With respect to your second question, this is an older post and Justin based it on FGPts, but I’ve found that his numbers hold for 5x5 as well:
In terms of SGP data, I’m not aware of it having been collected for the site. But the following are based on the average of four competitive 5x5 leagues that I was in 2019 for average 25th, median, and 75th percentiles as well as average min and max (I didn’t record 90th percentile):
BA: .261/.265/.270 [.254, .278]
HR: 279/319/345 (250, 366)
RBI: 928/998/1138 [820, 1138]
R: 968/1041/1105 [882, 1181]
SB: 97/112/133 [83, 165]
W: 61/87/100 [61, 110]
SV: 47/75/112 [31, 125]
K: 1318/1482/1661 [1113, 1725]
ERA: 4.23/3.87/3.66 [4.57, 3.35] (note: reversed order intentionally)
WHIP: 1.283/1.225/1.179 [1.340, 1.129]
Using those data, you can construct the following SGP denominators based on min and max:
BA: .0022 (1764/6650=.265)
HR: 10.57
RBI: 28.91
R: 27.25
SB: 7.43
W: 4.48
SV: 8.55
K: 55.61
ERA: 0.1111 (645/1500*9=3.87)
WHIP: 0.0192 (1838/1500=1.225)
Alternatively, you can base the SGP denominator on the difference between 3rd and 10th (i.e., the 25th and 75th percentiles):
BA: 0.0013 (1764/6650=.265)
HR: 9.39
RBI: 19.07
R: 19.57
SB: 5.11
W: 4.00
SV: 9.25
K: 48.93
ERA: 0.0814 (645/1500*9=3.87)
WHIP: 0.0148 (1838/1500=1.225)