The main reservation I have about the SCU grads is that they likely don't have an established employment history; I already know they were at different rentals every year during their studies (which is common for college students, including myself back then).But no matter, I'll collect data from all applicants and pick the one that looks and feels best (as @Kelly N. and others have suggested)

Include data on how you came to that number (comps, recent sales, neighboring properties' current tax assessments).If any tenants are only month-to-month, I would suggest you go ahead and have them sign a new lease.

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The SF data was simply used as a tool to extrapolate for other communities in the Bay Area as a whole, since most services only track major markets.

Your best bet to putting together a spread sheet you can use over and over is to get quotes from local contractors then make that your data base on a per square foot basis, unit basis or per linear foot.

I created it by manually pulling data from the MLS and presenting it in a way where you can get an idea of what subdivisions are promising and why, in as real-time as possible.Everyone has their opinions on how to tell if a particular market is ideal for an investment.

@Juan Cabrera, you are absolutely right about to-the-moon because my data analytics indicates that pockets of JC are moving from being rental owned (high cap rate) to owner owned (low cap rate but high prices).

If your not sure use sites like Zillow or your local property tax assessor data.

The pitches were very enlightening and provided some good data.

Lenders usually make 1 point on the loans and just as much work or more work for a new buyer entering commercial than an experienced entity buying a 10,20,30 million property etc.I am buying a small office condo to house one of my data workers.