A patient presents to KBCB with certain symptoms, and he will use the patient's history, symptoms, and other factors to form a differential diagnosis. But just because symptom X is indicative of disease Y, it doesn't mean he's found Y -- there can be MANY diseases that are indicated by symptom X*. So he orders further tests to either confirm or rule out his differential diagnosis.[*Also guided by heuristics, such as a symptom being more likely to be the result of an atypical presentation of a common disease than a typical presentation of a rare disease. Or as Sherlock Holmes put it, when you hear hoofsteps on the streets of London, you think horse, not zebra.]An MRI is one such test that may be indicated, and as I said above, it's a sophisticated process of data gathering, algorithmic analysis, and visualization that are then presented to him (or the radiologist) as the SME to interpret, and then it's also up to him as the SME to determine what to do about it.This really is not that much different from basketball analytics. We have a symptom -- say, we're loosing too many close games in the last minute. We make a differential diagnosis -- say, maybe we're launching the semipenultimate shot at the wrong time in two-for-one situations. We order a test -- let's say we analyze the raw SportsVU data for thousands of games looking for two-for-one situations, looking at the time the semipenultimate shot was launched. We then group this data by the specific time of this shot, and calculate the average net points that result. For fun we might even visualize this -- forming a graph which as it turns out is bell-shaped with a mean of around 30.5 seconds. (Or more realistically, we probably already have this available so we know what an optimal two-for-one SHOULD look like, just as KBCB already knows what a clear MRI should look like). So now we apply this knowledge to our patient (the basketball team) looking specifically at what they are doing in this situation with the best diagnostic tool at our disposal (the SportsVU data). The information goes to a SME, who notices that our team is launching its semipenultimate shots roughly three seconds later than optimal, with an average loss of 1.2 net points, which for this team would translate to three additional losses over the course of a season.So now we order an intervention, which in the case of the basketball team would be working with the coaching staff to understand the situation and show how it can be improved. The coaching staff devises drills to simulate these situations and get the team used to launching these shots a little sooner. Over time, this becomes second nature, repeated analytics of post-intervention play shows that the team is now launching its semipenultimate shot at an average of 30.1 seconds, and the team has seen a net gain of 1.1 points in these situations. Finally, the analytics guy gets a raise.