Any betting market that involves goalscoring is directly related to a clean sheet.<\/strong> For example, if you want to predict an exact score, you may opt for 1-0 as this is one of the most common scorelines \u2014 well, that 0 indicates that a team has kept a clean sheet.<\/p>\n <\/div>\n <\/div>\n\n\n\n Basically, if you bet on a clean sheet, you're betting that the opposing team won't score a goal. Other examples include over\/under goals, win to nil, score casts, and much more, which we'll delve into later in the article.<\/p>\n\n
Ways To Use Player Clean Sheet Stats<\/h2>\n \n\n
\n As we mentioned earlier, clean sheet statistics are an excellent set of data that can be used for many of the typical betting markets \u2014 entire bet builders can be created using these statistics. Below are the most common ways to use clean sheet odds and statistics.<\/p>\n\n
\n Clean Sheets\n <\/h3>\n \n\n
\n Who would have guessed? Yes, you can use clean sheets statistics to predict clean sheets! Players who are able to keep many clean sheets will probably continue to do so, especially when up against weaker opponents.<\/p>\n\n
\n Halftime & Fulltime Exact Scores\n <\/h3>\n \n\n
\n Guessing the exact score is no easy task; games at the highest level can be particularly unpredictable, but if you bet on a team finishing with a score of zero, you're essentially betting on the opponent keeping a clean sheet.<\/p>\n\n
\n Both Teams To Score\n <\/h3>\n \n\n
\n Common in bet builders, this kind of betting involves you predicting whether both teams will get on the score sheet \u2014 usually in the form of \u2018Yes\u2019 or \u2018No\u2019. If you think the players in the squad will keep a clean sheet, you can bet \u2018No\u2019 to indicate that both teams won\u2019t score.<\/p>\n\n
\n To Win to Nil\n <\/h3>\n \n\n
\n To win to nil betting is often considered a \u2018special\u2019 and may not be found for every league or competition. It basically means betting on a team to beat their opponents without conceding any goals.<\/p>\n\n
\n Scorecast\n <\/h3>\n \n\n
\n Another difficult bet to predict is scorecast betting, where two conditions must be predicted. The bettor must both pick a goalscorer and predict the exact result. Understandably, the odds are quite high and the statistics of players not conceding goals can help you decide whether a team will keep a clean sheet.<\/p>\n\n
Clean Sheet Player Betting Tips & Predictions<\/h2>\n \n\n
\n Clean sheet odds are already great, and just betting on this market alone could yield some positive results. Of course, nothing is guaranteed, but there are some things you can do to improve your betting experience.<\/p>\n\n
\n Bet Builders\n <\/h3>\n \n\n
\n One of the most commonly used features in football betting is the ability to combine small, realistic bets together on a single betting slip to increase the odds. This is a bet builder. Betting on a clean sheet is another option that can be added to a bet builder and can be complemented by other types of bets, such as the number of shots on goal, BTTS and many others.<\/p>\n\n
\n Use Other Stats Pages\n <\/h3>\n \n\n
\n It cannot be stressed enough: the more research you do, the more accurate your predictions will be. ThePuntersPage offers a wide range of statistics to ensure you have everything you could possibly need.<\/p>\n\n
\n A great example of using two stats together would be to combine player clean sheet stats<\/strong> and goalscorers stats<\/strong>. Finding a team with a good goalscorer and solid defence could be perfect for scorecast and win-to-nil bets.<\/p>\n\n\n Get Creative\n <\/h3>\n \n\n
\n Don't be afraid to be creative, the statistics page can be used for many other markets, even indirectly. For example, whether a team scores a goal or misses a penalty could depend on the skills of the goalkeeper.<\/p>\n\n
\n A comparison of defenders on the same team<\/strong> \u2014 there could be one defender who has a weaker defensive record, meaning that the team tends to concede more goals when he plays. A bet against the defender keeping a clean sheet could be the right way to go.<\/p>\n\nClean Sheet Player Records<\/h2>\n \n\n
\n Clean sheets have been around ever since they started keeping score in football, even if they weren't always known as clean sheets. The term dates back to the 1930s<\/strong>, when referees wrote the scores on white paper. If a team didn't score, they had a blank scorecard which they called a “clean sheet of paper”, and “clean sheet” has been the go-to term ever since.<\/p>\n\n\n The modern game has evolved thanks to football's data-driven approach; many statistics that would never have seemed important in the past are now vital for teams to gain an edge over their opponents. This has led to more and more data being collected, which is why the following records are relatively modern.<\/p>\n\n
\n Goalkeeper Records\n <\/h3>\n \n\n
\n When we speak of clean sheets, we immediately think of goalkeepers. The man between the sticks is the last line of defence<\/strong> and goalkeeping is often considered the most difficult position on the pitch.<\/p>\n\n\n Perennially underrated, some of the greatest players of all time have been goalkeepers! Here are some of the best of the bunch:<\/p>\n\n
\n Most clean sheets of all time<\/strong>\n <\/h4>\n \n\n\n
Player<\/th> | Total Matches Played<\/th> | Total Clean Sheets<\/th> | Clean Sheet Percentage<\/th><\/tr><\/thead> |
---|
Gianluigi Buffon<\/strong><\/td>970<\/td> | 504<\/strong><\/td>52%<\/td><\/tr> | Edwin van der Sar<\/strong><\/td>820<\/td> | 440<\/strong><\/td>53%<\/td><\/tr> | Iker Casillas<\/strong><\/td>911<\/td> | 440<\/strong><\/td>48%<\/td><\/tr> | Petr \u010cech<\/strong><\/td>781<\/td> | 397<\/strong><\/td>51%<\/td><\/tr> | Pepe Reina<\/strong><\/td>925<\/td> | 358<\/strong><\/td>39%<\/td><\/tr><\/tbody><\/table><\/figure>\n<\/div>\n\n\n Most clean sheets in a single season – Top 5 leagues<\/strong>\n <\/h4>\n \n\n\n Competition<\/th> | Player<\/th> | Clean Sheets<\/th><\/tr><\/thead> |
---|
La Liga<\/strong><\/td>Paco Lia\u00f1o Marc-Andr\u00e9 ter Stegen<\/td> | 26<\/td><\/tr> | Premier League<\/strong><\/td>Petr \u010cech<\/td> | 24<\/td><\/tr> | Serie A<\/strong><\/td>Gianluigi Buffon<\/td> | 21<\/td><\/tr> | Ligue 1<\/strong><\/td>Salvatore Sirigu Mike Maignan Vincent Enyeama<\/td> | 21<\/td><\/tr> | Bundesliga<\/strong><\/td>Manuel Neuer<\/td> | 21<\/td><\/tr><\/tbody><\/table><\/figure>\n<\/div>\n\n | | | | | |
| | | | | | | | | | |