ATS Stats

3 Reasons Why ATS Stats are Useless for Sports Betting

Although statistics are the lifeblood of winning handicapping models, many sports bettors approach statistical analysis poorly. Rather than compare teams and player match ups from a statistical perspective, they instead data mine a massive pool of stats in a search for trends. In order to discuss this topic further, let me introduce a few terms.

ATS stands for “against the spread”; this is how well a team has done against the point spread, as opposed to “straight up”, usually written as “straight”. A square bettor is a novice, or an inexperienced bettor (or sometimes an outright fish), where a sharp bettor is one who is considered a professional, educated etc.

With those terms now understood, my personal opinion is that many squares striving to become sharp, waste too much time on ATS data.

Reason #1 – Most trends are data mined variance used to sell a certain side.

Touts are the people who sell stats, and many touts are huge on ATS stats; in fact, their very business model relies on them. Picks sites, such as, have 15 or more cappers working under them, and when drawing up featured advertisements, they hone in on data mine stats.

Most desperate gamblers get excited when seeing a capper is 13-4 in his last 17, and that some other capper is 6-0 on his last six Friday night picks. A statistics minded person looks at it much differently:

The influence of luck and variance - coin flip example.

  • If one person simply flipped a coin 17 times, there is a 9.09% chance they’d flip heads 13 or more times.
  • If a team of 15 people flipped a coin 17 times each, there is a greater than 73% chance that at least one would go 13-4 or better in flipping heads.

As far as the 6-0 stat goes, that’s more randomness: Friday was selected because that’s where the stat looked best. If no one went 6-0 for a given day of the week, we’d be hearing about how some capper went 5-1 on his last six Tuesday’s, Thursday’s, or some other day’s picks.

The important points is: it was largely expected one capper would be 13-4 or better, and that there is nothing significant about “Friday” in this example.

Sports betting trends against the spread are quite similar, yet there are even more opportunities for data mining. Recently, I heard a stat that from the 1990 to 2007 season, teams with an average number of offensive holding penalties greater than 1.6 who are favored coming off a bye week are something like 16-5 ATS.

First off, this has major sample size issues; secondly, it is a quirky stat similar to the example above. If you dig deep enough, it is because of the randomness contained in a vast field of information that you’ll find something that looks good.

For more on the math side of things (and even more coin flipping), read the article on expected value.

Note on sample size.

The smaller the sample size is, the more likely that variance exists. There are often stats such as this: Since 1994, the Lions when favored by 3 points or less are 0-5 ATS. So what this tells me is that once every three years the Lions are favored by 3 points or less, and they have never won? Big deal; this is certainly not a stat you’d want to base large volume bets on.

Reason #2 – Point Spread Data prior to 2006 is tainted.

Prior to the online gambling boom, most sports betting was done with locals or in Las Vegas. Betting limits were rather small, unless you were a proven whale with good credit and a losing track record. Therefore, most bookies and Vegas sports books got away with shading their lines to increase profits.

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For example, when the fan-favored Yankees played the worst team in the league, the bookmaker wasn’t too worried about giving away +EV bets on the opponent, because they expected to take a large number of Yankees bets no matter what the price. Today, bookmakers cannot get away with setting off lines. The market is much more efficient, and the limits are large. At, it is possible to bet $50K in one shot on an NFL game.

At Pinnacle, bettors can wager $30,000 to $100,000 on some games, and if the line moves even slightly, they can bet it again and again. Those making these massive bets are extremely sharp bettors, who often work in teams/syndicates. Back in 2006, it was possible to bet, at what we’ll call “square sites”, only off market lines.

After a while, though, the betting public and the smarter squares realized that if you bet any line arbable with Pinnacle or Bookmaker, skipping the arb and just betting the offline, it was easy money. In the end, even the “square sites” were affected by the market becoming efficient and were forced to set much more accurate lines.

In a nutshell.

ATS stats that date back to a time where lines were mostly inefficient doesn’t tell much of a story at all.

In fact, if you go too far back, say to the 1990’s or earlier, for betting lines there are even more issues. Those lines you’re running the ATS data on in most cases are either some local bookie’s line or a certain Vegas line offered at some point or another for who knows when, how long or by whom, or they are pure fabrications. The latter is mostly likely the case, because when data first was offered for sale on a large scale, it was always with a declaimer that they used today’s most advanced handicapping methods to create what the line should have been.

As a few years passed and there was a larger market for stats based services, this was dropped, and rarely ever is it questioned where line history from 1993 might have come from. Is it the closing line, the opening line, Sands’ line, or was it the line someone’s cousin Vinny used for his bookmaking business. Most don’t know; however, they still use it to come up with ATS records using the past 17 years worth of data.

Conclusion: If you use ATS data, be suspicious of any data prior to 2006. Even with data after 2006, you want to make sure the data represents the closing line.

Reason #3: Every game’s point spread is a fresh and unique creation.

How a team does straight up can always be quantified, because there is no market created line. ATS stats are extremely subjective. If you use handicapping methods, data, or anything else from 4 years ago to create a betting line, that line is not going to be anywhere close to the line created using today’s method/data.

Today, odds makers do their best to predict the betting market, which is often based on their opinion of true probability. They then post the line and make adjustments to it as bets come in. The latter is a concept referred to as the line sharpening. The large educated bettors who help sharpen the line consider all data; anything they see that has value, they’ll bet. When the line reaches the point where big smart money is no longer interested, the line is considered sharp.

Any betting system such as this one: bet all home underdogs coming off a bye, which had a fourth quarter lead and then lost, is destined to lose money over the long haul. For a system to have any value, it has to consider the current betting line.

Because most all ATS database generated “systems” fail to account for the current market price and tell bettors to make the bet no matter what the line, the system is flawed. Such systems are likely to win going forward 50% of the time at best, making them no better than random picks, and in the end the bettor loses juice.

ATS spreads can have value, however. To see a small hint of this, see my article of “effects of the NFL bye week”. Other than that if you’re thinking statfox mined data gives you an edge, you need to learn more about the market. I touched on the market a bit already in this article, and also in my article “what to do when the line moves”.

If you’re discouraged by this, don’t be! There are plenty of systems out there that take into account the current market price. For example, see my article on “basic strategy teasers”. For the recreational bettor, all of this is actually good news. In an efficient market, on average the house edge is the same for most spread bets. If you now just shop for the best price on each bet, your chances of getting lucky are the same.

A quick note on recreational bets.

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Final thoughts on using ATS stats when betting online.

In closing:

  • To the recreational bettors, keep having fun, bet responsibly and hope luck is on your side.
  • To the experienced bettors, ignore these system bets that use ATS data only and instead focus on systems that account for the current market price.

No matter which type of gambler you are, I wish you the best of luck.

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