What is 1X2 prediction?

Well, 1X2 betting is mostly popular in football and involves betting on the result in a match with three possible outcomes, which are home win, away win, and draw. This market may also be known as Full Time Result, Match Betting, or Three-Way Bet.

thefootytipster.com - What is 1X2 Betting? - The Footy Tipster

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Make Your Bookie Cry And Pull The Hair By Generating $23,187

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What is 1X2 Betting?

Many inexperienced punters, or those who are new to sports betting, may find themselves looking at the available markets and asking, what is 1X2 betting?

How Does a 1X2 Bet Work?

If you are still confused, here’s a more detailed explanation and includes an example. Basically, the three outcomes of a match between two teams are represented by either 1, 2, or X. This means 1 is for a home win, 2 for an away win, and X for the draw. Using odds from Bet 365, let us use the scheduled curtain raiser for the 2017/18 Premier League season between Arsenal and Leicester as an example. In the Full Time Result market, Arsenal are represented by the 1 as they are the home team. Leicester are the away team, so are represented by the 2, and the draw is X. Looking at the odds, you can see that Arsenal are favourites at 1.36. Leicester are the outsiders, with odds of 8.50, and the draw is priced at 4.75. This means, using a 100 stake, that a bet on Arsenal to win would pay 136 if they’re victorious. Leicester to win is a possible return of 850, whilst the draw would pay 475 if the game finishes level. The 1X2 bet is sometimes also available in handicap betting, as long as there’s the possibility of a draw.

Combining Two of the Three Possible Outcomes

It is possible to combine two of the three possible outcomes, using a Double Chance bet. With this market, you can choose to bet on 1X, X2, or 12. This basically translates into home win or draw, draw or away win, and home win or away win. By combining two outcomes, you have a bigger chance of winning your bet although it would be for lower odds than in a normal 1X2 market. Using the match above, Arsenal v Leicester, let’s look at the difference in possible return. 1X (Arsenal or Draw) – Odds of 1.083. Possible return of 108.30 for a 100 stake

X2 (Draw or Leicester) – Odds of 3.20. Possible return of 320

12 (Arsenal or Leicester) – Odds of 1.20. Possible return of 120

Using our bet calculator, you can work out if it would be more profitable to combine two of the three possible outcomes using the double chance option or in the normal 1X2 market. Want to learn how to be an expert football bettor for free? Join our email course

Other Sports Using 1X2 Betting

Football is the obvious, and most popular, sport which uses the 1X2 betting market, but it’s not the only one. In fact, many bookmakers will offer this market on any team sport which has the possible outcomes of a home win, away win, or draw. Therefore, sports such as cricket, rugby, and even hockey are becoming increasingly popular among punters who use 1X2 betting.

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Which prediction is accurate?

Prediction accuracy is expressed as the correlation between the AMS prediction and the actual score. Accuracy of 1 indicates a perfect accuracy, whereas the accuracy of 0 indicates a random guess.

stats.stackexchange.com - What is "Prediction Accuracy (AUC)", and how is it the number conducted ...

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On the page linked, there are two metrics used to measure predictive accuracy of the algorithm. 1.The first is the usual Area Under the Curve (AUC) of the Receiver Operator Characteristic. As explained in the comments, AUC ranges from 0.5 to 1, with 1 being perfect classification and 0.5 being no better than luck. Since there are only two outcomes, the algorithm can either classify positive correctly, or incorrectly. Similar to flipping a coin, chance will predict correctly 50% of the time, giving 0.5 AUC a "worthless" accuracy. As you increase from 0.5 to 1, your algorithm gets better and better at correctly classifying outcomes. These algorithms are usually trained on a training set to tune parameters and tested on a test set to determine their accuracy and applicability. The AUC is found on the second table on the page. 2.The second of the metrics used is simply the correlation between the predicted outcome and the actual outcome. This was used because the outcomes were not binary; they were linear, and thus classification was inappropriate. This has the range 0 to 1, as there can be 0 correlation between the predicted and actual outcomes. The correlation is found on the first "linear" table on the page. As for the second part of your question, the 98,000 person sample that they mentioned most probably had known outcomes. For example, if your algorithm predicted a case (1), you could compare it to the actual known data to see if your algorithm predicted a true positive (TP) or a false positive (FP). This is how they measure the accuracy. As for the text classification system, you would need to provide more details, perhaps a separate question for that might be appropriate.