 8 meaning Team B achieved a bdp of 8. teams that consistently reduce the opposition's passing capabilities are usually seen as High Press aggressive mentality teams in the Premier League Jurgen klopp's Liverpool consistently dominate this chart and you can expect your past completion to be 7.7 percent lower when playing against Liverpool similarly Italiano's Florentino often score high in this ranking in this area up given their aggressive man-to-man pressing approach but the Innovations in pressing metrics don't end there and there's a new metric that looks to measure a team's counter pressing intensity GPI is the brand new kid on LeBlanc and helps us understand which teams are the most aggressive once they lose possession essentially it works by taking a look at a team's defensive actions in the highest 40 of the pitch in the first six seconds after losing possession now defensive action can be quite a broad definition and so GPI includes anything from files interceptions tackles and aerial Jewels or anything that looks to prevent the opposition moving up the pitch again as expected Liverpool often dominate this chart in the Premier League with other key teams in Europe being Frankfurt Barcelona and Napoli this metric has also helped us analyze a significant change in how football is being played with League averages for counter pressing intensity having significantly increased in the past six seasons showing a shift towards this more aggressive approach to regaining possession and there you have it all these statistics may seem overwhelming to begin with but simply by understanding what each metric is looking to collect it can take our understanding of the game to the next level and while all stats will always be slightly misleading if we take a look at them individually only by comparing them to other key metrics can we get a truly holistic view of how a team performs and obviously watching the game that that beats any statistic let me know what metrics you think are fundamental for analyzing A team's performance and which metrics should we ignore entirely leave your thoughts in the comments down below for more stats-based content why not check out this video on formations and which is statistically speaking the best in Europe as always if you enjoyed this content then please 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