Fall 2019 Season Stats Print stats
3/29/2020 5:15 pm
Week: 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21
Week 2 Scores
Home TeamWinsVisiting TeamWins
J's All the Way8Loose Cannons21
Dragons11Hot Chocolate & the Marshmallows17
What had Happened Was15The Darby's14
Demolition Crew23T-N-T6
Okilly DokillyBYE

Team Standings as of Week 2
Division 1
TeamTotal WinsTotal LossesWin %Byes leftMake ups
Demolition Crew441180%30
Loose Cannons382164.4%30
What had Happened Was332556.9%30
Division 2
TeamTotal WinsTotal LossesWin %Byes leftMake ups
The Darby's292751.8%20
Dragons243441.4%20
Hot Chocolate & the Marshmallows223240.7%20
T-N-T174129.3%20
Okilly Dokilly121544.4%10
J's All the Way82127.6%10

Player Standings as of Week 2
Division 1
PlacePlayer Name12Total
TGPTotal Games Played (Singles and Doubles)
PPGAPersonal Points Per Game Average
Win %Singles Games Win %
Rating
1
Dave Bonham
60
37
97
19
5.11
70
1174
2
Mike Lagana
49
45
94
17
5.53
88.9
1203
3
Tom Conrad Jr.
41
40
81
18
4.5
80
1185
4
John Downes
27
39
66
20
3.3
63.6
1122
5
Chuck D
26
35
61
16
3.81
100
1211
6
Dre
25
22
47
18
2.61
88.9
1167
7
Alan Mathews
--
40
40
9
4.44
80
1137
8
Lee F
31
--
31
9
3.44
100
1135
171-180
  1. Dave Bonham - 180
High Out
  1. Chuck D - 122
High Mark Out6 Cork
9 Mark
  1. Mike Lagana - x2
  2. Dave Bonham

Division 2
PlacePlayer Name12Total
TGPTotal Games Played (Singles and Doubles)
PPGAPersonal Points Per Game Average
Win %Singles Games Win %
Rating
1
Greg O
24
26
50
20
2.5
41.7
1022
2
Kelli
25
22
47
19
2.47
36.4
1034
3
Mike Darby
23
19
42
19
2.21
60
1066
4
Jimmy O
18
23
41
18
2.28
50
1048
5
Mike Lantz
11
27
38
17
2.24
44.4
1017
6
Jeff Flannery
25
11
36
13
2.77
66.7
1093
7
Nick C
--
29
29
9
3.22
60
1078
7
Jeff B
29
--
29
10
2.9
50
1060
8
Que
25
--
25
10
2.5
40
1051
9
O'dell
18
--
18
9
2
80
1093
10
Mike Webster
--
11
11
7
1.57
40
1028
171-180High Out
High Mark Out
  1. Mike Lantz - 6
6 Cork
9 Mark
  1. Mike Lantz

Division 3
PlacePlayer Name12Total
TGPTotal Games Played (Singles and Doubles)
PPGAPersonal Points Per Game Average
Win %Singles Games Win %
Rating
1
Tie Die
25
19
44
22
2
50
1024
2
Mike Jones
19
14
33
18
1.83
44.4
1026
3
Erica Drake
11
18
29
19
1.53
60
1048
4
Oscar Ross
20
8
28
15
1.87
42.9
1002
5
Chris K
18
7
25
16
1.56
44.4
1015
6
Howard Laisure
8
16
24
20
1.2
36.4
987
7
Juliana O
9
13
22
20
1.1
50
1011
8
Scott Jay
--
14
14
10
1.4
20
977
9
John Moore
13
--
13
9
1.44
20
987
9
John Jay
--
13
13
7
1.86
0
1004
9
Dana W
--
13
13
10
1.3
40
1006
9
Charles Jay
--
13
13
10
1.3
20
975
10
Travis
11
--
11
8
1.38
50
1020
11
Eddie Jay
--
10
10
8
1.25
40
1005
12
Thornie P
9
--
9
8
1.13
100
1082
13
Larry Cox
5
--
5
10
0.5
20
973
14
Tammy Ryan
4
--
4
8
0.5
0
951
171-180High Out
High Mark Out6 Cork
9 Mark

Division 4
PlacePlayer Name12Total
TGPTotal Games Played (Singles and Doubles)
PPGAPersonal Points Per Game Average
Win %Singles Games Win %
Rating
1
Tammy V
12
5
17
19
0.89
36.4
955
2
Tina G
10
6
16
18
0.89
55.6
990
3
Donna L
6
9
15
15
1
22.2
931
4
Rick Johnson
--
10
10
10
1
33.3
991
5
Junior Johnson
5
1
6
15
0.4
0
887
6
John Brett
--
1
1
4
0.25
0
969
171-180High Out
  1. Rick Johnson - 116
High Mark Out
  1. Rick Johnson - 9
6 Cork
9 Mark

Show Player Rating Details
Before SQL: 05:15:47pm
After SQL: 05:15:47pm
Before Elo processing: 05:15:47pm
After Initial ratings: 05:15:47pm
After Elo processing: 05:15:47pm
Show how the rating calculated
How is the rating calculated:
  1. Base rating is set at 1000 (this is just so we don't have negative ratings)
  2. Personal Points per Game Average times 20 is added to the Base rating (this is done to get an initial spread in the ratings, 20 is considered the weight the Personal Points per Game Average is given in the ratings)
  3. For each singles game a player plays we calculate the points exchanged from the loser of the game to the winner of the game.
  4. We adjust the lower ranked players rating up 50 points per difference in rank (a rank 3 shooter will get 100 points on their rating when facing a rank 1 shooter, this is an attempt to take the handicap into account)
  5. Given the adjusted ratings we calculated expected win % as 1 / (1 + 10^(($playerBRating - $playerARating)/ 400)) In this equation 400 is double the points difference needed to give one player a 75% chance of beating the other.
  6. Finally we can calculate the points exchanged between players as K * (1-expectedWin%) Where K is the weight each game is given in the ratings. If there is a 50/50 chance either player could win there would be 16 points exchanged between the players.

The variables in these ratings come down to how much weight we put on the PPGA (20), the weight we give the handicap (50) and the weight we give each game (32). I am still seeing if these numbers make sense and might adjust them as we get more data.