I’m a little confused about how the leasehackr score is calculated. From the description, I thought it should be MSRP / (effective monthly payment) / 12.
So for example here I would expect to get 46960 / 557 / 12 = 7.03, where 557 is the effective monthly from the calculator, but the calculator reports it as 7.7 years.
Am I missing something?
There is absolutely 0 reason to worry about it. It isn’t a useful metric anyway.
I find it a useful metric, and here is why. In my opinion, the value of a lease is generally proportional to the MSRP of the vehicle. In other words, I generally think a lease that costs $x/mo on a $y car is roughly as good a deal as a 2$x/mo lease on a $2y car. If you don’t think that lease price and MSRP are related in this way, then the leasehackr metric is not useful for you.
Most of the criticisms about leasehackr scoring and other metrics that I have seen are that they can’t be used to measure absolute value. In other words, you can’t make blanket statements that a leasehackr score above 7 is a good deal. As one example, brand XYZ may not lease well, so a low leasehackr score deal for brand XYZ might be “better” (more rare) than a higher leasehackr score deal for some other brand that does lease well. In this scenario, we are typically searching for a deal on one particular model of car. In other words, we don’t just care about the MSRP of the car, so the leasehackr score is not that helpful.
If you don’t care about brands and you just let MSRP represent the value of a lease, then the leasehackr score is a decent metric for “a good lease”. This is exactly what I am trying to do with the Edmunds data. Take a boatload of lease information and find cars that are “leasing well”.
I don’t think the leasehackr score is all encompassing, but if you think lease pricing should be considered relative to MSRP, then I argue it has some value.
There are two massive flaws in your logic here.
It assumes that msrp is actually a normalized value and that a $40k msrp vehicle from one brand is actually a better value than a $35k msrp vehicle from a different brand.
It assumes that a higher score on one vehicle means its a better deal than a lower score on a different vehicle.
I will concede one scenario where it is potentially useful. If you’re looking at two identical models that are optioned differently such that their msrp varies, it can be useful for comparing those two identical models.
Yes, that is what I said is the underlying assumption. I agree with you that this isn’t strictly true. Do I value leasing a $40K MB the same as leasing a $40K Ford? Probably not. But I would argue that it’s close. A $40K msrp vehicle may have the same value as a $35K msrp vehicle from another brand, but probably not the same value as a $20K msrp vehicle.
We’re going in circles here. If you accept that the value of a lease is proportional to the MSRP, then this is true. If you don’t, that’s fine.
Again, I’m not saying the leasehackr score is perfect. But it’s easy to compute, not subjective (to compute, though maybe to interpret 
), and if you accept that there is some (admittedly non-perfect) relationship between MSRP and value, I think there is value in the leasehackr score.
The reason I wrote my original post is that I was looking through thousands of lease prices from my Edmunds hacking project. I found that I was basically looking at the monthly price and the MSRP of the vehicle to decide on whether it was a good deal or not. This is basically what the leasehackr score is. (I don’t even know what half of these models are, so how else am I going to value the vehicles besides the MSRP?)
Different brands price differently. There are some that sell essentially at msrp as their marketing strategy. There are others that jack up the msrp and then offer big discount/incentives to give the consumer the perception of a good deal.
What is the difference between a $35k car sold for $35k and a $35k marked up to a $40k msrp and sold with a $5k “discount”? Nothing, yet the lh score between those two would be significantly different.
Now, imagine the $35k car marked up to a $40k msrp is sold for $38k. If you compared the lh score on it to a $35k car at msrp, you’d mistakingly think it was the better deal.
I think we basically agree. I’m just saying there is value in the number even if it is not perfect. If you accept that there is 5/40 = 12.5% error in MSRP “value”, then there can be about that much error in leasehackr scores too. I don’t advocate for comparing a 5.00000001 leasehackr score against a 5.0 leasehackr score. Or maybe even a 5 against a 6. But I can tell you a lot of the deals I’m seeing have 4.0 leasehackr scores, and I can’t imagine these ever being a “good deal”. You could have bought the car outright in 4 years at the effective lease rate.
For the record, what I’m doing now is filtering out anything below a 6 as “probably not great”. I don’t think this should be contentious.
Don’t need a “score” to tell you that.
I’ll merely address the math question since that is the question and not whether the metric is valuable.
Don’t know what the disconnect is. I thought maybe it was effective sans tax. It does come closer that way, but only if you include the DAS tax, which then doesn’t make sense to include that but not monthly tax.
This discussion is dangerously close to the % per month MSRP metric😁
Flip the numerator/denominator and that’s basically what it is.
It’s the same discussion times 12
Just because the lh score is 4 does not mean that one could buy the car and pay it off in 4 years at that rate.
Only because it got derailed into discussing the value of the number rather than just HOW that number is calculated. This can be a very objective topic if folks let it be.
Here is my objective answer to how LH Score is computed:
Leasehackr Score = (MSRP * (1 + Tax Rate)) / (Total Lease Cost / Months) / 12
Of Which:
Total Lease Cost = Monthly Payment incl. Tax * (Months -1) + Drive-Off + Disposition Fee - Rebate - Gov Fee
We compute LH Score on Signed! slightly differently because of the slightly different data we collect.
LH Score definitely oversimplifies the subject matter, but we think it’s good to have a benchmark number to start the shopping journey. The more people learn, the more they understand the intricacies of leasing and the myriad of factors that need to be considered when evaluating a lease, the less relevant the LH Score is. Not everyone has the time and energy to dive in deeply, however. Having a score to reference is better than staring at a blank canvas, not sure where to start.
That’s my 2 cents!
Aha! So tax is the discrepancy. The calc is programmed to compare lease payments with tax vs total MSRP with tax as if you paid tax on full MSRP. Weird. I kind of get it, although it really should be on sale price. But not a big deal.
Using that, I do get 7.6 in the OP’s example.
FYI, “-rebate” is incorrect since that is already taken into account in the payment. I didn’t subtract the rebate and got the 7.6.
Thanks!
So the difference is that you are applying the tax rate to the MSRP and I was not.
One of the interesting things about the LH score is you can interpret it different ways.
One interpretation is that it is a measure of leasing vs. buying. If you look at it this way, including the tax rate in the MSRP makes sense since you would pay tax if you bought the vehicle. On the other hand, where I live the tax rate for leases is different than purchasing, so applying the lease tax rate to the whole MSRP is a bit strange. It’s also a slippery slope because some of your incentives might only apply to leases, and obviously we can’t factor that into the LH score without a lot more information.
If you interpret the LH score as value (where MSRP is a proxy for value) scaled by the effective monthly payment of the lease, including tax does not really make sense. Leasing the car in a state with a higher tax rate does not give me more value
Anyway, thanks for the clarification!
Using OP’s example, in case anyone cares:
(546 * 38) + 1057 + 395 - 144 = 22,056
22056 / 39 = 565.54
46,960 * 1.1022 = 51,759
(51759 / 565.54) / 12 = 7.626
Being that it’s a relative score and not an objective score, as long as tax is applied universally, it should make no difference here.
Tax is dependent on location, so it’s not applied universally.