Are you thinking to integrate such measure or do you think it wouldnt be very useful?
It is not on our short-term to-do list. Part of the reason for that is we don’t collect this data (although it probably wouldn’t be that hard to get it). But I also don’t think it will be super useful. Accurately assessing overall putting skill requires many rounds of data. Estimating (presumably small) differences in skill for a golfer on different putting surfaces will require even more data to say anything meaningful. For example, if a golfer is truly 0.3 strokes/round better on one surface than another (which would be a large effect, in my opinion) it might take 50 rounds or more on each surface before we can confidently detect that. We also have the additional complication that golfers’ skill levels are likely changing over time, which needs to be controlled for.
The bottom line is that I think the signal / noise ratio is too low with this type of putting data to be of much use. However, combining the data with intuition could help (e.g. if a guy grows up playing on surface X and has above-average stats on surface X, it’s more likely that there’s something going on).
Do you know of any publicly available or scrapable data that has the grass type by course/year?
- Fantasy National had some data on this not sure in which format it is scrapable though
- Future Of Fantasy/Josh Culp used to compile that data publicly but it is now behind a firewall at NumbersFire I think? Maybe you could contact him on Twitter to ask about it