How GasPredictor.com's St. Louis Gas Predictor Newsletter Saves You Money

On this page:

• The Bottom Line
• Description of the test scenario
• Highlights of the test
• Why our results for St. Louis are so unrealistic.
• Table showing day-to-day events

The Bottom Line of the Test

Our subscriber paid $129.73 for gas since 10/12/2009. Our control driver paid $118.75. Our subscriber is ending the test with 6 more gallons of gas in his tank than the control driver has. The extra 6 gallons in the subscriber's tank is worth $14.15 . Subtracting that from the amount he spent for gas means that he spent $3.18 less than the control driver did. Extrapolating this savings over a full year (262 business days) yields an annual savings of $29.76.

Following our recommendations would save you $29.76 per year, or $25.17 more than the cost of a one-year subscription to the Gas Predictor Newsletter.

Note: We began publishing our St. Louis Gas Predictor on October 12, 2009, so this test does not encompass an entire year of predictions.

Be sure to read "Why our results for St. Louis are so unrealistic" for an explanation of why this is a fluke. We do not mean to represent this as a typical savings for our subscribers, but that's the way the test scenario worked out. Yes, we believe we can save you money on gas, but not that much.

And as a bonus, you get to smirk when you see the price go up and you knew it was going to go up. No extra charge.

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Description of the Test Scenario

This test compares two hypothetical drivers, the "subscriber" and the "control driver." Each has a car with a 14 gallon tank, each uses exactly two gallons of gasoline every business day, and each has just filled his tank the evening of October 11, 2009.

Our "control driver" does not subscribe to the Gas Predictor Newsletter. He simply leaves his gasoline budget to chance. He fills his tank whenever he gets home from work with only two gallons in the tank. Thus, he buys 12 gallons of gas every sixth business day, without regard to the cost. This represents the way most people buy gas, and shows how much a hypothetical driver would pay for gas without the benefit of our Gas Preditor.

On October 12, our "subscriber" begins receiving his St. Louis Gas Predictor Newsletter by e-mail. Each night, he tries to follow our recommendations, even though he can not always do so. If we recommend buying gas that day, he fills his tank, even if he just filled it the night before. If we recommend holding off and buying gas the next day, he does not buy any gas unless his tank is absolutely empty. If his tank is empty, he buys four gallons of gas, to get him through the next couple of days, and yet leave enough room in his tank that he can take advantage of any buying opportunity that our newsletter recommends.

We recognize, of course, that this test is not quite realistic in several ways. For one thing, nobody uses exactly two gallons of gas every single day. And nobody drives their car only to work, not driving at all on non-business days. Nobody has off every day that the Chicago Mercantile Exchange (CME) commodity exchange is closed. Nobody buys gas by the gallon, instead rounding up to the next dollar or otherwise easy amount of money to enter in their checkbook (or to make change, if they're paying in cash). And even though our predictions are perfectly wonderful, we're sure none of our subscribers would bother to buy just two gallons of gas because we recommended it. (No, even we don't do that.) However, we had to come up with fixed, simple rules in order to make the test a fair comparison between using our predictions and not using them.

For this test of the St. Louis Gas Predictor Newsletter, the price of gas used is the second-lowest price for unleaded regular gasoline in the St. Louis area at about 9:00 AM Central Time.

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Highlights of the Test

Coming Soon!

Why Our Results for St. Louis are So Unrealistic.

We have only been publishing the St. Louis Gas Predictor Newsletter for five and a half weeks as of our first anniversary on November 18. That's just 28 business days. Realistically, that is not enough data to form a reliable extrapolation for an entire year. One unusual stroke of luck, where the control driver happens to buy gas at a very inopportune time, will skew the results in the subscriber's favor dramatically.

By dumb luck, the control driver should buy gas the day before a large price increase or the day after a large price cut once in a while. But in this short test period, the control driver happened to get no such lucky breaks.

As we point out in the "highlights of the test" above, the control driver bought gas four times, and each was a bad time. Twice, he bought gas within two days after a large price increase, and twice it was within two days before a large price decrease. Yes, we predicted each of these price changes, and our subscriber was able to benefit from our predictions, but the control driver never got a break.

As time goes by, there will be fewer of these coincidences, and the control driver will get a break once in a while. With a more realistic and larger set of data, our hypothetical subscriber will save a significant amount of money on gas, but not a ridiculous amount.

The same sort of thing happened happened when we published a similar summary on the occasion of our 100th prediction. At that time, we had only been publishing our Houston Gas Predictor Newsletter for a few weeks - 19 business days - and we got similarly unrealistic results. Now, more than 8 months later, the same test scenario results in a hypothetical savings of $10.01 per year for our Houston subscriber, which is perfectly in line with our National results. We are sure the same thing will happen as we generate more results for our hypothetical St. Louis subscriber.

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Table of Day-to-Day Events in the Test

Key

• Date - The date we issued this prediction, pertaining to the next business day.
• Buy Today? - Did we recommend buying gas that day ("yes"), or waiting to buy gas the next day ("no")?
• Avg. Price - What was the second-lowest gas price in St. Louis? This is the price on the date given, not the predicted price for the next day.
• Sub. Gas in Tank - How much gas did our subscriber have in his tank at the end of that day, when he received his Gas Predictor newsletter?
• Sub. Bought - How much gas did our subscriber buy that day, whether we recommended it or not?
• Sub. Paid - How much did our subscriber pay for the gas he bought that day?
• Ctl. Gas in Tank - How much gas did our control driver have in his tank at the end of that day?
• Ctl. Bought - How much gas did our control driver buy that day?
• Ctl. Paid - How much did our control driver pay for the gas he bought that day?

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