Successful Betting and Forecasts: is Any Connection?

Sports betting can become an additional, alternative or even the main source of income, but on one condition: the player uses all available tools that can provide a sure victory over the bookmaker. These tools include, first of all, forecasts and without them to talk about a successful game at the bets is not realistic. Definitely, sports betting is not a casino, where any probability is calculated by the office (of course, not in favor of the player). Sport is much more unpredictable and diverse.

Factors of forecasting in sport

Before considering the tools of sports analytics, it is necessary to disassemble a sports match and determine those factors that will influence the victory of one or another athlete.  A good example is a tennis match, since the number of random factors is negligible here, it is easy to analyze and it is easier to make a prediction on it.  The predetermining factors here are:

• the success of each tennis player separately and the results of their previous meetings;
• personal indicators of the nature of the game – outputs to the grid, feed, number of errors, etc. ;
Quizzes. Biographies of athletes
Ultimate 100 questions, Cristiano Ronaldo, Lionel Messi, Kylian Mbappe, Neymar, LeBron James, Saul Alvarez, Stephen Curry, Conor McGregor, Max Verstappen, Erling Haaland.
• game performance on a certain type of coverage;
• motivation to win.

Of course, this is far from a complete list of features that are accepted for analysis.  But it illustrates how realistic it is to calculate the outcome of a match.

An example from life

Kremlin Cup.  WTA.  Match between M.  Rybarikova and M.  Sharapova.  The average coefficients are 1. 32 on Magdalena and 3. 8 on Maria.  That is, BS judged Sharapova’s victory unlikely, despite Sharapova’s confident return to the court, high motivation for victory and the previous meeting, which ended in favor of the Russian tennis player.  And not mistaken – the match ended in favor of the Slovak 2: 0 [7: 6; 6: 4].

Why was this forecast made?

• Sharapova is hard after a long break on the court.
• Too long a series of victories of Mary (inclusion of probability theory).
• Magdalena showed the whole season a successful game and a lack of risk appetite.

This is a small part of the variables used to analyze the upcoming match, but as a justification for the declared outcome it fits well. And the value of such a player is just the reasonableness of the outcome, its compliance with the declared BS coefficients, which should lead to an understanding of the profitability of the coefficient at a long distance and a relatively acceptable margin bet.

But, if the forecast was not used, then the beginning player with some probability of bet on Maria (and, accordingly, would lose). Alternatively, the player could go on the path of the experiment in Plymouth and make a bet “like everyone else”, which would predetermine his winnings, but which would not be professional.

Important! You can’t consider the BS coefficients as true in the last resort, since bookmaker analysts may be mistaken.  In addition, often the players themselves make trouble, making deliberately loss-making bets (lowering the coefficient).  This is a manifestation of the collective unconscious, on which a bookmaker and a professional player can “cash in”.

The algorithm ASB, which we use to obtain forecasts, allows you to get an advantage over the bookmaker in 5-8%.

Methods of forecasting

Sports analytics is divided into statistical and mathematical.  The difference between them is huge, because, despite the approximately identical initial data used for analysis, their actual use is radically different.

The use of statistical forecasting is based on any possible factors on the basis of which the conclusion is drawn.  In some ways, the method resembles induction (from private to general), the effectiveness of which is determined by the analyst’s ability to analyze the upcoming match, the quality of sources of information and the final interpretation of the data.  That is, the human factor in statistical forecasts is the determining factor.  The transmission of statistical forecasts rarely exceeds 60%.

It is interesting! A good example of statistical analysis is the behavior of the character played by Camberbatch in the Sherlock series (based on the works of A.  Conan Doyle).  The hero collected statistical data about the surrounding world, then using induction (mistakenly called by the writer and writers “deduction”) applied the knowledge acquired, compared them with the evidence and disclosed the crime.

The mathematical method is based on an algorithm that performs a mathematical calculation of the input data.  In this case, only those factors that can be expressed by a number or a coefficient are taken into account.  So, the algorithm does not take into account either the psychological mood of the athlete, no possible illness, or physical condition.  And unlike the statistical one, the human factor has no influence on the result of mathematical analysis.  Mathematical predictions prove to be true in more than 60 cases out of 100.

It is interesting! The properties and possibilities of mathematical analysis can be judged from the movie “Mind Games” about the young D.  Nash, the mathematical genius, the creator of the “Game Theory”.  Nash’s works are used universally, from economics and biology, to sports and military bets.

A little about analysts

Ironically, the human factor in sports forecasting can play a decisive role.  And it is he who explains why the accuracy of mathematical forecasts is growing year by year, and statistical forecasts rarely “break” the BS line.  To understand this phenomenon, one should turn to applied psychology, in particular to the SMIL test (MMPI).

Important! The test of personal accentuations is designed to determine the professional suitability of American pilots for military service.  Used today to create psychological portraits and is a key tool to understand the inner picture of the world and the inherent personality traits.

In accordance with the descriptions of personal accentuations, the main “suppliers” of statistical forecasts will be:

• Hysteroid (demonstrative behavior, desire to be noticed, emotional lability);
• schizoids (thinking outside the accepted standards, a propensity for symbolism, a desire for analysis, albeit with a lack of basic data, life in its “inner world”, the interpretation of the acquired knowledge regardless of the real world);
• hyper-personalities (optimism, sometimes reaching manic, the tendency to become a leader even where it is not necessary and harmful, the desire to lead at any cost).
• Follow the link and get your prediction before the match starts.

As can be seen from the “general features” peculiar to individuals with these accents, there can be no spe- cific performance in the analyst’s speech.  Unless the schizoid type of personality who has managed to socialize will give relatively accurate predictions based on his desire to analyze everything and everything.  Others will be engaged in forecasting (especially on voluntary, that is, free principles) only under the influence of the desire to be seen, to become a leader, to receive emotional feedback.  And if for the hypertensive person the quality of this connection is important (so he will try to give a correct prediction), then the hysteroid will in principle do not care what response will be if only he was.

But mathematical algorithms in sports forecasting can be created only by psychasthenics.  They are characterized by the most complete and detailed analysis with the collection, processing and use of any factors that can be crucial to the final result.  It is the psychasthenic that has enough perseverance in the comprehensive development and subsequent refinement of the mathematical algorithm.  And he will try to work for the result – the inherent anxiety will not allow him to give wrong predictions.  And the results will be presented to the general public only on condition that the developer himself is satisfied with the operability of the algorithm.

Psychiatric patients rarely work with statistical predictions, as they tend to automate the process.  In addition, some imaginary difficulties with external communications (communication with people) do not allow them to communicate with players directly, even through social networks, forums and personal sites.  All this is trusted automatics.

Summing it up, we can say that the best analysts are psychasthenics.  The schizoids concede to them in quality only because of their “ability” to supplement the missing data with borrowings from their inner world.  The other 2 psychotypes that make predictions, in general, are not inclined to deep analysis, and all their “predictions” will be a “game” of Probability.

Mathematical forecasting in sport

It can’t be said that statistical forecasts are significantly inferior in quality to mathematics.  However, it is mathematics that makes it possible to make the forecast more probable.  The mathematical model does not at all pretend to be true, but it will allow to predict the outcome of the sport event with much greater accuracy – the passability is more than 60%, which is the determining factor in the value-betting – the more times a bet is made, the greater the gain will be provided.  But, the mathematical model is also influenced by the theory of probability, but the variance will have a high significance, corrected for Einstein’s calculations.

Let’s analyze a simple model of a baseball game.  “Cleveland Indians” against the “Chicago Cubs”.  Suppose that in the near future neither the composition, nor other significant factors will change, but 100 games will be held.  In accordance with the mathematical forecast, baseball players from the Chicago club must win in 70 games out of them.  But, this does not mean that the first 70 matches the team will win, and starting with 71 to lose.  Moreover, this is excluded by the theory of probability – the more wins in the series will be won, the less chance that the next one will happen.  And vice versa.

Now, imagine a novice player making a bet on the “Chicago Cubs”.  The bet loses.  He makes a new one, and again loses.  That is, at a short distance, the player’s loss is obvious and there is a risk of complete devastation of the bank.  This effect, called the dispersion, can put an end to the career of the player and cause him to be disappointed in the bets for sports.  However, if the player continues to bet on the “Chicago Cubs”, he will return the loss and will be a plus.  With a score of 70% of victories and the accuracy of sports predictions of more than 60%, a full refund of the bank will occur at an average distance, a long player will come out in a stable plus.  The main thing is not to play on “raising” the series, that is, remember the effect of dispersion.

Modern mathematical algorithms radically differ from ordinary stochastic hierarchical expressions, and take into account the dispersion effect and the probability theory when calculating a sporting event.  At the same time, the development of the mathematical model implies the consideration of the BS line when creating a preliminary site for analysis, since data of the “Plymouth experiment” can’t be neglected.

Example of a winning strategy: value-betting

Among all the variety of strategy games against bookmakers, the most promising is value-betting.  As mentioned above, even a mathematical forecast does not guarantee a 100% result, so a raise game in any form (from x2) will only help you to say goodbye to the bank – the dispersion effect may partially overlap the Probability Theory.

“Valuei” does not assume a high risk, and if the player is not set to win in a short series, will get a good increase in capital over a long distance (for a short game it will not work).  When making a bet, the player must be guided by the result of the forecast and common sense.  Emotions here are not the place, as well as sympathy for individual teams and players.  You should consider the game with BS not as a gambling event, but as a routine job.

An example from life. Volleyball, South Korea, V-League, match Suwon Hyundai-Incheon Henkuk (October 25, 2017).  Coefficient 1. 49 with Under 4. 5.  With a bet on Suwon Hyundai with a specified odds, the win will bring 49% of the amount delivered.  The forecast passed – Suvon Hyundai team won 3: 0.  Only 3, so successful bets, will double the original amount.

But, consider the same volleyball: the Super League Italy, the Vibo Valentia-Ravenna match.  Under 184. 5 the coefficient was 1. 92, which almost doubled the bet made in case of victory.  However, in fact, the total was 188, which means a loss of the bet.  When playing on the valouys, such a development can (and should) be ready.  With a strategy to increase (x2 or more), the “discharge” of the bank will be more likely than a large series of failures that preceded this bet.