Sportsbooks look at several things when determining how to profile your account, and have systems in place for when to review your account.

Let's start with what they look at.

Price Sensitivity

Price sensitivity means you only bet at the best price available across many (ideally all) sportsbooks available to you.

This is lesson #1 in Sharp Betting 101. If you can bet $500 to win $1000 on the Lakers to win at FanDuel, or $500 to win $1200 at DraftKings, where are you gonna bet?

This is typically only relevant when a trader is reviewing a large bet in real time, as it is not worth it for sportsbooks to analyze the data on this retrospectively. Just betting at the best price doesn't make you a sharp, and the sportsbook will still beat you in the long run if this is your only trick.

Net wins/losses

This one is obvious -- are you up or down? How much? Over how many bets? How much total handle?

As you might expect, sharps are expected to be up, and squares down. The larger the sample size of bets you have in your account, the more conviction they have in this conclusion.

However, there is a conflict within this metric: it is the most significant to the sportsbook's actual business, but poorly predictive of long-term winning.

Being up after your first 10 bets doesn't predict that you'll be up after 1000. Getting 7/10 tails on coin flips doesn't mean you expect to get 700/1000. But... if you do get 700/1000 tails, you might want to get a different coin. If you're beating a sportsbook for $100,000 and they don't know why, they're still going to limit you.

Closing Line Value (CLV)

CLV, on the other hand, is very predictive of long-term success.

What is CLV?

CLV is the difference between the price (odds) you bet at, and the price the market closed at when the game started. CLV does not exist for live bets, nor do the actual events of the game impact pre-game CLV. Nobody knew Aaron Rodgers would blow out his knee 4 plays into the game beforehand, so that event doesn't factor into the pre-game prices.

If you bet at +100 odds and the market closes at -110, you got a good price. This means you had positive CLV, which indicates sharp betting.

If you bet at +100 odds and the market closes at +110, you got a bad price. This means you have negative CLV, which indicates square betting.

The most straightforward way to win at sports betting over the long run is to consistently bet at favorable prices. This is the "beat the sportsbooks at their own game" approach, and they are very familiar with it. When you consistently beat CLV in an obvious way, they notice and limit you.

How do sportsbook measure CLV?

There are a few valuable ways to measure CLV in order to make long-term predictions.

  1. Price-only

    Your betting history is the data sample. If you are beating CLV at a statistically significant rate, you are probably a sharp. The chances you are an exceptionally lucky square get smaller as your sample size of bets gets bigger.

    If you come out with guns blazing and mash a bunch of +EV bets on a new account, you will be heavily limited within the week.

  2. Price + Handle

    Let's play the cat and mouse game for a second. If you want to beat the above system, place a bunch of $1 parlays at terrible prices and then bet big on your real +EV bets. You pile up negative CLV to hide your sharp bets.

    Spoilers: this ain't the sportsbook's first rodeo.

    The way the sportsbook counters this is by factoring in how much you bet into their CLV calculation. Beating CLV by 10% on a $1,000 bet outweighs losing 10% CLV on 10 $1 bets.

Bet Selection

Betting in certain markets is often predictive of sharpness or squareness by itself.

A rule of thumb: the more popular the market, the more it is associated with square betting. Moneylines? Yep. Touchdown scorers? Home run hitters? 3-pointers? Oh yeah. Parlays and SGPs? Square Mecca.

What about sharp bets? If someone exclusively bets 3rd Quarter Alternate Spreads and NBA Player Assists + Rebounds Combo markets at 9am, they are a sharp. No normal basketball fan gives a shit about these stats, nor are they interesting to watch and root for.

Bet Timing

Person 1 bets from 7pm-9pm on weeknights, and all day Saturday and Sunday.

Person 2 bets from 9am-11am on weekdays, and not at all on weekends.

Take a wild guess which is which.

When do sportsbooks decide if you're a sharp?

A brand-new account doesn't have any betting data. It's a clean slate that is neither square nor sharp... yet.

Once you start betting, there are several things that will get your account looked at by the sportsbook.

Your First Withdrawal

This is often the first time a sportsbook will look at your account specifically. Let's look at 3 scenarios for what they might see:

  1. Bonus Abuse

    You deposited $1,000, used their $1,000 No Sweat First Bet on a big underdog moneyline, then withdrew your winnings. Looks pretty sharp to me. Limited.

  2. Too much CLV

    You deposited $1,000 and placed 10 straight bets. 9/10 beat CLV, 7/10 won, and all 10 of them were to win the same amount. Looks like you have a source of +EV bets and know how to manage a bankroll. Limited. This is the main pitfall for sharps who are impatient.

  3. Square behavior

    You deposited $1,000 and used the No Sweat First Bet on an underdog moneyline at sub-optimal odds. After that you placed 20 bets, 10 of which were parlays. 7/20 beat closing line value. You busted out once and deposited another $500. Looks pretty square to me.

Large Bets

If you're betting big enough, you will trigger trader reviews for individual bets. The trader first makes a judgment call on whether or not to accept your bet. If your bet is obviously sharp (or square!), they can flag your account accordingly. These human-input flags are weighed heavily during future reviews, as the traders have the real-time context and experience that data often does not.

Here are two example scenarios:

  1. Sharp

    You try to bet $1,500 on an NBA player prop. This is more than they automatically accept on this market, which triggers a trader review. The trader looks at their odds screen and sees their price is significantly off from the rest of the market. Bet denied. Flagged as sharp. Limited.

  2. Square

    You try to bet $10,000 on a primetime moneyline. Again, this is higher than they accept by default and it triggers a review. The trader sees that other sportsbooks are offering a better price for this moneyline. Accepted. Flagged as square. Limits raised.

Automated Triggers

We live in the era of data, and it's pretty easy to have a bot monitoring people's betting histories and sending alerts to traders to review accounts. The tricky part on their end is configuring the alerts to prevent false positives and avoid false negatives.

  1. False Positives

    A false positive in this context is when a square bettor gets flagged as having sharp activity. Limiting a square whale is a very costly mistake for the sportsbook, and they are accordingly cautious when reviewing these alerts.

  2. False Negatives

    A false negative is when an undetected sharp bettor places sharp bets without triggering alerts. In this case, the sportsbook wants alerts that aren't happening.

  3. "Perfect" alerting

    A perfect alerting configuration would have no false positives or false negatives -- it would find all the sharps and let the squares bet uninhibited. This is not realistic without a large data set per bettor -- there is too much volatility within a small sample size of bets unless the data is truly egregious.

There are also practical constraints around how much a sportsbook can rely on alerting. Intuitively you might expect them to err on the side of having more alerts so they don't miss sharps, but that can be unwieldy for traders, who have other job responsibilities. Alerts that are too noisy defeat the purpose of having alerts -- the trader sees too many false positives, loses trust in the alerting configuration, and stops scrutinizing alerts closely. Sharps slip by undetected.

The Ideal long-term strategy

The game for you, the bettor, is to get profiled as a square early and pile up square data while making your profit elsewhere, such as with our affiliate GBank credit card cashback. Eventually the sportsbook has enough data to semi-permanently flag you as a square, at which point your account may not be reviewed again for a long time.

This is the holy grail for a sharp bettor: an account profiled as square with high limits.