Thank you for the information. I use Chrome and hadn't noticed an issue, but we have our web guy looking into it to get it sorted. Also, I'll make sure to get the contact info in there.

I've never had an economics education, so I don't know exactly what you mean by "offer," but if you mean the value that it's priced at vs what it's purchased at, I'm not sure that is a relevant value given the malleability of the acquisition prices. I'm not currently including any online store's retail pricing because I don't have any information about how many of the cards are actually sold at those prices. Based on the information available on some web sites, I could make some guesses, but they are bound to be inaccurate. The data is all from completed sales only, and since some of the variables you mention aren't generally available I'm using the quantity sold and the the average price over various points in time to establish the card with the highest cumulative value and compare all the other cards by percentage of that maximum value. I considered altering the weight of certain values, but decided that if I was to do so it would need to be done formulaically to eliminate arbitrary results. There are a few other data points I'm considering adding to the mix, but I haven't yet started evaluating how to get reliable data and how to add them. If I can make the results more accurate, I will.

for your 2nd question… I could do that if I had enough information about how many of each card are used in some number of decks at some level of tournament or above. However, at this point, even with the cumulative data available, the results would be little more then anecdotal, and I don't think they would give any clear signals about the actual demand of specific cards. I like the idea though, so I'll see what I might be able to get out of it.

Chris

I went over how the EV was calculated in my last article, but to recap, I work it up in 2 different ways within my spread sheets. One way kicks out anything worth less than $0.75 and totals the rest based on distribution probability. The other way (which is used here) doesn't toss out the smaller card values. The reason I'm using the later method is a calculation issue since it's more difficult to filter out the lower prices with the way the data is summed. If this is a large issue for you guys I can work on changing the way it's calculated. it really shouldn't matter though because these numbers should be used for comparison reasons. I could assign arbitrary values to each one and as long as they were proportionally the same, they would still be an indicator of which packs have the higher dollar cards on average. Also, the average cumulative value of a pack as calculated here is pulled from real sales data. No where does it assume any card values. If common card X has never been bought as a single on eBay then it gets a $0 price in these figures. That $0.50 Haunting Echoes you mentioned might be hard to shift but but it has been sold at the calculated price in the last 7 days. Good guess on that by the way, in the last week Haunting Echos has sold 68 copies at an average of $0.049, and 265 copies at $0.55 for the last 30 days.

As for using $3.95 for the price of a pack, that is the suggested retail. I know that they are $3.95 at Walmart, $4.99 at Best Buy, $3.95 at Card Store X, $3.50 at Card Store Y, $2.36 when purchased by the box on the world wide web, and $1.00 when your brother Phil "hooks you up" but since I can't predict what kind of deal every person is getting, the Manufacturer's Suggested Retail seemed like a good baseline. I wouldn't use any other value here just like I won't lower the M11 EV because someone traded me a Baneslayer Angel at $10 last night. If you would like to sub in your own values there, feel free, but it won't alter the comparative EV.

Chris