How Good Is That Rust-bucket In The Showroom Window?

The Cadillac Eldorado Coupe is one of the vehicles the PCs might consider. Image by Samuel Faber from Pixabay
Something of a bare-bones post this time around, necessitated by the fact that I’m away from home and all its resources.
I haven’t been idle while away; I had prepared more than enough RPG work in advance to see me through. Part of that work involves… well, that’s a little more complicated.
You see, the PCs in my superhero campaign are currently cut off from most of their usual resources, on a limited budget, and operating under “deep cover” conditions – which means that to get around, they will need to buy a couple of second-hand cars. The current game date is in 1986. But, at the moment, I don’t know what criteria they will choose to prioritize – so I’ve been forced to list almost every vehicle on the second-hand lot. Lots, actually – there’s one that will be all GM products, including subsidiaries like Oldsmobile, Chevrolet, and Cadillac – and one that will be Ford-oriented.
Heck, at this point, I can’t even be certain what their budget will be (just that it will probably be a lot tighter than they think it is going to be)!
So I’ve been putting together a sortable spreadsheet of the different cars, I have a huge number of possible criteria for them to choose from, and I’ve been busy populating it. But that’s only indirectly what this post is about.
The Value Of A Rust-bucket
To determine the price of the different old cars, I’ve been forced to develop a methodology.
- Start with the new price. This can be hard to determine, but if you give me a data point I can extrapolate forwards or backwards based on the knowledge that in the 70s and the 80s, prices of cars rose by about 3% a year, much less than the inflation rate.
- Add the value of any extras.
- Adjust the new-car price for inflation, i.e. into 1986 dollars (but it can be done to any year). This matters because the cars are to be bought “now” with “now” dollars, and so gives a basis for valuation.
- Factor in the Depreciation of the car. This tends to be highest in its first year of age and then diminish to a slower, more progressive decline – but the pace of that decline will vary a bit from car to car, model to model. In particular, if there’s some reason for a car to hold its value unusually well, or unusually poorly, this may need some manual overriding, so it’s not as straightforward as a simple calculation – that’s just the starting point.
- Load on the state and federal taxes. In the state where this is to occur, the state taxes are 12% and the federal taxes are 8% (according to the in-game economy). And, of course, these compound. So multiply by 1.12 and then 1.08.
- Load on a profit margin for the dealer. For the GM dealer, I’ve set that to 18%, for the Ford dealer, 22%. So multiply by 1.18 or 1.22, respectively.
- Apply a factor for the condition of the car. This could as much as halve the price, but that’s not very likely. Most will be in the 70-85% range.
- Apply a factor for the level of Lack Of Demand for second-hand cars of the type. If a car is on the verge of becoming a collector’s item, or has already achieved that status, this value may actually be less than 1, so that the value of the car that the dealer can command is higher than even the adjusted “new” price! In other words, drop the price if no-one will pay what the dealer is asking, and put it up if the car is likely to be a hot property.
- That gives me the “sticker price” – but no second-hand dealer ever expects to get the ‘sticker price’, they expect to have to bargain. Some of that comes in the form of a trade-in, some may come in terms of (discounted) insurance being thrown in, but some will come from how willing the salesman is to deal, and how desperate they are to offload a particular car (so that they can put something more profitable in its place). So, I use the profit margin determined earlier as the basis for a “maximum discount” that a dealer might offer. These two values give a high price (the sticker price) and low price (the discounted sticker price) for the vehicle.
This takes into account every factor that I could think of, and does most of it more-or-less automatically. It’s easier for me to use online calculators to calculate the inflation and depreciation, though I can do it manually if I have to.
The Random Element
The biggest unknown is the 7th item on that list – the condition. In addition, while I’m controlling the manufacturer, brand, model, and year (from what was available at the time of manufacture), there are some things like color that should be randomly determined.
To address these random elements, I’ve put together a series of quick tables, based around one or more d10 rolls (because that’s the die I happened to grab on my way out the door).
Other campaigns
But, after doing so, it occurred to me that with a little tweaking and loose interpretation here and there, these tables could be just as applicable to a motorcycle, a yacht, a cabriolet, or even the quality of an inn or tavern. In other words, most campaigns would be able to use them for something at some point. So the key point of today’s post is to share them with you.
But I did not have time to create pretty HTML tables as I usually would – so these will be offered bare-bones, Judges’ Guild style.
Color Classification
Roll d10
1 – 4: Common
5 – 7: Frequently-used
8 – 9: Uncommon
10: Rare
This uses a 4-3-2-1 pattern. If I had one more result to allocate, I would have bumped ‘Common’ up to a 5.
Common Colors
Roll d10
1 – 3: Black
4 – 5: White
6 – 7: Silver
8: Light Gray
9: Dark Gray
10: Gold
This (and subsequent tables) are a distillation of a general impression left from (a) Australia in the 70s and 80s, and (b) watching American TV shows from the era. I do not attempt to vouch for their accuracy – and I might not want them to be accurate, anyway. I want the overall impression that the results give to feel realistic – and that means a lot of car colors may be over-represented. There was a lot of give-and-take; I had a lot more colors to list than slots available!
I’ve used a 3-2-2-2-1 pattern here, but broken that last ‘2’ up into light and dark variants.
Frequently-used Colors
Roll d10
1 – 3: Red
4 – 6: Yellow
7 – 8: Navy Blue
9: Blue
10: Dark Green
A 3-3-2-1-1 pattern. I would love to have been able to bump the Navy Blue up to match the Red and Yellow frequencies of occurrence, but there wasn’t room in the table.
Uncommon Colors
Roll d10
1: Slate Blue (grayish blue)
2: Beige
3: Tan
4: Brown
5: Blue-Green
6: Lime
7: Mint Green
8: Sunset Yellow (i.e. slightly orange)
9: Cherry Red
10: Purple
I saw cars painted these colors quite a bit. Not as often as the preceding categories, but enough to make an impression.
Rare Colors
Roll d10
1: Cream / Pale Yellow / Sand
2: Pink
3: Hot Pink
4: Sky Blue
5: Grass Green
6: Apple Green
7: Orange
8: Two-tone (roll twice more, ignoring this result if it comes up again)
9: Fleck / Metallic / “Gemstone Glitter”
10: Fancy paint-job / Decorated
Fading
Roll d10, Add 1 to the result for every 5 years of age
1-3: None
4-6: Slight (value loss d10%)
7-8: Somewhat-faded (value loss 10 + (2 x d10)%)
9: Badly Faded or Peeling (value loss 20 + (2.5 x d10%)
10+: Patchy / Cracked / Crazed (value loss 20 + (3 x d10%)
Rust
Roll d10, Add 1 to the result for every 5 years of age
1-3: None
4-6: Superficial (value loss 1.5 x d10%)
7-8: Some Spots, may be hard to spot (value loss 10 + (2 x d10) %)
9: Deep Rust, Some paint bubbling (value loss 25 + (2.5 x d10)%)
10+: Riddled with rust, serious paint bubbling (value loss 40 + (4 x d10)%)
General Condition
Roll d10
Add one for every 5 years of age
Add one for paint fading result of 8 or more
Add two for rust result of 8 or more
1-4: Good
5-7: Repaired (value loss 5 + d10%) (+ see below)
8-9: Dodgy / Poor (value loss 15 + (3 x d10)%) (+ see below)
10+: Appalling (value loss 45 + (5 x d10)%) (+ see below)
Repairs
Roll d10
Add one for paint fading result of 8 or more
Add two for rust result of 8 or more
Add two for condition result 5-7
Add three for condition result 8-9
Add four for condition result 10+
1-4: Excellent (as new)
5-7: Solid, professional (condition value loss halved)
8-9: Rough (condition value loss unchanged)
10: Amateurish (condition value loss doubled)
Extras
Roll 2d10, “Interpret” the results if inappropriate
2-4: Performance Enhancement
7 in 10 chance of another one being fitted
Choose randomly from:
Brakes
Tyres
Engine
Gearbox
Suspension
Only if all above are present & a 6th performance enhancement is indicated:
Nitro (post 1950 only).
5-8: Cassette Player (8-Track if appropriate, reroll if not available yet)
9-12: Decorative Tyres (white-walls, radials, bigger wheels, whatever)
13-15: Radio / (8% chance CB Radio 1975-1985)
16-18: Air Con / Heater (reroll if not available yet)
19-20: Seats / Trim
This uses a dumbbell-shaped die roll for the first time – the most likely result centers on a result of 11. So I started with that and used the most frequent outcome for the ‘middle values’ (4 out of 19), then progressively placed less probable results (4 and 3 out of 19, respectively) to either side of that, and so on. A lot of results had to be conflated to get the number of results down to a manageable number, but that forced the creation of the subsystem for performance enhancements which, I actually think, is an improvement on a purely random result.
I estimate the value of any extras if that information isn’t available to me. It usually isn’t. There’s a lot of rule-of-thumb involved. Value from extras should be added before any adjustments (including inflation and depreciation) are calculated.
Conditional value adjustments & an example
These are applied consecutively, not summed.
Basic Maths: adding 10% is the same as multiplying by (1 + 10/100), or 1.1. In other words, if you’re adding a percentage of less than 100%, write a 1, put a decimal point, and then write the amount of the percentage. Adding 12.75 percent is multiplying by 1.1275.
If, for some reason, you need to apply an increase of more than 100% – lets say 245% – you add the hundreds to the basic 1, and then write the rest after a decimal point; adding 245% means multiplying by 3.45.
To reduce by a percentage, you need to use (100 – percent) and then divide by 100 to get the number you should multiply by. So subtracting 4% = multiply by 0.96, subtracting 8% = multiply by 0.92, subtracting 12.5% = multiply by 0.875.
Notice something: if you add the individual digits of the percentage to the individual digits of the multiplication factor, each one comes to a 9, except the last ones, which come to a 10: 1+8=9, 2+7=9, and 5+5=10. Once you know this, you can work the calculations the other way quickly and easily – so much so that I haven’t even shown this work in the example below.
EG a $10,000 vehicle which gains 8.2% in inflated dollars, loses 25% (1st year) and 14.5% (2nd and third years), with a 4% value reduction for lost performance (half of which can be regained with a full tune-up), which also loses 12% for fading paint, 16% for rust, 8% for condition, halved, with $800 worth of extras, would be worth:
- 10,000 + extras $800 = $10, 800;
- plus inflation: 1.082 x $10, 800 = $11, 685.60;
- less 1st year depreciation: 0.75 x 11, 6585 = $8, 764.20;
- less 2nd & 3rd year depreciation: 0.855^2 x 8 764.20 = $6, 406.85;
- less performance loss: 0.96 x 6 406.85 = $6 150.58;
- less 12% for fading paint: 0.88 x 6150.58 = $5 412.51;
- less 16% for rust: 0.84 x 5 412.51 = $4 546.51;
- less 8% for general condition, halved: 0.96 x 4 546.51 = $4 364.65.
- I will usually round this to the nearest $5 for convenience: $4 365.
Of course, a car that’s only three years old with noticable paint fading and rust spots would be quite a concern.
To be complete, we next need to add the taxes, demand (from general information about the model, estimate the impact of demand for this particular type of car at this particular time), & profit margin:
- plus taxes: 4 365 x 1.12 x 1.08 = $5 279.90;
- plus-or-minus demand: 0.95 x 5 279.90 = $5 015.91;
- plus profit margin: 1.18 x 5 015.91 = $5 918.77;
- rounded to the nearest $5 again, gives $5 920.
Factor in the dealer’s willingness to do a deal (eroding his profits, or even selling below cost to get rid of a waste-of-space), and you have a complete example:
- less maximum discount = 0.92 x 5 920 = $5 446.4.
- round this, too, to the nearest $5, to get $5 445.
So the dealer wants $5920, but would settle for as little as $5445 – a substantial discount, but one that still leaves him with (18-8=) 10% profit – on a car worth $4, 365.
Oh, and if you want to know how much the extras are worth, multiply any of the above values by the ratio of extras alone to price-with-extras to get the equivalent.
So,
- value of the extras: 4365 x 800/10800 = 323.33;
- Dealer wants: 5920 x 800/10800 = $438.52 (and this is how much he will say they are worth, rounded to the nearest $5, or $440);
- Dealer will settle for 5445 x 800/10800 = $403.33. Except that he would want to keep them on the car and use them to help sell the bigger item!
Behind The Curtain
As a value-added extra, I’ve tried to at least indicate how the tables were derived; you can consider knowing how something is done, so that you can do it (or anything similar) yourself if you need to, as a Christmas Bonus!
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