EXPLANATION OF DATA AND
PRESENTATION FORMATS

Running Tally of SEC
Predicted v. Actual Results

DATE OF
Game
Home Visitors Points Points Predicted Final Score Final Winning Pick Winner Spread on Home Road
GAME
Home Visitors Winner Home Visitor Spread Team Equals "1" Spread Win Win
50105
1
Arkansas Mississippi 72 63 9 Arkansas 69 46 23 Arkansas 1 14 1
50105
2
Georgia Tennessee 70 70 0 Tennessee 65 72 -7 Tennessee 1 -7 1
50105
3
Kentucky USC 66 65 1 Kentucky 79 75 4 Kentucky 1 3 1
50105
4
Miss. St Auburn 75 71 4 Miss. St 90 53 37 Miss. St 1 33 1
50105
5
Vanderbilt Alabama 75 74 0 Vanderbilt 70 56 14 Vanderbilt 1 14 1
50108
6
Alabama LSU 81 73 8 Alabama 73 58 15 Alabama 1 7 1
50108
7
Florida Arkansas 72 70 2 Florida 82 74 8 Florida 1 6 1
50108
8
Mississippi Miss. St 65 69 -3 Miss. St 76 87 -11 Miss. St 1 -8 1
50108
9
Tennessee Vanderbilt 69 73 -5 Vanderbilt 63 88 -25 Vanderbilt 1 -20 1
50108
10
USC Georgia 72 62 10 USC 74 54 20 USC 1 10 1
50111
11
Arkansas Alabama 75 73 2 Arkansas 61 64 -3 Alabama -5 1
50112
12
Auburn Florida 71 78 -7 Florida 78 84 -6 Florida 1 1 1
50112
13
Kentucky Vanderbilt 71 68 3 Kentucky 69 54 15 Kentucky 1 12 1
50112
14
LSU USC 67 74 -7 USC 79 64 15 LSU 22 1
50112
15
Mississippi Georgia 68 66 2 Mississippi 59 54 5 Mississippi 1 3 1
50112
16
Tennessee Miss. St 68 71 -3 Miss. St 64 63 1 Tennessee 4 1
50115
17
Auburn Mississippi 72 70 2 Auburn 72 79 -7 Mississippi -9 1
50115
18
Georgia Kentucky 64 72 -8 Kentucky 55 76 -21 Kentucky 1 -13 1
50115
19
Miss. St Arkansas 68 70 -2 Arkansas 80 55 25 Miss. St 27 1
50115
20
USC Tennessee 72 63 9 USC 66 63 3 USC 1 -6 1
50115
21
Vanderbilt Florida 71 72 -2 Florida 65 82 -17 Florida 1 -15 1
50118
22
Alabama Miss. St 75 72 3 Alabama 98 49 49 Alabama 1 46 1
50119
23
Florida Tennessee 76 66 10 Florida 76 83 -7 Tennessee -17 1
50119
24
LSU Arkansas 70 77 -7 Arkansas 66 63 3 LSU 10 1
50119
25
Mississippi Kentucky 62 70 -7 Kentucky 50 53 -3 Kentucky 1 4 1
50122
26
Arkansas Auburn 77 70 7 Arkansas 95 65 30 Arkansas 1 23 1
50122
27
Georgia Vanderbilt 67 73 -6 Vanderbilt 68 59 9 Georgia 15 1
50122
28
Kentucky LSU 76 67 9 Kentucky 89 58 31 Kentucky 1 22 1
50122
29
Miss. St USC 65 68 -3 USC 73 61 12 Miss. St 15 1
50122
30
Mississippi Alabama 68 74 -5 Alabama 58 66 -8 Alabama 1 -3 1
50125
31
Florida Georgia 76 65 11 Florida 70 47 23 Florida 1 12 1
50125
32
Tennessee Kentucky 65 72 -7 Kentucky 62 84 -22 Kentucky 1 -15 1
50126
33
Auburn Alabama 76 80 -4 Alabama 55 60 -5 Alabama 1 -1 1
50126
34
LSU Mississippi 71 70 1 LSU 70 60 10 LSU 1 9 1
50126
35
USC Vanderbilt 70 67 3 USC 68 63 5 USC 1 2 1
50130
36
Alabama Georgia 78 69 9 Alabama 75 47 28 Alabama 1 19 1
50129
37
Arkansas Kentucky 68.5 67.9 1 Arkansas 67 68 -1 Kentucky -2 1
50129
38
Auburn Tennessee 75 73 2 Auburn 62 59 3 Auburn 1 1 1
50129
39
Florida USC 69 67 2 Florida 80 72 8 Florida 1 6 1
50129
40
LSU Miss. St 71 74 -3 Miss. St 69 62 7 LSU 10 1
50129
41
Vanderbilt Mississippi 71 65 7 Vanderbilt 73 51 22 Vanderbilt 1 15 1
50201
42
Miss. St Florida 68 72 -4 Florida 71 57 14 Miss. St 18 1
50202
43
Georgia LSU 72.7 72.9 -0.2 LSU 79 95 -16 LSU 1 -16 1
50202
44
Mississippi Auburn 71.0 71.4 -0.4 Auburn 70 55 15 Mississippi 15 1
50202
45
USC Arkansas 68 66 1 USC 64 52 12 USC 1 11 1
50202
46
Vanderbilt Tennessee 74 68 7 Vanderbilt 67 62 5 Vanderbilt 1 -2 1
50205
47
Auburn Miss. St 72 74 -2 Miss. St 90 76 14 Auburn 16 1
50205
48
Florida Alabama 76 73 3 Florida 85 54 31 Florida 1 28 1
50205
49
Georgia USC 63 71 -8 USC 53 60 -7 USC 1 1 1
50205
50
Mississippi Arkansas 64 71 -7 Arkansas 65 66 -1 Arkansas 1 6 1
50205
51
Tennessee LSU 74 73 1 Tennessee 77 55 22 Tennessee 1 21 1
50205
52
Vanderbilt Kentucky 69 70 -1 Kentucky 70 84 -14 Kentucky 1 -13 1
50208
53
Kentucky Florida 69.3 68.9 0 Kentucky 69 66 3 Kentucky 1 3 1
50209
54
Arkansas Georgia 74 64 10 Arkansas 62 47 15 Arkansas 1 5 1
50209
55
LSU Auburn 77.0 77.4 0 Auburn 90 69 21 LSU 21 1
50209
56
Tennessee Alabama 71 76 -5 Alabama 54 72 -18 Alabama 1 -13 1
50212
57
Alabama Mississippi 75 67 7 Alabama 71 45 26 Alabama 1 19 1
50212
58
Arkansas LSU 78 69 9 Arkansas 65 62 3 Arkansas 1 -6 1
50212
59
Kentucky Georgia 73 63 10 Kentucky 60 51 9 Kentucky 1 -1 1
50212
60
Miss. St Vanderbilt 70 71 -1 Vanderbilt 60 54 6 Miss. St 7 1
50212
61
Tennessee Florida 67 75 -8 Florida 73 84 -11 Florida 1 -3 1
50212
62
USC Auburn 75 67 8 USC 71 74 -3 Auburn -11 1
50215
63
USC Kentucky 66 65 1 USC 73 61 12 USC 1 11 1
50216
64
Alabama Arkansas 73.6 73.7 0 Arkansas 72 63 9 Alabama 9 1
50216
65
Auburn Vanderbilt 73 77 -4 Vanderbilt 43 67 -24 Vanderbilt 1 -20 1
50216
66
Florida Mississippi 73 63 10 Florida 90 53 37 Florida 1 27 1
50216
67
Miss. St LSU 75 70 5 Miss. St 72 80 -8 LSU -13 1
50219
68
Alabama USC 71 71 -1 USC 87 68 19 Alabama 20 1
50219
69
Georgia Auburn 73 74 -2 Auburn 57 45 12 Georgia 14 1
50219
70
Kentucky Miss. St 70 65 5 Kentucky 94 78 16 Kentucky 1 11 1
50219
71
LSU Florida 70 78 -8 Florida 77 73 4 LSU 12 1
50219
72
Mississippi Tennessee 68 67 1 Mississippi 60 58 2 Mississippi 1 1 1
50219
73
Vanderbilt Arkansas 70 71 -1 Arkansas 79 65 14 Vanderbilt 15 1
50222
74
LSU Alabama 74 80 -6 Alabama 61 59 2 LSU 8 1
50223
75
Florida Vanderbilt 73 70 4 Florida 69 61 8 Florida 1 4 1
50223
76
Georgia Miss. St 67 71 -4 Miss. St 62 76 -14 Miss. St 1 -10 1
50223
77
Kentucky Auburn 76 68 8 Kentucky 81 73 8 Kentucky 1 0 1
50223
78
Tennessee USC 64 71 -7 USC 80 72 8 Tennessee 15 1
50226
79
Alabama Kentucky 72 73 -1 Kentucky 71 78 -7 Kentucky 1 -6 1
50226
80
Arkansas Tennessee 74 66 8 Arkansas 70 68 2 Arkansas 1 -6 1
50226
81
Auburn LSU 78 76 2 Auburn 64 77 -13 LSU -15 1
50226
82
Miss. St Mississippi 70 64 5 Miss. St 71 68 3 Miss. St 1 -2 1
50226
83
Vanderbilt Georgia 74 66 8 Vanderbilt 65 37 28 Vanderbilt 1 20 1
50227
84
USC Florida 68.1 67.7 0 USC 64 65 -1 Florida -1 1
50301
85
Arkansas Miss. St 71 67 5 Arkansas 55 57 -2 Miss. St -7 1
50302
86
Alabama Auburn 81 75 6 Alabama 94 53 41 Alabama 1 35 1
50302
87
Georgia Florida 66 75 -9 Florida 38 50 -12 Florida 1 -3 1
50302
88
Kentucky Tennessee 73 64 9 Kentucky 73 61 12 Kentucky 1 3 1
50302
89
Mississippi LSU 71 70 1 Mississippi 53 58 -5 LSU -6 1
50302
90
Vanderbilt USC 67 69 -1 USC 75 65 10 Vanderbilt 11 1
50305
91
Auburn Arkansas 71 76 -5 Arkansas 77 64 13 Auburn 18 1
50305
92
LSU Vanderbilt 72 77 -5 Vanderbilt 81 69 12 LSU 17 1
50305
93
Miss. St Alabama 73 74 -1 Alabama 63 66 -3 Alabama 1 -2 1
50305
94
Tennessee Georgia 71 69 2 Tennessee 78 68 10 Tennessee 1 8 1
50306
95
Florida Kentucky 70 68 2 Florida 53 52 1 Florida 1 -1 1
50306
96
USC Mississippi 69 60 9 USC 76 70 6 USC 1 -3 1
Home Road
Max
Max 80.9 79.8 10.9 98.0 95.0 49.0 49.0 Max 45.8 Wins Wins
Min
Min 62.4 60.4 -8.9 38.0 37.0 -25.0 1.0 Min -20.4 65 31
Mean
Mean 71.2 70.2 1.0 141 1/2 70.4 64.1 6.3 12.6 Mean 5.4 67.7% 32.3%
Std Dev
Std Dev 3.9 4.2 5.5 11.3 11.3 14.8 9.9 Std Dev 13.0
Mean, both ways
134 1/2
Std Dev
1 Number of Games to date: 96 96
Number of Winners Picked: 64 64
Percentage Picked Right: 66.7% 2.666667

 

My prediction methodology is based on average team performances for the season, prior to the first SEC Basketball game, and the teams' respective RPI Strength of Schedule prior to any SEC games.  Predictions have been tracked for almost 50 games since late in the 2004 season, and the winner has been successfully predicted over 76 percent of the time.   The average predicted score and actual scores are shown below together with the standard deviation.  In this table, the last three columns show the mean and standard deviation for the differences between the predicted and actual scores for the home and visiting team, and the mean and standard deviation of the predicted v. actual scoring margin.

 

Predicted Scores Actual Scores Number Point Differentials
Home Visitors Home Visitors of Games Home Visitor Line
72.6 67.3 Mean 73.0 65.1 0.5 0.3 2.4
8.7 7.0 Std Dev 12.0 11.9 56 9.1 10.3 13.3
8.3 70.0 12.5 69.0 9.7 (0.4)

 

    
    
      
    

Of course, the system seldom predicts the actual score but over a period of about 40 game predictions, the predicted and actual scores track remarkably well.  As the Point Differential data illustrates, the average difference between the home team's predicted and actual score for a game is less than 1 point, with a standard deviation of 9.2 points.  Similar results for the visiting team and the game margin.

Tennessee Tech is the fifth game of this season.  Kentucky's offensive and defensive efficiency for this season continue to emerge.  Click below to view graphical presentation of the data for the first three games played this season.  Companion Graphs for last season are also available so you can compare the progress of this season with last.

Click Here To View Graphs
Last Update: Nov 20, 2004
(Watch For Updates Throughout The Season)

There are four sets of graphs, each set showing data for the current season for all games played and data for last season.

Graph Set 1:  Average Offensive and Defensive Efficiency, both in terms of points per possession.  The distance between the offensive and defensive data is the average Net Game Efficiency [See Graph Set 2].  A second set of data is also included, the five game running average for offensive and defensive efficiency.  By comparing the slope of the average data and the position of the 5 game averages relative to the season average, one can assess the current state of play.

Graph Set 2:  Net Game Efficiency after each game of the current and past season.  This graph provides important information about the season.  Net Game Efficiency values above 0.25 ppp have correlated to NCAA final four quality seasons.  Values between 0.10 and 0.25 ppp indicate successful seasons, and probable post season play.  Values between -0.10 and 0.10 ppp are indicate of average teams.  This graph shows instantly how Kentucky is doing at any time during the season.

Graph Set 3:  The Power Rating is the ratio of a team's offensive and defensive efficiencies.  Each game has a unique power rating as well.  This bar graph shows the distribution of game power ratings.  Each bar represents a Power Rating Increment of 0.1, e.g. .8 to .89 is a single bar as is 1.10 to 1.19.  Notice for 2003-04 how the data forms a bell shaped distribution around its mean value.  The data for each season can be expressed in its statistical terms, a mean, standard deviation, etc.  Certainly, a season with an average power rating of 1.25 with a standard deviation of .20 is better than seasons having a mean of 1.10 with a standard deviation of 0.20 or a season having a mean of 125 and a standard deviation of 0.35.  Even after three games, a trend is emerging on this graph.  It appears that this Kentucky team will be more powerful than its predecessor.

Graph Set 4:  Another bar graph of game data.  This time it is concurrent plots for offensive [foreground] and defensive [background] efficiencies.  Just as the power forms a classic bell shape, so do each of these data sets.  The separation of the two sets is important to winning percentage.  The greater the separation, the higher the winning percentage. The separation is the Net Game Efficiency.  Looking at the difference in this manner provides some insight about why even the very good teams sometimes lose to weaker teams.  As this data shows, every team will experience variable performance, offensively and defensively, game to game.  These variations can be represented statistically just like the power data can, with means, etc.  However, unless the separation between the offensive and defensive data is so large [over the combined standard deviations] that there is no overlap of the two data set, there is always some probability that the better team will lose to the weaker team. The smaller the overlap, the less likely it is that the better team will lose.  The greater the overlap, the higher the percentage of games the team will lose.  When the data substantially overlap, the team will win and lose about the same number of games.

 

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Copyright 2005 Richard Cheeks
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