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- What role has experience played at the Euros? - Is the average age and number of caps for a Euros squad betting important? - How experienced were previous squads that have won the Euros? - European Championship stats, insight, and analysis How Crucial is Experience at Euro? Understanding the role experience plays in Euro betting is vital, especially given the unpredictable nature of international soccer. Unlike club football, where teams have a consistent roster, predicting outcomes in international tournaments like Euro poses unique challenges. Take the case of England, which participated in 12 matches between the 2022 World Cup and the 2023/24 season. During these games, manager Gareth Southgate fielded 43 different players, showcasing significant squad turnover. This dynamic makes forecasting England's Euro 2024 squad and their performance at the tournament a daunting task. This unpredictability isn't exclusive to England; all 24 participating nations face similar challenges. While favorites may seem poised for victory, historical data reveals that success at Euro often eludes even the most favored teams. Correlation coefficients for average caps and age compared to finishing position The correlation is often next to non-existent though, so we need to drill down deeper to see if any other trends or running themes are worthy of our attention. Analyzing Trends: The Impact of Age and Experience To assess the correlation between team statistics and Euro performance, we delve into historical data from past tournaments. By ranking teams based on finishing position and analyzing factors like points per game, goal difference, goals scored, average age, and average caps per player, we aim to uncover trends that could inform betting strategies. Surprisingly, Spearman's Rank Correlation Coefficient reveals inconsistent correlations between these statistics and tournament outcomes. Contrary to conventional wisdom, success at Euro doesn't necessarily hinge on squad experience. In fact, younger squads with fewer caps have often outperformed their more experienced counterparts. Given the limited correlation, it's essential to explore additional trends and themes to refine our betting strategies effectively. The Importance of Squad Composition Examining the average age and caps per player of Euro squads sheds light on the intricate relationship between experience and success. Analysis of the last six Euros indicates that while winning teams typically field experienced squads, outliers exist among lower-ranking teams. For instance, champions like France, Spain, and Italy boasted squads with significant experience. However, teams finishing lower in the rankings also displayed high levels of experience, challenging the notion that age and caps guarantee success. Average number of caps and ages for the top 16 teams at the last six Euros When analyzing previous tournaments, it is perhaps best to primarily concentrate on the last two editions, as Euro 2016 was the first time the tournament featured 24 teams (as will compete this year). The data from eight years ago in France paints a confusing picture. On one hand, seven teams at Euro 2016 had a maximum of 10 players with no more than 25 caps in their squads, and four of them (Germany, Iceland, Poland, and Wales) reached the quarterfinals. That would indicate that experience is important, particularly as Iceland and Wales were widely regarded to have exceeded expectations. However, only two nations from the top eight for total caps or oldest average age progressed to the quarterfinals. Ireland’s Euro 2016 squad was the oldest among the 112 teams that qualified for the previous six Euros, and while they did progress to the knockout phase, they also won only one of their four matches in total. Deciphering Historical Data A closer look at recent tournaments, particularly Euro 2016 and Euro 2020, unveils nuanced insights. While experienced squads like Portugal and Italy performed admirably, younger and less experienced teams like England and Spain defied expectations, reaching advanced stages of the tournament. The data also reveals a shift in squad dynamics, with Euro 2020 witnessing more inexperienced teams and expanded rosters. Despite this, several underdog teams exceeded expectations, highlighting the unpredictability inherent in Euro betting. Experience scores for teams that reached the final at the last five Euros These stats reveal some interesting observations. The Italy squad at Euro 2000 were led by 105-cap captain Paolo Maldini, but also featured 16 players with no more than 25 caps. Only 8 of the 111 other teams who have competed at the last six European Championships sported a higher proportion of their squad with such little international experience, and it took until Euro 2020 for any of them to reach the quarterfinals. Strategic Insights from Past Champions Analyzing the composition of past champion squads offers valuable strategic insights. While experience often correlates with success, exceptions exist, emphasizing the multifaceted nature of Euro betting. Teams like Italy and Greece leveraged a balanced mix of experience and talent to secure victory, while outliers like Spain succeeded with a blend of youth and seasoned players. Understanding these dynamics can empower bettors to make informed decisions when navigating the complexities of Euro betting. In conclusion, while experience may influence Euro outcomes, it's not a definitive predictor of success. By leveraging historical data and strategic insights, bettors can develop more nuanced betting strategies tailored to the unique dynamics of international tournaments. Now you know how important are age and experience for betting. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- How likely is a run of profitable bettings? - How the margin affects your returns - Identify the difference between luck & skill Is Short-Term Betting Success Always Reliable? The dynamics between a bookmaker and bettor pivot on odds established by the former and the bettor's interpretation of its accuracy. For instance, let's consider a fair coin toss. The expectation for either heads or tails from a single toss is equal, with implied odds of 0.5, equating to a fair price of 2.0. However, for profitability, a bookmaker typically offers shorter odds than 2.0. For example, odds of 1.87 for both outcomes would imply a probability of 0.535 for each. The margin, which calculates betting margins, derives from the sum of implied probabilities. In the above example, this totals 1.07, typically quoted as a 7% margin. How Likely is a run of profitable bets? A low-margin bookmaker, like 7x7Bets, is preferable as it's more likely to offer value betting opportunities, especially in sports markets where odds are influenced by various factors. Assessing the Likelihood of Profitable Streaks Betting with a low-margin book is the initial step towards profitability. The most evident sign of passing the value test is a profitable yield. But bettors should evaluate the likelihood of a series of bets resulting in profit or loss based on implied true probabilities. Understanding how the margin influences returns is crucial. For example, with a margin of 7%, five wins from ten bets would result in a net loss. Margin's Impact on Returns The importance of understanding the bookmaker's margin is illustrated by its effect on returns. If each event were priced at 1.95, with a 2.5% margin, the losses from picking five winners out of ten bets would decrease. To turn a profit from such poor value wagers, six or more successes are necessary. With nearly a 0.21 probability of exactly six wins in ten trials, a profit can be made. Significance of Margin Awareness Understanding margins is crucial. Although individual wagers may be poorly valued, there's a chance that six or more wins will occur in ten bets, yielding profit. Differentiating Luck from Skill through Records Maintaining records of your estimated true probability of success against the bookmaker's implied probability is essential. Comparing these values enables spreadsheet simulations to evaluate the role of luck and skill in your current yield. A knowledgeable bettor assesses outcomes probabilistically, considering both individual results and overall profit or loss from a series of bets. Now you know how does luck influence short term betting. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- Applying the Martingale strategy to even money bets - Risk and reward using the Martingale strategy - Modelling Martingale strategy outcomes - Understanding the effects of a house edge First things first, this article comes with a caution. Whenever someone speaks highly of Martingale in the realm of betting, the appropriate action is to correct them and walk away. Martingale is a notorious progressive betting system that escalates stakes after losses in hopes of recouping them. Such a loss recovery approach should never be taken seriously. I have frequently written about its flaws, including the mathematical evidence proving its inadequacies on Betting Resources. When dealing with any money management strategy where your perceived edge over the odds (be it positive or negative) remains consistent across all bets, it’s impossible to alter this advantage by merely adjusting stake sizes. All that changes is the risk-reward balance. In Martingale’s case, you’re trading a substantial risk for the possibility of a high reward: potentially catastrophic losses. Bearing this in mind, I’ve opted to explore Martingale in a controlled manner to illustrate a responsible usage without the usual catastrophic risks. Through this exploration, I aim to highlight how betting is always a trade-off between risk and reward. The greater the reward sought, the higher the risk one must embrace. How to get the most out of a holiday in Vegas I've always dreamt of visiting a Las Vegas casino. It’s well-known that casinos primarily offer games with negative expected returns. While techniques like card counting may provide an edge over the Blackjack table, such strategies will likely get you swiftly kicked out. For instance, all Roulette proposition bets are destined to lose over time, governed by mathematical rules where the house advantage is dictated by the zero. Setting aside tales of biased wheels observed over tens of thousands of spins, it’s safe to assume you won’t maintain a profitable edge. Acknowledging this, I’ve pondered the optimal approach to maximizing both enjoyment and duration of play during a holiday there. This contemplation will focus solely on even-money bets at the Roulette table, such as odd or even and red or black. How long will you last with flat staking? Flat staking, where you wager the same amount on every bet, represents the simplest betting strategy. Suppose we bet a dollar on each spin of the wheel. What might occur over 1,000 spins? The expected results adhere to a binomial distribution shown below. The blue curve represents outcomes under fair conditions, while the red curve accounts for the 2.7% house advantage on a single zero Roulette wheel: Even on a fair wheel, the likelihood of significantly increasing our bankroll is slim, at just a 5.7% chance of winning $50. Considering the house edge, the chances worsen (0.74%). However, the risk of losing $50 is comparably modest, with only a 23% chance, and just a 1% chance of losing $100. While flat staking is safer, it doesn’t offer substantial rewards. Surely, there's a more thrilling way to spend a vacation in Vegas? Using Martingale and inevitable losses The basic form of Martingale involves doubling the stake after each loss on an even-money bet until a win is secured, then resetting the stake. The risks associated with Martingale are clear to all but the overly confident bettors, as losing streaks are a natural outcome of frequent play. The more you bet, the more likely you are to experience extended losses. As an approximate guide, the expected longest losing streak in a series of n bets can be estimated using the logarithm of n divided by the odds minus one. For even-money bets, you might encounter three consecutive losses within eight bets, four within 16 bets, five within 32 bets, and so forth. In a series of 1,000 bets, you're likely to face a losing streak of about nine to ten bets. 7x7Bets has previously published a comprehensive article on this topic. Modelling Martingale outcomes Assuming unlimited funds and an exceedingly accommodating casino that allows any bet size, your projected profit from 1,000 spins would be $500 on a fair wheel, or $486 with a single zero. Realistically, neither scenario is feasible. More crucially, a long losing streak could either deplete your funds or shake your confidence sufficiently to make you quit. The logical approach involves setting clear objectives and boundaries for your betting while simulating various outcomes, similar to what we did for flat stakes. Consider this scenario: Starting with a $1 stake for each Martingale cycle, aim to win $500 over 1,000 spins. We will limit the risk of bankruptcy during the 1,000 plays to 50%. What is the maximum acceptable loss before deciding to stop, given the above conditions? This query can be addressed using a Monte Carlo simulation. The following table displays outcomes from 10,000 simulations. If the bankroll dips below a set threshold during the series, play is halted, and the strategy is deemed unsuccessful. Otherwise, play continues through 1,000 spins, marking the strategy as successful. Here, the roulette wheel is presumed fair, with no zero: A reformulated betting proposition It's apparent that the more loss we're willing to tolerate at any point in the series, the higher our chances of ultimately reaching our $500 goal. A loss limit of about $300 provides a 50% probability of success after 1,000 spins. Conversely, half the time, the average loss approaches $500. Essentially, we've redefined the betting scenario: risk $500 to gain $500, translating to odds of about 2.00 (or even odds in fractional terms). These odds closely mirror the ratio of average gains to losses, effectively representing your true odds. For a fair wheel without a zero, these odds should match. The element of randomness in sports betting Setting the threshold at minus $1,000 allows for longer losing streaks, reducing the likelihood of failure and thus offering shorter odds (1.29). However, if you're reluctant to risk a total loss of $1,725, you could reduce the initial stake size in the progression. A stake of $0.29 would then equate to a bet of risking $500 to win approximately $145. Compared to the more conservative flat staking method, this approach significantly increases the risk of a larger loss but also raises the potential for a larger win. You may not lose $500 in 1,000 roulette spins betting $1 per spin, but you’re also unlikely to win $500. The chances of either scenario are exceedingly low. Understanding the effects of a house edge Introducing a 2.7% house edge through the zero alters the dynamics. The chart below compares the bankruptcy rates between wheels with and without a single zero. With the introduction of a zero at a threshold of minus $300, you can expect to fail approximately 58% of the time. To maintain a 50% chance of success, you would need to increase your maximum acceptable loss threshold to about minus $440. Under such conditions, you're facing an average loss of about $670 to win $486. Remember, since your bet win expectation is now 48.6%, your actual profit for a successful series would be closer to $486, not $500. This adjustment suggests odds of 1.73, significantly lower than the initial 2.00 calculated by the failure probability. This discrepancy illustrates a loss in value, far exceeding the house margin. Your implied value ratio is 1.73 divided by 2.00, or 0.865, a steep price for employing Martingale. What distinguishes winning from losing bettors? The expected value for an even-money roulette bet over 1,000 bets with flat stakes gives you around a 20% chance of turning a profit, versus an 80% chance of a loss. This is evident from the areas under the orange curve in the binomial chart, to the left and right of the zero-profit line. Your implied odds of success are then 5.00, and your value ratio is 2.00 divided by 5.00, or 0.40, relative to a fair wheel without a zero. In reality, your loss of value using this managed Martingale strategy varies depending on your minimum bankroll loss threshold and your proposition odds. The shorter the odds (and the lower the failure rate), the less value you lose. For a threshold of minus $100, the implied odds by the failure rate are about 5.00 with a single zero wheel, compared to about 3.68 without, implying a value of 0.74. Conversely, with a threshold of minus $1,000, the odds are approximately 1.4 and 1.29 respectively, suggesting a value of 0.92. If the threshold were $10,000, the value would be nearly 0.99. This relationship is curiously reminiscent of the favorite–longshot bias. The distribution of risks and rewards We can depict how a managed Martingale strategy like this alters the betting scenario by illustrating the distribution of potential outcomes. The chart below displays the distribution from the 10,000 Monte Carlo simulations for the minus $300 bankroll threshold scenario on a fair roulette wheel. It shows a clear division between zones of success or failure, contrasting sharply with the original distribution from flat staking (shown in the dotted orange curve). What happens when you change the odds? While this discussion revolves around simple even-money bets, the principles of Martingale can be applied to any odds and any betting market, including sports. Adjustments to the size of the Martingale progression are calculated by the formula: odds divided by odds minus one. Thus, for odds of 3.00, stakes after losses increase by a factor of 1.5; for odds of 1.50, by a factor of three. Predictably, the longer the odds you bet on, the larger the stake you must risk to reformulate your bet as an even-money proposition. For example, betting at fair odds of 5.00 means you would need to risk about $800 to potentially win $800. Conversely, betting at odds of 1.50 results in an effective proposition of risking $333 to win $333. However, you can always adjust the initial progression stake size to account for this, as discussed earlier. Now you know what can the Martingale strategy teach us about betting and how to apply it into money betting. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. 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- Knowing when the odds are against you - The challenge of selecting one favourable outcome - The Monty Hall solution This is critical for punters because, put simply, if a bettor can't discern implied probability and if a bookmaker’s odds offer 'value,' they will not profit in the long haul. The Monty Hall problem Imagine a brand new car is parked behind one of three doors. The remaining two conceal goats. You must pinpoint the correct door to win the car, but initially, there’s nothing to guide your choice. After you pick a door, another door swings open to unveil a goat. Now, you're faced with a decision – stick with your first pick or switch to the other closed door? The probability that the car is behind the unopened door is 66.66%. Named after the “Let’s Make a Deal” host, a hit American show during the 60s & 70s which introduced this puzzle, the Monty Hall problem is a straightforward mathematical challenge that effectively showcases human difficulty with seemingly simple decisions. Through this nifty little riddle, the program illustrated how average folks display counter-intuitive actions when tackling probability puzzles – a scenario all too familiar to casual gamblers. When this puzzle was featured in Parade magazine, it baffled 10,000 readers, including numerous math professors who protested the solution. The Monty Hall solution The strategy for the Monty Hall problem is straightforward: always switch doors. Once the initial door is opened, the car is certainly behind one of the remaining doors, though it’s unclear which. Many contestants erroneously perceive no benefit in switching doors, assuming each has an equal one-third chance. This notion is mistaken – actually, the likelihood of snagging the car doubles by switching. While it’s true each door initially had a 33.3% chance of concealing the car, once a goat is revealed, the odds that the car is behind the other door jump to 66.6%. Calculating these probabilities is simpler when you consider choosing between your initial door (33.3% probability) and the combined chance of the other two doors (33.3% + 33.3%). This is because once a door is selected, the other two are conceptually linked – there's a 66.6% probability the car is behind them. When one door is subsequently removed, a 66.6% chance remains that the car is behind the other one. Refer to the example below: Knowing when the odds are stacked against you This predicament cleverly demonstrates how effortless it is to misjudge non-random information as random. The UK game show “Deal or No Deal,” which involves 26 sealed boxes with varying sums of money, pays tribute to “Let’s Make a Deal” by exploiting the general public’s poor understanding of probability, as participants often rely on incorrect 'hunches' about their chances (refer to our article on heuristics in betting for more insights). Such errors are common blunders among bettors who often act against their own best interests, swayed by slick advertising tricks or persuaded to view betting as a lifestyle rather than a matter of math. Mastering betting involves recognizing whether the odds on an event reflect the actual statistical probability of its occurrence. It doesn't matter if it's a game show, the lottery, or online sports betting; grasping and identifying value is crucial for making a profit. Now you know what is the Monty Hall problem and how to use it when betting. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- Expected value and expected utility explained - Utility under uncertainty - How to calculate the optimal stake amount? The role of utility in profitable betting Expected value, a concept that was first tackled by French scholars Pascal and Fermat in the 17th century as they attempted to decode a points game, illustrates the average winnings one might expect from a wager. It doesn't, however, offer much guidance on how much of one's capital should be put at risk per bet. This is where the notion of expected utility enters the picture. Expected value and expected utility explained Expected value (EV) in betting is derived by taking your chances of winning (p) and multiplying it by the potential payout per bet, and then deducting the probability of a loss multiplied by the potential loss per bet. Since the probability of losing is the flip side of winning, expressed as 1 (or 100%) minus the probability of winning, this simplifies the calculation: 'o' signifies the European decimal odds offered by the bookie. For any gambler, expected value is crucial because it predicts whether they're likely to gain or lose money over time. After determining the expected value, a gambler needs to decide how much of their funds to wager. The 18th-century mathematician Daniel Bernoulli argued that only the reckless decide on their stake based solely on the objective expected value, without considering the subjective impact of their bet, namely the appeal of the potential gain or loss. This subjective appeal is referred to as utility. Utility under uncertainty Imagine being presented with two chests. The first holds €10,000 in cash. The second could contain either €20,000 or nothing, and it's a 50/50 chance. Which one would you pick? Kelly's formula is designed to maximize a winning gambler's bankroll over time. This forms a typical utility dilemma. Mathematically, both chests have an expected value of €10,000. If you could play endlessly, your choice wouldn't matter. But you can only play once, making the law of large numbers irrelevant. Choosing the first chest guarantees you €10,000. Opting for the second chest means your outcome is down to luck: win and pocket €20,000; lose, and you get nothing. Given these stakes, most folks opt for the sure €10,000. From a utility standpoint, the surety of €10,000 far outweighs the risk of walking away empty-handed. Those preferring guaranteed outcomes over risky ones with the same mathematical expectation are exhibiting risk aversion. How to calculate the optimal stake amount? Daniel Bernoulli posited that when faced with uncertainty, the typical rational response is risk aversion. He stated: “the utility derived from any small increase in wealth will be inversely proportionate to the quantity of goods previously possessed.” This means the more wealth you have, the less you value a little extra. This utility function, described as logarithmic, is also known as the diminishing marginal utility of wealth. Although the Kelly Criterion can lead to notable fluctuations in returns, it allows winning bettors to maximize their bankroll in the long haul. This practical application of Bernoulli’s theory provides a framework for gamblers and investors alike, known as the Kelly Criterion. John Kelly, while at AT&T's Bell Labs in 1956 dealing with long distance telephone noise issues, developed this, which gamblers and investors quickly adopted to optimize financial management and profit growth. While Kelly’s rationale differed from Bernoulli's, his criterion mathematically aligns with the logarithmic utility function. Essentially, it advises a bettor to bet a portion of their total wealth on a bet proportional to the expected value (EV) and inversely proportional to the success probability. Remembering that EV = po – 1 (where p is the ‘true’ probability of success and o represents the decimal odds of the bet), we can determine the Kelly stake percentage (K) as: Utility maximization through the Kelly Criterion Fundamentally, the Kelly Criterion aims to maximize expected logarithmic utility. One result of employing the Kelly Criterion is substantial fluctuation in returns, a trait that may not suit every bettor’s preference for utility. Moreover, its application necessitates accurate calculations of ‘true’ probabilities of outcomes. Yet, Kelly’s method does, in theory, allow successful bettors to significantly grow their bankroll over time. To effectively use this strategy, a bettor needs a bookmaker like 7x7Bets, known for its unparalleled standing in the betting world and its open stance towards strategic money management without penalizing winning. Now you know how much should you risk per bet. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- What is the variance? Where is the edge? - Net results vs. number of trades If only it was that simple. How often have we heard someone claim a losing streak is just “bad variance”? On the flip side, rarely do winners attribute their success to “good variance,” do they? Even if you find a viable edge on a betting market, profits aren’t necessarily guaranteed in the short term. Numerous punters reckon they can manage the rough patches and get variance, but do we truly grasp its full impact? I tested this with my own wagering records on a specific approach at 7x7Bets. A $5,000 bankroll 20% Kelly staking where possible $496,000 turnover $14,600 in closing Expected Value (the projected profit based on my advantage) 2.94% Closing EV return on investment (ROI) $22,500 actual profit 4.54% actual ROI Average odds placed - 2.38 Average true closing odds - 2.34 The first thing you might notice is that my actual profit and ROI is bigger than I would expect. Indeed, when you consider the long-term trend of my earnings against the closing line, it’s stayed above it for most of this duration. So, have I just been fortunate? Absolutely, as the chart below will show: If luck has been on my side in this run, then the question for you is how likely is it that my results could be replicated if someone was using the same strategy as me? Before you respond, try answering these: Using the same parameters and over the same number of trades as I mentioned above, what’s the probability… That someone else would make $22,500 in profit? That someone else would perform worse and only make $15,000 in profit? That someone else would perform better and make $35,000 in profit? Of losing the entire $5000 bankroll? This was tested over 10,000 simulations and the results are below: Did the results astonish you? They surely did for me. There was under a 13% chance of achieving the results I did. I realized I was fortunate before this simulation but I didn’t grasp HOW fortunate. Thankfully, the simulation showed that it was virtually impossible for me to lose my entire bankroll using my strategy and implied edge. Yet, there’s still a rare chance of seeing an overall loss. With around 10,000 or so trades, that’s what one should expect, yet many bettors lack the patience, bankroll management, or mental strength to watch this scenario unfold. The graphic below isn’t a flying comet made of coloured yarn, but a visualization of the simulations that were run. You might notice some of the simulations do show a net loss over the first few thousand trades but all gradually turn more profitable as more bets are logged. So we’ve concluded that I’ve got rather lucky so far, but what might I expect for the next 10,000 bets I place? Actually, there is a 20.5% chance that I make no more profit and my bankroll stays static, but a 54% chance that I earn at least another $7,500. The odds of me reaching $50,000 profit during this period are slim (2.5%). The final graphs I will show you are the simulations after 20,000 and 30,000 trades. What do you notice? What strikes me is the fewer outliers with extreme values. You can tell because the lines are more tightly packed together with a larger volume of bets. Final thoughts This is just one scenario and the data isn’t foolproof, but it illustrates how variance can be more unpredictable than we reckon, even with a strategy that sports fairly low average odds. It gives even more reason to hang tight during a bad losing streak and not to get too cocky during a hot spell. If you’d like to give it a go yourself, the sportsbettingcalcs site is ready for your simulations. You might uncover some intriguing insights! Now you know the truth about variance. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- Parlay betting strategy - The limitations of parlays Why Parlays are generally considered to be poor bets Typically, wagering on Parlays is viewed as a less favorable betting strategy. Each event added to the bet amplifies the bookmaker's margin significantly. This often results in bets that greatly favor the bookmaker. Parlay betting strategy: Multiplying advantages A commonly overlooked aspect of Parlay bets is their potential to enhance a bettor’s edge, just as they increase the bookmaker’s margin. For bettors confident in their edge against the bookmaker, Parlays can serve as potent tools to amplify their advantage. Consider a bettor who determines that three events, each at decimal odds of 2.00 (indicating a 50% implied probability), actually possess a 55.55% chance of occurring (equivalent to odds of 1.8): Parlay betting strategy In such cases, the bettor gains from the Parlay similarly to how the bookmaker typically benefits. Their edge is significantly broadened. Dependent events Without an existing edge, another scenario where a Parlay could be beneficial is if the bettor can link bets that seem independent but are somehow interconnected. For instance, imagine a wager on a cricket player and a separate bet on a team he doesn't play for, to score beyond a certain total during the season. Should the team score highly, it might indicate a high-scoring season across the league. Such outcomes could stem from rule modifications, a shift in league play styles, or various minor elements that collectively impact both results favorably. These conditions would likely increase the player's scoring chances, even if he’s not part of the specific team. Thus, the bets are interrelated to some extent. While most bookies might prevent such combined bets, it’s not impossible for a punter to occasionally find two apparently unrelated bets that actually correlate. Parlays and volatility Bettors should note that Parlays heighten the volatility of outcomes in the short term. Taking the earlier example, a bettor wagering on individual results might win over 50% of the time based on their predicted probability. However, when outcomes are combined into a Parlay, the win rate might drop to 17%, although the reward would quadruple. Such an increase in potential returns also boosts the volatility of earnings. It’s conceivable that events in a Parlay might not occur together frequently, making this variability challenging to manage without sufficient long-term betting to average out outcomes. The limitations of Parlays Besides the typical constraints experienced by successful bettors at bookmakers, Parlays pose additional challenges, even at more astute betting platforms. The scenario depicted in this article, of a bettor enhancing their edge over the bookie, is something bookmakers tend to avoid. Hence, even sharper bookies might lower the odds when bets are compiled into a Parlay. Moreover, the inherent volatility of Parlays complicates the bookmakers' risk management strategies. In summary, like most betting tactics, the efficacy of Parlays depends largely on the bettor's skill. They can be as advantageous for a skilled bettor as they are detrimental to an inexperienced one. Now you know what is the parlay strategy and how can that be used in betting. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- The story of Goalimpact - How Goalimpact uses metrics and statistics - A real life case study - How can Goalimpact aid bettors? Originally, the algorithm was developed to assess the strength of soccer teams, much like the Elo rating system in chess. Remarkably, it rated Greece as robust contenders—a prediction overlooked by many—which was validated when they clinched the championship. Motivated by this triumph, Jörg consistently applied the model to his soccer betting endeavors. Nevertheless, the model's effectiveness waned post the summer transfer window due to team roster modifications that weren't accounted for, leading to a pivotal shift from team to player ratings in the algorithm. This new method proved superior, maintaining accurate strength assessments even with player transfers. Jörg’s betting success on subsequent tournaments speaks volumes about the efficacy of this approach. Thus began the journey of Goalimpact. How does Goalimpact work? Goalimpact quantifies a player's effect on the goal differential per minute on the field, focusing solely on actual performance rather than extensive player statistics. This model opts for a holistic approach, acknowledging the soccer field as a complex network where each action is interconnected, making it challenging to isolate which specific actions lead to victory. Much like the +/- statistic in basketball, the algorithm recognizes the ultimate objective in soccer—to win by outscoring the opponent, as famously summed up by Johan Cruyff: “To win you have to score one more goal than your opponent.” Essentially, soccer boils down to optimizing goal difference. Hence, a player’s merit is objectively rated based on their ability to improve their team's goal difference while playing—regardless of the circumstances. Goalimpact offers an objective measure of what makes a player "good," by factoring in the strength of opposing players, which is not considered in basketball's +/- system. This gives Goalimpact a relative value for player comparisons globally. How does the algorithm learn? Goalimpact's algorithm requires only basic match data such as starting lineups, goal timings, substitutions, and players' birthdates to compute player quality from a minimum of 1,000 minutes of play. The model also integrates fatigue, disciplinary actions, and home advantage into its calculations. With over a million players tracked worldwide, it leverages birthdate data to adjust for age-related bias and to forecast players' peak potential. An example Consider a hypothetical match where Manchester City scores against Manchester United in the 30th minute and leads until halftime. Post-substitution, United ties the game in the 60th minute, and the match ends 1-1. In such a scenario, where both teams are presumed equally skilled, Goalimpact would adjust only the ratings of players involved in the scoring, namely Casemiro and Donny van de Beek, reflecting their direct impact on the match outcome. This example underlines that while one game might offer limited data, continuous updates refine the model, focusing solely on player quality over time. Case study: the discovery of Alphonso Davies A notable success story within Goalimpact is that of Alphonso Davies, whose potential was identified early on despite his modest market value of under €500,000. His trajectory to becoming a world-class player was accurately predicted by Goalimpact. The graph of Alphonso Davies' Goalimpact ratings illustrates his average performance over time, with projections showing a steep ascent towards elite status, indicative of top-tier European league potential. For context, the world’s best players typically score above 170 in Goalimpact ratings. How Goalimpact can aid bettors Goalimpact’s methodology offers a realistic and unbiased prediction model. It estimates a team's overall strength from the sum of individual players’ ratings, facilitating the derivation of expected goal differences between teams. This model can significantly enhance betting strategies by providing a more precise comparison of expected outcomes versus betting odds offered by platforms like 7x7Bets. This structured, data-driven approach ensures bettors are well-informed, leveraging objective player ratings to predict match results more accurately. Now you know what is Goalimpact and how to bet with objective Player Ratings. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- What is price elasticity of demand? - Betting and airlines What is Price Elasticity of Demand? Price elasticity of demand quantifies how the consumption of a product fluctuates with price changes. Essentially, the more elastic the demand, the greater the variation in product consumption in response to price shifts. For instance, in the case of a product like bread, which has elastic demand, a price hike leads to a significant reduction in purchase quantities. Conversely, for products with inelastic demand, such as petrol, a similar price increase results in a relatively minor decrease in consumption. This concept might seem straightforward, but how does it relate to the betting industry? Price Discrimination: Favourites, Longshots, and Airlines The favourite-longshot bias is a well-known phenomenon in the gambling sector. It is observed that a disproportionate amount of a bookmaker’s margin favors the longshot. This bias is partly attributed to casual gamblers who tend to back the longshot in any given race, irrespective of the price. In contrast, more price-conscious punters search for value bets, typically on the favourite. This behavior can be explained through the lens of demand elasticity. A similar customer segmentation strategy is employed in the airline industry, where companies aim to maximize revenue by tailoring ticket prices based on customer profiles. Casual travellers, who exhibit high price sensitivity, might change their travel plans based on ticket prices. Hence, airline tickets for this group represent a highly elastic demand. On the other hand, business travellers, who prioritize convenience and time savings over cost, display inelastic demand characteristics. Price changes are less likely to affect their booking patterns. Airlines capitalize on these dynamics by offering lower prices for early bookings, catering to elastic demand customers. As the travel date nears and seats fill up, prices are ramped up, targeting business travellers with inelastic demand. This strategy effectively segments the market into two distinct customer types. Favourite-Longshot Bias and Betting Companies Similar to airlines, betting companies may employ a dual-market approach. Market A consists of value-seeking bettors analogous to airline's recreational travellers. These bettors are highly price-sensitive and will scout for the best available odds. If the odds are not attractive, they might opt out of betting. Market B includes less price-sensitive recreational gamblers who place bets based on convenience, such as user-friendly betting platforms, regardless of the competitiveness of the odds. In this scenario, bookmakers serve both markets, much like airlines. The less price-sensitive Market B may effectively subsidize the sharper, value-seeking Market A. This model explains why favourite-longshot bias might arise if bookmakers adjust their pricing strategies similarly to how airlines manage ticket sales. Unlimited Supply and Information Flows: Why Bookmakers Limit Customers Unlike airlines, which have a finite number of seats, bookmakers can accept an unlimited number of bets as long as there is market demand. However, most price-sensitive bettors only place bets when they anticipate a net gain, which could be detrimental to a bookmaker’s profit margins. Although airlines might suffer losses on some price-sensitive passengers to fill seats, bookmakers face a different challenge. They might limit or restrict their most astute bettors to prevent losses. 7x7Bets, however, takes a different approach by not restricting these sharp bettors. For 7x7Bets, the insights gained from the wagers of these informed punters are valuable for setting more accurate betting lines. This allows them to optimize their earnings from casual bettors while still attracting significant action from the savvy Market B. Volatility: Why Would Sharp Bettors Prefer Short Odds? The question remains: why do sharp bettors tend towards shorter odds rather than longshots? One reason could be that the high volatility associated with longshots makes it difficult to measure betting success accurately. More frequent events provide a larger sample size, facilitating more reliable long-term profit calculations. Furthermore, bookmakers are cautious with longshot pricing due to the high potential payouts involved. Hence, sharp bettors might gravitate towards favourites, steered by the bookmakers’ conservative odds setting. Additionally, the thrill of potentially turning a small stake into a large win may appeal more to Market A bettors, who predominantly gamble for entertainment. This rephrased article integrates local Indian English nuances and maintains the structure and data integrity as specified. Now you know what is price elasticity of demand and favourite-longshot bias. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- The Halo Effect - Lessons to learn - Are betting judgements biased? How bettors make lazy judgements The Halo Effect Most folks tend to have a better opinion of Alan than of Ben, despite the fact that the qualities listed are identical but in a reversed order. This peculiar judgment arises not from the characteristics themselves, but rather from the sequence in which they are introduced. Instead of recognizing that the sequence of presentation is the only variation, our mind’s effortless part (often called System 1) searches for consistency in evaluations to quickly form a seamless story. The first positive trait—Alan is smart—predisposes us to view subsequent traits in a way that supports this initial impression, and the reverse happens with Ben, perceived as jealous. This phenomenon is recognized as the Halo Effect. It's straightforward to notice how betting decisions are influenced by the sequence in which data is presented. What’s the relevance to betting, you ask? Switch the scenario from imaginary individuals to two cricket teams or tennis players, and replace personality traits with match results or performances, and it becomes clear how betting judgments are swayed by the order of data acquisition and the weight given to specific performances. This bias isn’t standalone; folks are also prone to the Availability Heuristic, which causes us to attribute undue importance to the most easily recalled events/ideas. Availability ties closely to how strong our emotional response to an event is, which intensifies when the events leave a lasting impression, like high-run chases or epic five-setters. Armed with insights into the Halo Effect and Availability Heuristic, let's explore a few instances within betting where these biases manifest: The Indian cricket team The esteemed position of India’s national cricket team is a cut above, influenced heavily by the disproportionate regard from the betting public, not entirely based on objective evaluation. It's a fact that Team India has secured numerous victories in critical tournaments, yet their success has been intermittent, clustered in specific golden eras. These periods of triumph, along with cricketing legends like Sachin Tendulkar and Kapil Dev, have established a 'Halo' that distorts perceptions of all Indian teams, confirmed by availability bias through easily remembered spectacular innings, particularly from famous tournaments. While younger fans might not recall events from decades ago, the media reinforces these perceptions (confirmation bias) by continuously projecting that all Indian cricketers are exceptionally talented. This consistency in evaluation fosters a cohesive narrative: “India has produced many world-class cricketers—hence, all Indian players are top-notch.” Interestingly, significant defeats, like those in crucial World Cup matches, could potentially diminish this long-standing Halo, albeit only slightly. The Halo Effect also elucidates why an inordinate amount of recognition is bestowed on famous former cricketers who transition into coaching roles. There's no statistical proof that a stellar player will make an excellent coach. Sunil Gavaskar was a cricketing maestro, yet expectations from him as a coach were set unreasonably high due to his playing achievements. The Halo from his playing days leads many clubs, fans, and bettors to anticipate more than is realistically feasible when these legends manage teams. This topic gained attention with the book Moneyball and its subsequent movie adaptation. Reverse Halo If the first thing you notice at your vacation resort is a tattered sign, this sets a negative tone, skewing all following impressions about your stay. From a betting viewpoint, a poor performance in a match disproportionately skews future assessments. Our intuitive mind is invaluable and incredibly potent, often safeguarding us by detecting threats. However, after Rory McIlroy surrendered a four-shot lead in the final round of the 2011 US Masters, he was labeled a failure by many. Prior to this event, he was a rising star, but one disastrous round of 80—vividly remembered due to the Availability Heuristic—shifted public opinion drastically. Bettors who maintained a more holistic view reaped benefits when he won the US Open by eight shots shortly thereafter, and the US PGA Championship in 2012. Had these victories occurred prior to his meltdown at the Masters, judgments of his subsequent performances would have been more lenient. This is especially relevant considering McIlroy’s historical walk-off during the second round of the Honda Classic with a score of 7-over par and visibly troubled. Lessons to Learn Our intuitive mind is precious and immensely powerful, especially in perceiving imminent dangers. Nonetheless, it struggles with statistical evaluations. The solution is to engage our more deliberate mind (System 2) actively. Before deciding on a bet, it's crucial to consciously seek out three counterarguments to your initial assessment and rely on as much objective data from a comprehensive sample size as possible, while disregarding simplistic narratives often propagated by mainstream media. Bettors who delve into intriguing psychological concepts like the Halo Effect might be keen to share their newfound knowledge, yet this doesn't mean they can easily alter their tendencies to place 'Halos' on sports teams or players. The real test lies not in acquiring new facts but in evolving your understanding of situations you encounter. Now you know What is the Halo Effect and how bettors make lazy judgements. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- What is the Hot Hand effect? - How can the Hot Hand effect impact sports betting? - Exceptions to the Hot Hand effect What is the Hot Hand effect? The phrase "Hot Hand" originated in basketball, suggesting that a player who makes consecutive shots is more likely to succeed in subsequent attempts. This belief is widespread among coaches, spectators, and players, reinforcing the idea of this effect. Yet, research indicates that the likelihood of continued success due to the Hot Hand effect is no greater than random chance. Studies in other sports, like cricket, show minimal significant statistical effects. Whether examining batting streaks or teams' winning sequences, typically, these runs end, and performance returns to the norm. If the effect is minimal or non-existent, why do we give it so much weight? Evolutionarily speaking, our early ancestors needed to recognize patterns in nature to find essential resources like food and water, which translates into spotting and exploiting patterns in betting today. Furthermore, witnessing such phenomena personally might make us believe it happens universally, even among top athletes. However, data from junior golfers (Cotton and Price, 2006) suggests that higher skill levels make athletes less influenced by confidence boosts. Our cognitive bias towards "presentism" also plays a role—believing that current trends will continue longer than they actually do. Exceptions to the Hot Hand effect In certain scenarios, the Hot Hand effect appears more pronounced: Analysis of ten pin bowlers indicated a 12% higher chance of hitting a fifth strike following four consecutive strikes (Dorsey-Palmateer and Smith, 2004). In the NHL's hardest shot competition, statisticians observed almost perfect consistency in shot speeds among players (Reifman, 2007). In tennis, players were more likely to win the next point if they had won the previous one (Klaasen and Magnus, 2001). These instances involve repetitive actions with brief intervals, where the Hot Hand effect is more observable. Competitions like the 3-point shootout in the NBA All-Star game also merit consideration, although as the number of variables increases, detecting the Hot Hand effect becomes challenging. How can the Hot Hand effect impact your betting? The Hot Hand effect could mean that media hype influences casual punters in the market by focusing on teams or players experiencing winning streaks—or the reverse with a Cold Hand. This can lead to skewed odds, presenting opportunities for a contrarian betting strategy. Recognizing when a team or player is performing above or below their usual level is crucial. Research shows that players might change their tactics when they are aware of their winning streak, and competitors might adjust their strategies accordingly, complicating the ability to maintain a streak. Understanding overperformance or underperformance with an objective perspective, especially considering the opponents and game conditions, can provide an edge over other bettors. Remember, even the best runs eventually end, as the local saying goes, "Every tide has its ebb." Now you know what is the hot hand effect. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!

- How do you know how much a bet is worth? - Understand that variance has a real cost - Is the risk of variance costing you money? Introduction to the "Swap Equivalent" for Astute Bettors Recently, I've introduced a nifty concept called the “Swap Equivalent” that's quite handy for folks who take their betting seriously. It's designed to quantify how you should equate the Expected Value (EV) of your risky bets with what's known as Certainty Equivalents (CE). Simply put, multiply your EV by the Swap Equivalent to get the CE—this is essentially the cash amount that would make you feel just as content as holding your open wager. Moreover, this formula helps you gauge the Cost of Variance. For many, the notion of variance is a bit vague and puzzling. However, for savvy sports bettors, it symbolizes the regular fluctuations in profits as you pursue that ultimate treasure at the end of your betting journey. Variance is more than just a bothersome hurdle; it carries a tangible cost. Why? Because if it didn’t, the Certainty Equivalent for any bet would match its Expected Value right off the bat. This concept has been explored in several of my previous write-ups, highlighting their distinction. Let’s define the actual Cost of Variance (CoV) as the gap between your EV and your CE. Although it might seem minuscule per bet, it accumulates significantly over time: CE = s * EV CoV = EV - CE This relationship shows that the real Cost of Variance is essentially your EV minus a portion determined by the Swap Equivalent: CoV = EV - s * EV CoV = EV * (1-s) Take, for instance, a sportsbook offering today’s cricket match with odds like Team A +130/Team B -150. Using the odds from 7x7Bets, you reckon Team B has a 60% winning chance. Theoretically, betting on Team B at these odds should mean your EV is zero, suggesting that over time, the outcome would be as good as having that bet amount in your pocket. Yet, these figures don’t reveal everything. They only cover one aspect of your betting strategy—the value aspect. There’s another critical dimension to consider: risk. By placing any bet on Team B, irrespective of the EV, you expose your money to risk and face variance to reclaim it. So, what’s the cost of this variance? Let’s find out. Imagine you have a bankroll of ₹1,000 and decide to bet ₹50 on Team B, considering there’s no EV loss. You would win 60% of the time (returning ₹83.33) and lose 40% of the time (returning nothing). The expected value of your bankroll post-match would be: 0.6 ₹83.33 + 0.4 ₹0 + ₹950 = ₹50 + ₹950 = ₹1,000 Now, to calculate the Swap Equivalent post-bet: s = ((1 + w) ^ p - 1) / (p * w) s = ((1 + 0.088) ^ 0.6 - 1) / (0.6 * 0.088) s = (1.052 - 1) / 0.053 s = 0.985 or 98.5% Here, w represents the payout as a percentage of your bankroll, and p is the probability of your bet winning. In this case, w is ₹83.33/₹950 = 0.088. While the EV of your ticket stands at ₹50, the CE is only ₹49.25 due to the Swap Equivalent. This shows that the variance cost incurred is: CoV = EV * (1 - s) CoV = ₹50 * (1 - 0.985) CoV = ₹50 * 0.015 CoV = ₹0.75 This example clearly illustrates the financial impact of variance on your betting outcomes, essential for any serious bettor in India to understand. A Slippery Slope for Your Bankroll It might look like a small sum, but consistently making this wager could slightly erode your theoretical growth each time, potentially leading to bankruptcy. In fact, simulating this bet 10,000 times results in bankruptcy 81.6% of the time (illustrated by the plot of five typical simulation runs provided below). To grasp this more intuitively, consider the state of your bankroll after wins versus losses. If you win, your bankroll climbs to ₹1,033, making your next ₹50 bet just 4.8% of your total funds. Conversely, a loss drops your funds to ₹950, where the same ₹50 bet then constitutes 5.3% of your bankroll. This dynamic results in you wagering a smaller fraction of your bankroll when you win and a larger fraction when you lose. This disparity can quickly snowball, taking large bites out of your remaining funds during a losing streak, which is hardly a strategy for wealth accumulation or even breaking even. You might think, as long as you don't bet your entire bankroll at once, you can't possibly go broke, right? This theory sounds solid but is it foolproof? Consider proportional betting — betting 5% of your current bankroll each time. This approach means you bet more following wins and less after losses, presumably evening things out. Moreover, since you never wager 100% of your funds, going broke seems unlikely. But what does "broke" really mean? Technically, you never lose all your money with proportional staking, but what if your bankroll dwindles to just ₹10? That's practically broke, isn't it? Let's examine another simulation under these conditions, but this time, you're considered broke if you fall below ₹10. The results are even more dire. The increased stakes after winning amplify the impact of any subsequent losses, leading to steeper downswings. Even starting with a stroke of luck (probably the only way to avoid going broke after 10,000 bets), you typically end up broke more than 88% of the time, as shown in the chart below (Y-axis displayed on a logarithmic scale for clarity). Not surprisingly, given a substantial bet percentage with no betting advantage, your Expected Growth (EG) for a single bet is -0.083%. While it might not seem significant, after 5,600 bets, you would typically see your ₹1,000 bankroll reduced to under ₹10. Calculating your expected ROI with the same odds but a 3.3% edge gives you a full Kelly fraction of 5% for betting on Team B, with an EG of +0.083%—exactly offsetting the negative EG in my scenario, indicating equal disappointment for a neutral EV bet and equal satisfaction for a profitable one. Imagine if, rather than being a regular bettor, you were Jeff Bezos with a staggering $100 billion at your disposal. In such a scenario, the Swap Equivalent for your betting ticket would virtually hit 100%, implying zero economic cost from your wagers. The calculations to demonstrate this are straightforward but interesting due to the sheer scale of the numbers involved. The Swap Equivalent (s) and Cost of Variance (CoV) equations would be adjusted as follows due to the massive bankroll size: s = ((1 + w) ^ p - 1) / (p * w) s = ((1 + 0.00000000083) ^ 0.6 - 1) / (0.6 * 0.00000000083) s ≈ (1.0000000005 - 1) / 0.0000000005 s = 1 or 100% Here, the wager amount (w) is minuscule relative to the bankroll, leading to an s value of virtually 1, or 100%. This results in the Cost of Variance calculation: CoV = EV * (1 - s) CoV = 50 * (1 - 1) CoV = $0 With such an immense bankroll, the economic implications of typical betting variances become negligible. This illustrates how variance, a critical factor for average bettors, fades into insignificance with sufficient financial backing, highlighting the unique position of high-net-worth individuals in high-stake gambling scenarios. Conclusion Realizing the tangible cost of variance helps understand why focusing solely on +EV bets while ignoring -EV or neutral ones is short-sighted. Variance acts like a hidden fee or commission, similar to stock trading, costing you money. Reducing this risk might mean making smaller initial bets, but even optimal staking can't always prevent your bet's EV from exceeding its certainty equivalent significantly. In situations where the EV of a bet drastically outstrips the certainty equivalent, hedging your risks (either by betting the opposing side at a low-margin bookmaker like 7x7Bets or managing your exposure on an exchange) serves as a financial safeguard. If the cost of this insurance is lower than the cost of your variance, then it becomes the more economically sensible choice. Now you know how to place a bet with the cost of variance. Sign Up Now or click HERE to play at 7x7Bets, the most reliable and trustworthy online casino in India. Don't forget to claim your withdrawable real money welcome deposit bonus, weekly cashback bonus and referral bonus!