I assume we all feel activity declining for the last decade. I did the math.
Again without Classic league as it distorts the view.
Zooming in on more recent years.
Here's NNN league activity. Some data is inaccessible unfortunately. I have attained conflicting versions of data, so there are two plots.
These graphs as an attachment:
The script that made these graphs:
Data from https://www.tus-wa.com/leagues/seasons-info/ in TSV format:
tus.tsv
Again without Classic league as it distorts the view.
Zooming in on more recent years.
Here's NNN league activity. Some data is inaccessible unfortunately. I have attained conflicting versions of data, so there are two plots.
These graphs as an attachment:
The script that made these graphs:
Code Select
#!/usr/bin/env python3
from datetime import datetime as dt, timedelta
from functools import reduce
import re
def fmt_dt(s):
return dt.strptime(s, '%B %d, %Y, %H:%M:%S')
with open('tus.tsv', 'r') as f:
ll = [x.split('\t') for x in f.read().splitlines()]
R = {l[0]: [] for l in ll }
for l in ll:
start = fmt_dt(l[2])
end = fmt_dt(l[3])
g = sum([int(re.sub('[^\d]', '', s)) for s in l[4].split(', ')])
dur = (end-start).days+2
R[l[0]].append((start+(timedelta(days=dur/2)), g/dur, 2))
for k,v in R.items():
R[k].sort()
import matplotlib.pyplot as plt
mx_y = 0
for l,vv in R.items():
xs = [v[0] for v in vv]
ys = [v[1] for v in vv]
plt.plot(xs, ys, 'o-', label=l)
mx, mx_i = -1, -1
for i,(x,y) in enumerate(zip(xs, ys)):
if y > mx:
mx = y
mx_i = i
mx_y = max(mx, mx_y)
label = "{:.2f}".format(y)
plt.annotate(round(mx, 1),
(xs[mx_i],ys[mx_i]),
textcoords="offset points",
xytext=(0,5),
weight='bold',
color=plt.gca().lines[-1].get_color(),
ha='center')
plt.yticks(range(0, int(mx_y), 5))
xticks = sorted(list(set([a[0] for b in R.values() for a in b])))
xticks = (reduce(lambda acc, v: acc + [v] if len(acc) == 0 or (v-acc[-1]).days > 300 else acc, xticks, []))
plt.xticks(xticks, [d.strftime("%m/%y") for d in xticks])
plt.grid(True, linewidth=0.5, linestyle='-')
plt.ylabel('games')
plt.xlabel('season mid (month/year)')
plt.title('Average games a day per season')
plt.annotate('https://www.tus-wa.com/leagues/seasons-info/ (May 7, 2022)',
xy = (1.0, -0.1),
xycoords='axes fraction',
ha='right',
va="center",
fontsize=10)
plt.tight_layout()
plt.legend()
plt.show()
Data from https://www.tus-wa.com/leagues/seasons-info/ in TSV format:
tus.tsv
I don't have really evidences just this: