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About soccer betting statistics over betting

About soccer betting statistics

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This is particularly important on the attacking end of the field. Their raw numbers, or their per-appearance numbers will make them look like mediocre attacking players when in fact they are being incredibly productive. Shots It sounds obvious, but the number of shots a team takes and concedes turns out to be really important, and a fairly predictive measure of future success. Building on the work of hockey, early soccer analysts used tools such as Total Shot Ratio and PDO as tools for predicting future success based on past shots, and it works quite well.

Using shots means more data, and that data is surprisingly predictive. There are, of course, good shots and bad shots. And some teams are better at taking more of the former, and others rely heavily on the latter. Shots are similarly useful when evaluating attacking players. Almost all great attacking players take a lot of shots. The idea of the player who is relatively conservative about firing away but is a deadeye when he hits the ball is largely a myth.

Part of what makes great soccer scorers great is that they are able to get their shots off. Similarly to evaluating teams, it can be tricky to account for players who take a lot of bad shots. But, after accounting for that one useful way is to also look at shots within the yard box as well as total shots , looking for players generating a lot of shots is a good way to find guys who are going to score a lot of goals.

Players who score on a high percentage of the shots they take are not necessarily good shooters. They are. But, over the course of a game or a season, or five seasons, the amount that those skill differences matter pales in comparison to both the amount of the kinds of shots they take matters, and blind dumb variance.

Good teams tend to have high possession statistics. That is because good teams tend to have good players, and good players tend to be good at doing things such as passing the ball accurately to other good players, or taking the ball from bad players on the other team. But, playing a high-possession style does not, in and of itself, make a team good. There are plenty of club teams, such as Chelsea or Atletico Madrid that have chosen to play a style that focuses on defending without the ball and counterattacking effectively.

Those teams maximize their personnel and tactical choices to effectively execute that style, and they are perfectly capable of staying at the top of European soccer by doing that. This is particularly important in international tournaments where teams are formed by nationality and not by professional planning.

Collections of talent are unavoidably awkward fits, as opposed to being cohesive units. The top teams in the world such as Germany, Spain or Brazil all fit together and are happy to be possession machines. But for many others, the talent pool leads to adopting defensive strategies that downplay possession in favor of conservative positioning. Trying to judge middle-tier World Cup squads by their possession percentage is a recipe for disaster. Expected goals remains the gold standard for predicting future performance.

Conceptually the idea is simple. Instead of counting shots, give each shot a value reflecting the likelihood it will be a goal. Instead of looking at goals, or shots, look at expected goals taken and conceded. That does a better job of predicting future results.

Building team ratings both in attack and defense based on some form of xG is definitely a best practice. The devil is in the details. Nor is having the data to do it accurately. Some aspects are easy to isolate. Where on the field is the shot from, both distance and angle? What part of the body is used to take the shot?

Headers, for example, result in fewer goals than kicked shots do. Olivenza 1. Atletico Monzon 1. Burgos Promesas. Arenteiro 2. Paiosaco 0. Fisterra 1. Santa Ana. Real Aranjuez. CD Mensajero 1. Racing Murcia 2. Los Garres 0. Malaga II 3. Union Estepona CF 0. Sporting de Huelva. Madrid CFF. Atletico Madrid W. Valencia W. Barcelona W. El Olivar U Badajoz U Valencia U Marina U Real Zaragoza U Getafe U Calavera U Sevilla U Santa Fe U Castilleja U Txantrea U Valvanera U Oyonesa U Italy -.

Atalanta 1. Reggina 1. Chievo 2. Calcio Padova. Borgosesia 1. Saluzzo 1. Venezia U19 0. Atalanta U Genoa U Lazio U Torino U France -. Strasbourg 1. Nantes 0. Auxerre 1. Grenoble Foot 38 1. Amiens SC 1. Brest 0. Dijon 0. Caen 1. Scotland -. Kilmarnock 1. Livingston 1. Mirren 1. Mirren Win 4. Germany -. Portugal -. Sporting Braga.

Oliveira Hospital. Canelas Valadares Gaia. Vila Cortez. Caldas Win Draw Sintrense Win. Netherlands -. Mexico -. Ciervos 0. Azores de Hidalgo 1. Poland -. Turkey -. Galatasaray Win Draw Alanyaspor Win. Belgium -. AS Eupen 1. KRC Genk 1. Club Brugge 2. Czech Republic -. Slovenia -. Koper 1. Croatia -. Rijeka 2. Denmark -.

Fremad Amager 1. AGF 2. Brazil -. Internacional 2. Fortaleza 1. Friburguense 0. Chile -. Greece -. AEK Athens 1. PAOK 1. Olympiakos Piraeus 2. Angola -. Argentina -. Austria -. Colombia -. Cyprus -. Estonia -. Hungary -. Iceland -. India -. Israel -. Luxembourg -. Malta -. Nicaragua -. Paraguay -. Qatar -. Romania -. Saudi Arabia -. Somalia -. Sudan -. Switzerland -. Uruguay -. Match Stats - Finished Matches. Sunderland U18 1. Australia -. Premium is Here!

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The stats you need when betting on football. Analysing the mountains of available football data for betting can be extremely time consuming. Matchbook explains. 1. Never start betting with hefty amounts. Start with low stakes. · 2. Brush up your sports and betting knowledge every now and then. · 3. Analyse your bets before. forexshope.com › soccer-stats-to-know-betting-world-cup-analysis.