Jon Solow
commited on
Commit
·
df0753c
1
Parent(s):
f1a728b
Add note regarding fractional scores calculated
Browse files
src/pages/13_Score_Settings.py
CHANGED
@@ -23,7 +23,6 @@ def get_page():
|
|
23 |
- The strategy that is most likely to win the total pool is if you can pick players from one team in the NFC and one team in the AFC who are in the Super Bowl (or all players from one team).
|
24 |
- Players on teams who have a bye in the Wildcard Round can be used in that round. They will earn 0 points in the first round, but will start with 2X points in the second week
|
25 |
- If you have a player on teams that lose, you can replace them with players who are still playing, but will start with 1X. Consider differentiating from the players you know other contestants picked.
|
26 |
-
|
27 |
"""
|
28 |
)
|
29 |
|
@@ -47,6 +46,9 @@ The prizes will be divided among the top scorers in each category as follows:
|
|
47 |
"""
|
48 |
)
|
49 |
|
|
|
|
|
|
|
50 |
for stat_type in ["Offense", "Kicking", "Defense / Special Teams"]:
|
51 |
st.header(stat_type)
|
52 |
for stat in STAT_TYPE_KEY_MAP[stat_type].values():
|
|
|
23 |
- The strategy that is most likely to win the total pool is if you can pick players from one team in the NFC and one team in the AFC who are in the Super Bowl (or all players from one team).
|
24 |
- Players on teams who have a bye in the Wildcard Round can be used in that round. They will earn 0 points in the first round, but will start with 2X points in the second week
|
25 |
- If you have a player on teams that lose, you can replace them with players who are still playing, but will start with 1X. Consider differentiating from the players you know other contestants picked.
|
|
|
26 |
"""
|
27 |
)
|
28 |
|
|
|
46 |
"""
|
47 |
)
|
48 |
|
49 |
+
st.header("Stat Values")
|
50 |
+
st.write("Note: Fractional scores are calculated and used for ranking, while the website shows the rounded value.")
|
51 |
+
|
52 |
for stat_type in ["Offense", "Kicking", "Defense / Special Teams"]:
|
53 |
st.header(stat_type)
|
54 |
for stat in STAT_TYPE_KEY_MAP[stat_type].values():
|