Many sports bettors use data-driven analytics to replace the guesswork in their decision-making to gain a strategic advantage over The Books. Instead of relying on emotion, hunches, or team loyalty, bettors use advanced statistics and predictive models to improve their chances of long-term profitability. Two specific metrics that I often get asked about are Expected Value (or EV) and Fair Value (or FV). What do these metrics mean and why do we care? Allow me to elaborate.

In sports betting, Fair Value (FV) is the true, no vig, probability of an betting outcome, while Expected Value (EV) measures the long-term profitability of a specific bet by comparing the FV to the sportsbook’s odds. Sharp bettors use these concepts to identify and exploit mispriced odds over time, rather than just picking winners.

Let’s break this down further, shall we.

Fair Value (FV)

Fair Value represents the true, objective probability of a betting outcome, with the sportsbook's commission (known as the "vig" or "juice") removed.

In layman’s terms, the odds that a bookmaker would offer if they were not charging a fee to take the bet. For example, the FV of a coin flip is +100 for both heads and tails, representing a true 50% probability for each outcome. You can determine the fair value of a bet by removing the vig from a sportsbook's odds, often using a "no-vig" calculator or by averaging odds from multiple "sharp" (efficient) sportsbooks.

Example: A sportsbook offers odds of -110 on a team, which implies a 52.38% chance of winning. After removing the vig, the fair value odds might be +100, indicating a true 50% probability.

Expected Value (EV)

Expected Value is a statistical calculation that determines the average amount of money a bettor can expect to win or lose for each bet placed repeatedly over a long period.

In other words, EV quantifies your potential edge on a specific bet. A positive EV (+EV) means the bet has a long-term advantage for the bettor, while a negative EV (-EV) means it is profitable for the sportsbook.

In order to calculate EV, we use it’s formula:

EV=(Probability of Winning×Profit per Win)−(Probability of Losing×Amount Wagered)

As an example, let’s use the common ‘coin flip’. The fair value odds (FV) would be +100 for both heads and tails (50% probability). Now let’s say that the consensus sportsbook odds are juiced at -110 for either result, but you find one book that is offering +120 odds for tails. A much better price than the consensus. Sweet!

Now to calculate the EV, we run the numbers through the equation, like so:

EV = (Probability of Winning × Profit) - (Probability of Losing × Loss)

EV = (0.50 × $120) - (0.50 × $100)

EV = $60 - $50

EV = $10

What we’ve learned is that for every $100 wagerd on tails at +120 odds, you can expect to profit and average of $10 per bet over the long run, making this a +EV bet.

The Relationship Between EV and FV

The connection between these two concepts is fundamental to profitable betting: Expected Value is calculated by comparing your Fair Value assessment to the odds a sportsbook is offering.

In summary, remember to find the Fair Value using your own research or a consensus of sharp sportsbooks and determine the true, no-vig probability of an outcome. Then compare odds, by finding a sportsbook that offers odds more favorable than the FV you previously calculated, and then finally, calculate the EV using the FV probability and the sportsbook's offered odds. If the EV is positive, you have found a profitable betting opportunity.

So there you have it. Don't let the math scare you. That's the easy part. Researching the data points used for input is where the real work comes from. Relish the process, it's that important.

I hope I was able to shed some light on this subject, and like I said, you will absolutely want to incorporate these analytics within your own research. Some might even say it's +EV to do so. 😂 (sorry, data science humor)

LFG!

~Let's Go David J