Explaining the Likelihood and Variance (aka Error) stats
Variance Stats (aka Error Stats)
The variance stats show an average difference from the starting handicap line. It gives you an idea of whether a team is over/undervalued and shows which league/teams the market has priced most inaccurately in the past.
The calculation is: [Team’s score difference] -/+ [Team’s starting line]; always using the absolute value.
Here is an example of Asian Handicap error stats based on four games:
- A home team’s starting Asian Handicap line is set at -0.5, they won the game 3-1; the average error equals 1.5 [ 3-1 => 2 – 0.5 => 1.5 ]
- A home team’s starting Asian Handicap line is set at -1, they lost the game 2-4; the average error equals 3 [ 2-4 => -2 – 1 ) => abs(-3) => 3 ]
- An away team’s starting Asian Handicap line is set at+0.75, the game ended 2-2; the average error equals 0.75 [ 2-2 => 0 + 0.75 => 0.75 ]
- A home team’s starting Asian Handicap line is set at +1.25, they won the game 1-0; the average error equals 2.25 [ 1-0 => 1 + 1.25 => 2.25 ]
Based on these four games, the average error equals 1.875 => (1.5 + 3 + 0.75 + 2.25) / 4 (number of games).
Here is an example of Goal-line error stats based on four games:
- The starting line of Goal-line is set at 2.5, the final score 3-1; the average error equals 1.5 [ 3+1 => 2.5 – 4 => abs(-1.5)=> 1.5 ]
- The starting line of Goal-line is set at 2.75, the final score 2-4; the average error equals 3.25 [ 2+4 => 2.75 – 6 ) => abs(-3.25) => 3.25
- The starting line of Goal-line is set at 4 , the final score 2-2; the average error equals 0 [ 2+2 => 4 – 4 => 0 ]
- The starting line of Goal-line is set 2,25, the final score 1-0; the average error equals 1.25 [ 1+0 => 1 – 2.25 => abs(-1.25 ) => 1.25]
Based on these four games, the average error equals 1.5 => (1.5 + 3.25 + 0 + 1.25) / 4 (number of games).
The lower the number is, the more accurate the work the bookmakers have done with pricing games. We recommend taking a look at teams with a greater number as these teams have been harder to price for bookies and have more potential value. The same model applies to the Goal Line and Asian Corners market.
Error AH 5/10/15 – variance stats of Asian Handicap based on the last 5/10/15 games.
Error GL 5/10/15 – variance stats of Goal-Line based on the last 5/10/15 games.
Error AC 5/10/15 – variance stats of Asian Corners based on the last 5/10/15 games.
We have listed teams with the greatest average difference from the opening line (Asian Handicap & Goal Line & Asian Corners) on the Statistics page, as well as on every league page, for instance, England Championships.
The numbers represent the % of times an event has happened thus far based on the previous results. For instance, FH Over 0.5 80%. The small green number indicates the number of games these stats are based on. In the given case, the home side stats are based on the last 10 games, and 80% means that 8 times out of 10, they have either scored or conceded at least one goal in the first half. The away team, on the other hand, has scored or conceded at least one goal in all of the last 10 games. The number underneath (90%) these two is the average of both.
If these stats are very high or low, then this means it has happened on a very regular basis, and the likelihood is that there’s an increased probability it will happen again.
- Green stats are designed to be mainly used for “Over” (Goal-line, Corners) markets.
- Red stats are designed to be mainly used for “Under” (Goal-line, Corners) markets.
- Pink/Yellow stats are a little less reliable to bet on, as these outcomes have been less consistent based on the team’s previous games. Yet, a high yellow stat like 80% on the “Winning Half-Time” or “Scored First-Half” market is still a quite reliable indicator in some cases.
It is never suggested to just blindly choose the highest percentages and create a “once in a lifetime” accumulator based on it. It is essential to conduct additional research using the team statistics, for example, and checking the current form, league, injuries, H2H, and so on. For instance, average stats of FH Over 0.5 goals can be 90%, but it could be that both sides have conceded in most of the games, and scored a few times only. It is advisable to avoid such games.
One thing that is recommended to use is the likelihood scanner on either the In-Play or Schedule page to filter the list of games by likelihood stats. This way, you can spot the potential value bets quickly.
Additionally, these stats can be used for creating custom notifications. Choose the Likelihood option from the Type dropdown, and then set the Event value, as well as any other values. Add more rules that are based on Odds and Stats to create powerful and instant in-play or pre-game alerts.
Read more about creating custom notifications here.
Many of you are already familiar with the backtesting system, but if you are not, we recommend reading the following article first: In-Play Notifications Backtesting System. In a nutshell, the backtesting system provides you a unique opportunity to determine your custom notifications’ profitability without need to collect data for months. With the latest update – […]
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