Mark provided a link for you, and I have some additional thoughts/questions for you to ponder:
1. "if you cannot measure you cannot improve" (Lord Kelvin), so your desire to develop a measurement system is important.
2. You suggest the measure is continuous but bounded by 1 and 100. This is typically not considered continuous, but perhaps discrete and bounded at that. You also only give examples that are 10, 20, 30, etc. What is the measurement unit (smallest increment of change reported by the measurement system? if it is 10, then you have 10 categories.
3. What is meant by the phrase "does really well" or "better" mean? These are not operationally defined.
4. Repeatability and reproducibility are the two components of measurement precision assessing the variability of the system (under certain conditions). There are other aspects...stability, accuracy, bias and also your last point, discrimination assessing the effective resolution of the measurement system. These can all be assessed with proper sampling of the measurement system (EMP, MSE, MSA...whatever you call it) in the appropriate inference space (compared to the sources of variation you wish to distinguish).
5. What do you mean by "I've been going down the rabbit hole of MSA & EMP analysis/probably error"? What rabbit hole? EMP provides good guidance for evaluating measurement systems. I think one of the bigger challenges is to recognize that decisions about the adequacy of your measurement system depend on what sources of variation you want to measure. How your samples represent those sources in your study can have a huge effect on your conclusions.
"All models are wrong, some are useful" G.E.P. Box