The Home Court Advantage in Contemporary College Basketball (1998-2001)

Thomas H. Giedgowd

Duke University

With thirty-five seconds left on the clock, the opposing team inbounds the basketball. The college basketball game was intense; the score was tied, the players were exhausted, and the crowd was sitting on the edges of their seats. The freshman point guard nervously dribbles the basketball up the court to the deafening chants of "defense, defense" by the home team’s crowd. As the clock ticks down, the point guard struggles to find another player to pass the ball to and mistakenly dribbles the ball off of his foot and out of bounds. The home team inbounds the basketball, passes it around, and makes a shot to win the game. The crowd erupts and the home team celebrates on the court. The opposing team walks skulkingly off of the court.

Many theories and analyses have been written on the causes and effects of the home court advantage in sporting events. These papers offer a range of theories about the causes of the phenomenon, usually citing such factors as the heightened aggression of the home team (Schwartz and Barsky 1977), psychological influence of a crowd (Whyte 1943), or familiarity of the players with the playing field (Schwartz and Barsky 1977). The true causes of the home court advantage phenomenon in any sport are not fully known. Understanding the causes and effects of the home court advantage is an important deed, and can also prove very lucrative within many commercial areas of team sports. The placement of bleachers/seats when building stadiums, organizing team schedules, choosing "neutral" playing fields, and sports gaming are all greatly affected by, or affect a teams home court advantage.

My study of the home court advantage within college basketball attempts to unearth a new cause that was never previously studied before; the strength of the home schedule compared to the strength of the away schedule. Although this variable seems like a common sense cause of the home court advantage, no major study has explored this variable in depth before. Before diving into the data, methods and results of my study, previous theories and studies on the home court advantage are presented and analyzed. After reviewing previous contributions, my theories are presented and tested. Within the study section the home court advantage (HCA) variable for each college team is computed for the specific year, and regression analysis is used to correlate other variables with the HCA.

Previous Contributions and Insights to the Home Court Advantage in College Basketball

Crowd Influence

A topic closely associated with the study of the home court advantage is the effect that spectators and a friendly crowd has upon team performance. Although the crowd influence is a large part of the home court advantage, it doesn’t account for everything. In Duke Men’s Basketball coach Mike Krzyzewski’s book Leading With the Heart he gives praise to the Cameron Crazies (the students that attend the basketball games) for their performance and influence over the games: "In truth, the students are part of our team. They are our sixth man. When they arrive at the games, many have painted their faces, designed humorous signs, created chants that echo throughout the arena during a game. They call themselves the Cameron Crazies … One year, I told them that one of our defensive goals for the game would be to force the ball along the sidelines, and that whenever our opponents picked up the dribble in those situations, I wanted our players to yell, "Ball! Ball! Well, the next day, before the game actually started, I walked out onto the court to say hello to small groups of students who were waiting in their seats-and we briefly discussed what the assignment was again. And sure enough, during the game, we forced a few of those situations and it wasn’t just the players on the court who were yelling, ‘Ball! Ball!’ It was the entire student body. We won that game, and as I walked off the court, I pointed to the students and kept mouthing the words, ‘You did this. You did this.’"

Probably the most famous and influential study of crowd influence was done by William Foote Whyte in his book Street Corner Society. His book, written about gang bowling in the 1950’s took an analytical approach to the influences of a crowd upon competition. While bowling, if a certain member of the group were either bowling above or below their set status in the group, then verbal taunts or critiques would bring their performance into accordance with how they normally preformed. This study of crowd effects on performance is a universal one. The crowd effect on the home court advantage serves two purposes. It discourages the opposing team and promotes the play of the home team.

Another study of team performance was done by Barry Schwartz and Stephen Barsky. Their study, conducted over a 15 year period (1952-1966) closely analyzed the quality of play of Big Five college basketball teams when they played at home. Schwartz and Barsky had several findings that were surprising. While playing in front of a home crowd, they found that home teams take more shots and score more field goals and points then they do playing in front of a hostile crowd. They also found that there were no important differences with regard to assists, teamwork, personal fouls, or scores as a percentage of shots, the Big Five teams had a distinct advantage when it came to rebounding on their home courts. A study conducted by Phillip E. Varca done on the home crowd advantage in basketball also found that home teams play more aggressively at home, and exhibit more aggressive tendencies when playing in front of a friendly crowd. After studying SEC college basketball teams for the 1977-1978 season, Varca drew these conclusions about team performance in front of a home crowd: home teams grab more rebounds (37.5 home – 34.4 away), have more blocked shots (2.8 home – 2.3 away), and have more steals (6.6 home – 5.3 away). Each of these statistics, indicating heightened aggression, are more pronounced when playing in front of a friendly crowd.

Schwartz and Barsky also had some more unusual findings. The home court advantage was greater when the conditions of play are most uniform. In basketball and hockey (when the surfaces and courts are closely regulated) the home court advantage was the greatest. In sports such as football and baseball (where the fields vary due to Astroturf, domes, stadium size, etc) the home court advantage is least pronounced.

Within Mark Mizruchi’s "Local Sports Teams and the Celebration of Community" he formulates and tests several hypothesis about the causes of the home court advantage. Within my study I attempt to re-create several of his findings, while testing some other hypothesis of my own.

Data and Methods

Within my study, I focused on men’s division I basketball teams. I chose the top twenty teams from the 2000-2001 Season, the middle twenty teams (151-170), and the lowest ranked twenty teams (301-319). The reasoning behind this choice was to prove that the home court advantage was not peculiar to one particular group of teams within a division. After gathering data from the 2000-2001 season, I stuck with the same 60 teams, and gathered data from the 1999-2000 and 1998-1999 men’s college basketball seasons to further test my hypotheses. During the 1998-1999 seasons, Albany NY, High Point, and Sacred Heart were not included within the Division I basketball statistics, and were therefore omitted from the study in the 1998-1999 season.

The average home court advantage of all of the teams for 2000-2001 was 26.67%. This was the average of all teams Home Winning Percentage – Away Winning Percentage. For the 1999-2000 seasons, the average HCA was 29.37% and the 1998-1999 season had a 28.19% HCA. Tabular representations are shown below.

2000-2001 HCA Calculations: Avg. HCA: 26.67%
 
School Name
Ranking
Home Games Won
Home Games Played
Home Winning Percent
Away Games Won
Away Games Played
Away Winning Percentage
HCA factor (Home Winning Percent - Away Winning Percent)
Duke
1
14
16
88%
9
10
90%
-3%
Stanford
2
10
12
83%
11
11
100%
-17%
Arizona
3
13
15
87%
7
11
64%
23%
Michigan St
4
14
14
100%
6
9
67%
33%
Illinois
5
13
13
100%
6
11
55%
45%
North Carolina
6
10
12
83%
8
11
73%
11%
Maryland
7
11
14
79%
6
9
67%
12%
Kentucky
8
11
12
92%
6
11
55%
37%
Boston College
9
16
16
100%
6
10
60%
40%
Florida
10
13
15
87%
8
11
73%
14%
UCLA
11
12
15
80%
8
11
73%
7%
Kansas
12
11
12
92%
7
11
64%
28%
Mississippi
13
14
15
93%
6
10
60%
33%
USC
14
12
15
80%
6
11
55%
25%
Oklahoma
15
11
12
92%
5
10
50%
42%
Iowa St
16
13
13
100%
6
10
60%
40%
Texas
17
16
17
94%
6
11
55%
40%
Temple
18
9
14
64%
8
14
57%
7%
Virginia
19
14
15
93%
5
11
45%
48%
Indiana
20
12
14
86%
4
10
40%
46%
Troy St
151
8
11
73%
6
13
46%
27%
Long Beach St
152
8
12
67%
4
11
36%
30%
SW Missouri St
153
8
12
67%
2
12
17%
50%
Princeton
154
8
9
89%
5
13
38%
50%
Maine
155
9
11
82%
7
15
47%
35%
Louisiana Tech
156
8
11
73%
7
15
47%
26%
Chattanooga
157
8
10
80%
3
12
25%
55%
New Mexico State
158
6
12
50%
7
14
50%
0%
Evansville
159
10
14
71%
3
12
25%
46%
East Tenn St
160
8
10
80%
7
14
50%
30%
Marist
161
12
13
92%
3
13
23%
69%
Washington
162
5
15
33%
3
12
25%
8%
Old Dominion
163
8
12
67%
3
14
21%
45%
Arkansas LR
164
7
10
70%
6
13
46%
24%
Youngstown St
165
8
10
80%
6
12
50%
30%
Niagara
166
7
12
58%
8
14
57%
1%
Manhattan
167
9
12
75%
5
13
38%
37%
Navy
168
7
10
70%
8
16
50%
20%
Wisc Green Bay
169
6
13
46%
3
12
25%
21%
Texas A&M
170
6
12
50%
1
11
9%
41%
Cornell
301
3
11
27%
3
12
25%
2%
Robert Morris
302
5
11
45%
2
17
12%
34%
Southern
303
7
12
58%
2
11
18%
40%
Middle Tenn St
304
3
13
23%
1
13
8%
15%
Hartford
305
2
11
18%
1
12
8%
10%
Eastern Mich
306
3
14
21%
0
13
0%
21%
Mt St Marys
307
5
12
42%
2
14
14%
27%
Sacred Heart
308
5
12
42%
2
15
13%
28%
Grambling
309
5
9
56%
3
16
19%
37%
North Texas
310
1
10
10%
1
13
8%
2%
Florida A&M
311
3
11
27%
0
13
0%
27%
Jackson St
312
4
10
40%
3
15
20%
20%
High Point
313
4
10
40%
0
15
0%
40%
Quinnipiac
314
3
11
27%
1
13
8%
20%
Albany NY
315
4
14
29%
1
12
8%
20%
St Marys CA
316
1
12
8%
0
14
0%
8%
Texas Southern
317
4
10
40%
3
16
19%
21%
Prairie View
318
4
11
36%
1
15
7%
30%
Ark Pine Bluff
319
1
9
11%
0
17
0%
11%

1999-2000 HCA Calculations: Avg. HCA: 29.37%
 
School Name
Ranking
Home Games Won
Home Games Played
Home Winning Percent
Away Games Won
Away Games Played
Away Winning Percentage
HCA factor (Home Winning Percent - Away Winning Percent)
Michigan St
1
14
14
100%
7
13
54%
46%
Duke
3
13
15
87%
10
10
100%
-13%
Iowa St
4
16
16
100%
6
9
67%
33%
Stanford
5
11
13
85%
10
11
91%
-6%
Florida
6
15
17
88%
6
10
60%
28%
Temple
7
13
13
100%
9
13
69%
31%
Arizona
10
17
18
94%
7
11
64%
31%
Oklahoma
12
15
17
88%
6
9
67%
22%
Texas
13
13
14
93%
6
12
50%
43%
Kentucky
18
13
13
100%
5
10
50%
50%
Illinois
19
13
15
87%
5
9
56%
31%
Indiana
20
12
14
86%
5
10
50%
36%
Kansas
24
13
14
93%
5
11
45%
47%
Maryland
26
16
17
94%
4
9
44%
50%
North Carolina
27
9
14
64%
6
11
55%
10%
UCLA
29
12
16
75%
5
11
45%
30%
Virginia
53
11
13
85%
5
12
42%
43%
SW Missouri St
57
12
14
86%
6
12
50%
36%
Long Beach St
58
11
12
92%
10
11
91%
1%
USC
60
10
13
77%
3
11
27%
50%
New Mexico State
75
12
14
86%
7
13
54%
32%
Mississippi
84
12
15
80%
1
10
10%
70%
Louisiana Tech
106
10
11
91%
10
17
59%
32%
Eastern Mich
113
6
10
60%
6
14
43%
17%
Evansville
120
12
15
80%
3
10
30%
50%
Princeton
130
10
12
83%
7
12
58%
25%
Navy
141
13
15
87%
7
10
70%
17%
Washington
146
4
13
31%
5
14
36%
-5%
Boston College
151
7
15
47%
1
10
10%
37%
Wisc Green Bay
154
10
12
83%
2
13
15%
68%
Maine
155
10
11
91%
8
11
73%
18%
Middle Tenn St
166
8
12
67%
5
14
36%
31%
Niagara
183
10
12
83%
6
15
40%
43%
Robert Morris
185
8
11
73%
7
14
50%
23%
Texas A&M
203
5
12
42%
0
12
0%
42%
Troy St
204
10
12
83%
5
13
38%
45%
Old Dominion
207
8
13
62%
3
14
21%
40%
Marist
208
8
12
67%
6
14
43%
24%
East Tenn St
216
6
11
55%
5
14
36%
19%
Quinnipiac
217
9
12
75%
7
14
50%
25%
Youngstown St
223
5
10
50%
5
13
38%
12%
Manhattan
229
7
11
64%
4
12
33%
30%
Chattanooga
237
6
12
50%
2
11
18%
32%
St Marys CA
239
6
12
50%
1
15
7%
43%
Jackson St
241
7
11
64%
5
15
33%
30%
North Texas
246
5
12
42%
1
13
8%
34%
Southern
250
8
9
89%
6
14
43%
46%
Texas Southern
266
4
8
50%
6
12
50%
0%
Mt St Marys
276
5
10
50%
4
15
27%
23%
High Point
279
5
8
63%
1
14
7%
55%
Hartford
285
6
13
46%
3
14
21%
25%
Albany NY
288
3
7
43%
4
16
25%
18%
Cornell
297
4
11
36%
4
12
33%
3%
Arkansas LR
299
4
14
29%
0
13
0%
29%
Florida A&M
303
5
10
50%
3
13
23%
27%
Prairie View
308
3
8
38%
2
15
13%
24%
Ark Pine Bluff
313
3
9
33%
1
14
7%
26%
Sacred Heart
314
3
11
27%
0
14
0%
27%
Grambling
318
0
9
0%
0
15
0%
0%

 
 
 
 
 

1998-1999 HCA Calculations: Avg. HCA: 28.19%
 
School Name
Ranking
Home Games Won
Home Games Played
Home Winning Percent
Away Games Won
Away Games Played
Away Winning Percentage
HCA factor (Home Winning Percent - Away Winning Percent)
Duke
1
14
14
100%
11
11
100%
0%
Michigan St
3
14
14
100%
8
11
73%
27%
Maryland
5
16
17
94%
6
9
67%
27%
Kentucky
7
12
13
92%
5
10
50%
42%
Stanford
9
11
13
85%
10
13
77%
8%
North Carolina
15
13
16
81%
7
12
58%
23%
Temple
16
11
12
92%
6
13
46%
46%
Arizona
17
15
15
100%
5
11
45%
55%
Indiana
19
15
18
83%
5
9
56%
28%
UCLA
20
16
17
94%
5
10
50%
44%
Florida
21
15
16
94%
4
10
40%
54%
Kansas
27
10
13
77%
6
11
55%
22%
SW Missouri St
29
12
15
80%
7
13
54%
26%
Washington
34
12
13
92%
2
11
18%
74%
Mississippi
38
10
13
77%
3
10
30%
47%
Oklahoma
42
11
14
79%
6
12
50%
29%
Illinois
48
6
14
43%
4
11
36%
6%
Texas
51
8
13
62%
9
14
64%
-3%
Evansville
56
9
12
75%
9
13
69%
6%
USC
62
11
16
69%
4
12
33%
35%
Princeton
78
8
10
80%
9
14
64%
16%
Virginia
86
9
15
60%
3
10
30%
30%
New Mexico State
92
10
11
91%
7
13
54%
37%
Old Dominion
109
12
14
86%
7
13
54%
32%
Wisc Green Bay
110
11
13
85%
5
11
45%
39%
Iowa St
111
11
14
79%
1
10
10%
69%
Louisiana Tech
112
9
9
100%
6
13
46%
54%
Navy
142
10
12
83%
6
10
60%
23%
Texas A&M
152
9
14
64%
3
12
25%
39%
Maine
153
8
10
80%
8
14
57%
23%
Niagara
158
10
10
100%
5
14
36%
64%
Youngstown St
178
6
9
67%
5
11
45%
21%
St Marys CA
179
6
11
55%
3
12
25%
30%
Chattanooga
182
8
12
67%
5
12
42%
25%
Marist
183
10
14
71%
5
12
42%
30%
Southern
184
10
10
100%
6
11
55%
45%
Long Beach St
186
6
12
50%
5
13
38%
12%
East Tenn St
190
7
11
64%
6
12
50%
14%
Boston College
191
5
14
36%
0
10
0%
36%
Eastern Mich
194
2
11
18%
3
12
25%
-7%
Arkansas LR
207
7
10
70%
2
12
17%
53%
Robert Morris
227
9
12
75%
5
13
38%
37%
Mt St Marys
228
7
13
54%
4
13
31%
23%
Jackson St
229
6
8
75%
6
15
40%
35%
Middle Tenn St
235
7
15
47%
3
12
25%
22%
Hartford
245
7
13
54%
4
12
33%
21%
Cornell
250
4
11
36%
5
12
42%
-5%
North Texas
252
3
10
30%
1
15
7%
23%
Florida A&M
273
5
9
56%
3
14
21%
34%
Manhattan
274
3
12
25%
2
14
14%
11%
Troy St
277
4
9
44%
3
11
27%
17%
Quinnipiac
288
4
11
36%
4
15
27%
10%
Texas Southern
298
4
8
50%
2
13
15%
35%
Grambling
300
3
9
33%
2
11
18%
15%
Prairie View
307
2
8
25%
2
14
14%
11%
Ark Pine Bluff
310
1
9
11%
0
14
0%
11%

Looking at these statistics, it greatly surprised me that almost every basketball team had a positive HCA for all three years. Those teams that did end up having a negative HCA did not have a very great disparity between their home and away winning percentages (-17% was the greatest amount of difference by Stanford in 2000-2001). Teams such as Duke and Stanford (who ended up having negative HCA’s for the 2000-2001 and 1999-2000 seasons) can attribute their negative HCA to the fact that they won such a high percentage of their games, and just happened to lose 1 or 2 more games at home than away).

Easier schedules

After acknowledging the fact that college basketball teams win a greater percentage of home games than they win on the road, I formulated a few hypotheses as to why this fact occurs. My first hypothesis was very simple. Do college basketball teams simply play a greater percentage of easy teams at home, and play their tougher games on the road? In order to investigate this, I went through each team’s schedule and analyzed the strength of the teams that they played. I broke their schedules up into home and away games. Within the home and away categories, I separated the teams that they played into five different categories by strength (ranking) of the team. I gave the teams ranked 1-25 a weighting of 5, 26-50 a weighting of 4, 51-100 a weighting of 3, 101-200 a weighting of 2, and 201-319 a weighting of 1. I took each team's percentage of games within the divisions (1-25 for example) and multiplied it by their applicable weighting. I added up all of the weightings for home and away schedules, and then subtracted the Strength of the Away Schedule from the Strength of the Home Schedule. If the end result was positive, then that meant that the team’s schedule was tougher away then it was at home. My findings were surprising. I found that an overwhelming majority of the teams that I analyzed had easier home schedules than away schedules. The average for the 2000-2001 season was .3156. The value of the number is almost meaningless, but the fact that it was a significant positive number (when compared to the individual results that each team had) show that on average, home games are played against easier teams that away games. The method that I used does have a minor flaw: it is not very accurate for the lowest twenty teams that I studied. The lowest twenty teams played a majority of their games against other low ranking teams, and would not have a chance to fully use the weightings of playing tougher ranking teams (i.e. the 5 weighting of 1-25 ranked teams). Below is a tabular representation of my findings for each of the three seasons.
 
 

2000-2001 Schedule Strength Calculations: Avg. Sched. Strength: +.315604
 
School Name
1-25 Home Games
26-50 Home Games
51-100 Home Games
101-200 Home Games
201-319 Home Games
1-25 Away Games
26-50 Away Games
51-100 Away Games
101-200 Away Games
201-319 Away Games
Strength Away - Strength Home
Albany NY
0
0
0
1
13
0
3
0
1
8
0.762
Arizona
4
4
2
4
1
4
1
3
3
0
0.145
Ark Pine Bluff
0
0
0
1
8
1
1
4
2
9
0.889
Arkansas LR
0
0
1
6
3
0
0
4
4
5
0.123
Boston College
0
2
5
4
5
1
2
6
0
1
0.950
Chattanooga
0
0
0
4
6
0
1
1
5
5
0.433
Cornell
0
0
0
2
9
0
0
0
1
11
-0.098
Duke
6
1
2
4
3
5
1
2
2
0
0.713
East Tenn St
0
0
0
3
7
0
1
1
5
7
0.414
Eastern Mich
0
0
3
6
5
0
0
4
6
3
0.220
Evansville
0
2
3
5
4
0
1
2
7
2
-0.048
Florida
2
4
2
2
5
2
3
3
2
1
0.539
Florida A&M
0
0
0
3
8
1
0
2
2
8
0.497
Grambling
0
0
0
0
9
0
0
0
0
1
0.000
Hartford
0
1
0
5
5
0
1
1
4
6
0.023
High Point
0
0
0
3
7
1
0
1
4
9
0.367
Illinois
4
2
2
4
1
4
2
2
3
0
0.329
Indiana
4
3
2
4
1
3
3
3
1
0
0.443
Iowa St
2
1
3
5
2
2
2
3
2
1
0.508
Jackson St
0
0
0
1
9
0
2
1
2
10
0.567
Kansas
2
2
4
3
1
3
2
3
3
0
0.371
Kentucky
2
4
3
1
2
4
4
2
1
0
0.750
Long Beach St
1
2
1
4
4
1
1
2
3
4
-0.061
Louisiana Tech
0
0
1
4
6
0
1
2
7
5
0.388
Maine
0
1
0
2
8
1
2
0
3
9
0.412
Manhattan
0
0
0
8
4
0
1
1
8
3
0.333
Marist
0
0
0
8
5
1
0
2
7
3
0.538
Maryland
5
1
1
2
5
4
1
1
2
1
0.627
Michigan St
6
2
1
5
0
4
1
1
2
1
-0.087
Middle Tenn St
0
1
1
5
6
1
0
1
8
3
0.308
Mississippi
2
5
1
3
4
1
3
4
2
0
0.433
Mt St Marys
0
0
0
2
10
0
0
0
2
12
-0.024
Navy
0
0
1
2
7
2
0
1
1
12
0.288
New Mexico State
0
0
3
5
4
0
0
3
7
4
0.012
Niagra
0
0
1
7
4
0
1
2
7
4
0.250
North Carolina
5
1
3
2
1
6
1
1
2
1
0.235
North Texas
0
0
2
6
2
1
2
1
6
3
0.385
Oklahoma
2
1
4
2
3
4
1
2
3
0
0.850
Old Dominion
0
0
2
7
3
1
0
2
8
3
0.226
Prairie View
0
0
0
1
10
0
2
1
2
10
0.576
Princeton
0
1
0
1
7
2
0
1
2
8
0.479
Quinnipiac
0
0
0
1
10
1
0
1
1
10
0.448
Robert Morris
0
0
0
2
9
0
1
2
4
10
0.465
Sacred Heart
0
0
0
3
9
1
1
0
2
11
0.350
Southern
0
0
0
1
11
0
0
0
1
10
0.008
St Marys CA
0
2
3
5
2
2
3
1
4
4
0.226
Stanford
3
2
3
3
1
3
1
3
4
0
0.023
SW Missouri St
0
2
2
6
2
0
1
3
6
2
-0.083
Temple
4
0
4
5
1
2
1
4
6
1
-0.286
Texas
3
2
4
4
4
3
0
5
3
0
0.508
Texas A&M
3
1
2
2
4
3
0
4
4
0
0.432
Texas Southern
0
0
0
0
10
2
0
1
3
10
0.813
Troy St
0
1
0
2
8
1
2
0
1
9
0.392
UCLA
4
1
6
4
0
3
1
3
4
0
-0.061
USC
3
2
3
6
1
3
1
2
5
0
0.182
Virginia
4
2
3
2
4
4
1
1
2
3
0.091
Washington
4
1
5
4
1
4
2
2
2
2
0.133
Wisc Green Bay
1
2
2
7
1
0
3
1
5
3
-0.282
Youngstown St
0
0
3
2
5
1
0
3
2
6
0.200

1999-2000 Schedule Strength Calculations: Avg. Sched. Strength: +.387543
 
School Name
1-25 Home Games
26-50 Home Games
51-100 Home Games
101-200 Home Games
201-319 Home Games
1-25 Away Games
26-50 Away Games
51-100 Away Games
101-200 Away Games
201-319 Away Games
Strength Away - Strength Home
Albany NY
0
0
0
1
6
1
0
1
4
10
0.482
Arizona
2
3
4
7
2
3
3
2
2
1
0.677
Ark Pine Bluff
0
0
0
0
9
1
1
1
3
8
0.857
Arkansas LR
1
1
1
5
6
1
1
1
7
3
0.231
Boston College
2
1
4
4
4
2
3
3
1
1
0.867
Chattanooga
0
0
1
6
5
0
0
1
6
4
0.061
Cornell
0
0
1
1
9
0
1
1
3
7
0.394
Duke
1
3
3
4
4
1
2
4
3
0
0.567
East Tenn St
0
0
0
7
4
0
1
1
6
6
0.149
Eastern Mich
0
2
3
3
2
1
3
3
3
4
0.071
Evansville
0
0
4
7
4
0
0
5
5
0
0.500
Florida
4
2
1
5
5
2
3
2
3
0
0.694
Florida A&M
0
0
0
0
10
2
0
0
1
10
0.692
Grambling
0
0
0
1
8
1
0
2
1
11
0.489
Hartford
0
0
1
3
9
1
1
1
4
7
0.544
High Point
0
0
0
2
6
1
2
1
3
7
0.821
Illinois
5
1
3
2
4
3
1
3
1
1
0.378
Indiana
4
1
6
0
3
4
1
3
1
1
0.386
Iowa St
3
2
1
7
3
2
1
1
5
0
0.313
Jackson St
0
1
0
2
8
0
1
2
3
10
0.170
Kansas
3
3
2
6
0
4
2
1
3
1
0.240
Kentucky
3
4
3
2
1
3
4
1
2
0
0.338
Long Beach St
0
1
3
2
6
0
1
0
5
5
-0.189
Louisiana Tech
0
0
1
4
6
0
1
2
6
7
0.267
Maine
0
0
1
1
9
0
0
2
1
8
0.182
Manhattan
0
0
0
5
6
0
0
0
5
7
-0.038
Marist
0
0
0
6
6
0
0
1
6
7
0.071
Maryland
2
2
5
6
2
2
1
3
3
0
0.458
Michigan St
5
0
4
2
3
7
2
2
1
1
0.857
Middle Tenn St
1
0
2
3
6
1
0
3
4
6
0.083
Mississippi
2
3
2
4
4
4
2
0
3
1
0.833
Mt St Marys
0
0
0
3
7
1
0
3
5
6
0.700
Navy
0
0
1
3
11
0
0
1
2
7
0.067
New Mexico State
0
1
1
8
4
1
1
3
4
4
0.379
Niagra
1
0
0
3
8
1
1
0
3
10
0.083
North Carolina
2
3
3
5
1
1
3
3
3
1
0.000
North Texas
1
1
2
4
4
1
1
3
6
2
0.212
Oklahoma
4
1
2
7
3
3
1
1
3
1
0.458
Old Dominion
0
0
0
7
6
0
1
1
7
5
0.319
Prairie View
0
0
0
0
8
0
0
2
5
8
0.600
Princeton
0
0
1
3
8
2
0
2
2
6
0.750
Quinnipiac
0
0
0
3
9
0
2
0
4
8
0.464
Robert Morris
0
0
0
2
9
0
0
2
4
8
0.390
Sacred Heart
0
0
0
4
7
2
0
0
3
9
0.422
Southern
0
0
0
0
9
0
0
0
2
12
0.143
St Marys CA
1
1
3
2
5
2
1
5
5
2
0.483
Stanford
1
3
2
3
4
1
3
2
4
1
0.371
SW Missouri St
0
1
4
7
2
1
0
3
8
0
0.214
Temple
0
2
6
3
2
2
1
3
6
1
0.154
Texas
4
0
3
6
1
5
2
1
3
1
0.583
Texas A&M
4
0
1
4
3
4
1
3
3
1
0.500
Texas Southern
0
0
0
0
8
0
1
1
1
9
0.500
Troy St
0
0
0
4
8
0
0
1
4
8
0.128
UCLA
4
4
2
4
2
3
3
2
2
1
0.205
USC
2
3
2
4
2
2
4
2
2
1
0.441
Virginia
1
2
2
3
5
2
2
3
4
1
0.692
Washington
4
3
2
3
1
2
3
3
3
3
-0.604
Wisc Green Bay
0
1
2
8
1
1
1
2
8
1
0.212
Youngstown St
0
0
1
5
4
1
1
0
6
5
0.300

1998-1999 Schedule Strength Calculations: Avg. Sched. Strength: +.289333
 
School Name
1-25 Home Games
26-50 Home Games
51-100 Home Games
101-200 Home Games
201-319 Home Games
1-25 Away Games
26-50 Away Games
51-100 Away Games
101-200 Away Games
201-319 Away Games
Strength Away - Strength Home
Arizona
2
3
5
3
2
2
3
2
2
0
0.556
Ark Pine Bluff
0
0
0
2
7
0
2
3
3
6
0.849
Arkansas LR
0
0
0
8
2
0
1
0
8
3
0.117
Boston College
3
1
2
5
3
2
3
3
2
0
0.786
Chattanooga
0
1
0
6
5
1
1
0
2
8
0.000
Cornell
0
0
2
3
6
0
0
3
1
8
-0.053
Duke
3
1
6
1
3
3
1
6
1
0
0.545
East Tenn St
1
1
0
2
7
0
1
1
4
6
-0.068
Eastern Mich
1
0
7
3
0
2
1
4
3
2
-0.076
Evansville
0
1
5
4
1
0
2
4
4
3
-0.161
Florida
2
2
4
1
7
4
0
4
2
0
1.163
Florida A&M
0
0
0
0
9
1
0
1
1
11
0.500
Grambling
0
0
0
2
7
0
0
2
2
7
0.323
Hartford
0
0
2
3
8
0
0
2
4
6
0.128
Illinois
6
2
3
1
2
6
2
2
0
1
0.448
Indiana
6
1
7
4
0
4
2
2
1
0
0.500
Iowa St
0
3
3
5
3
1
3
3
3
0
0.771
Jackson St
0
0
0
2
6
0
3
0
6
6
0.750
Kansas
2
3
5
3
0
0
2
4
4
1
-0.671
Kentucky
5
0
3
2
3
2
3
4
1
0
0.446
Long Beach St
1
0
2
5
4
0
1
3
4
5
-0.083
Louisiana Tech
0
0
0
6
3
0
1
0
8
4
0.179
Maine
0
0
1
2
7
0
0
3
3
8
0.243
Manhattan
0
0
1
8
3
0
0
1
7
6
-0.190
Marist
0
0
1
6
7
0
0
2
6
4
0.262
Maryland
3
1
7
2
4
3
1
5
0
0
0.954
Michigan St
5
2
2
2
3
7
2
1
1
0
1.078
Middle Tenn St
1
0
3
3
8
0
0
1
4
7
-0.367
Mississippi
3
2
3
1
4
3
1
3
3
0
0.477
Mt St Marys
0
0
0
4
9
0
1
1
3
8
0.308
Navy
1
0
1
3
7
0
0
1
4
5
-0.150
New Mexico State
0
0
2
6
3
0
1
2
4
6
-0.063
Niagra
0
0
1
6
3
1
0
1
8
4
0.200
North Carolina
2
4
6
3
1
2
2
5
0
3
-0.188
North Texas
0
0
3
5
2
1
2
3
6
3
0.367
Oklahoma
0
3
3
5
6
1
2
2
3
1
0.712
Old Dominion
0
0
1
7
5
1
1
1
8
2
0.615
Prairie View
0
0
0
2
6
0
1
0
6
7
0.393
Princeton
0
1
2
1
6
1
1
3
2
7
0.271
Quinnipiac
0
0
0
2
9
1
1
1
2
10
0.552
Robert Morris
0
0
0
3
9
1
0
0
4
8
0.365
Southern
0
0
0
2
8
0
0
1
1
9
0.073
St Marys CA
1
1
0
7
2
1
0
1
5
5
-0.356
Stanford
3
4
3
3
0
4
3
3
2
1
0.000
SW Missouri St
0
1
6
6
2
1
2
7
3
0
0.677
Temple
2
2
2
6
0
1
3
3
5
1
-0.154
Texas
2
3
2
5
1
1
3
1
7
2
-0.429
Texas A&M
0
3
4
3
4
0
3
2
4
3
-0.012
Texas Southern
0
0
0
2
6
0
2
1
4
6
0.673
Troy St
0
0
0
1
8
0
0
1
4
6
0.434
UCLA
2
5
4
4
2
2
4
3
1
0
0.641
USC
3
3
2
6
2
3
4
4
1
0
0.813
Virginia
4
1
5
1
4
3
1
4
1
1
0.400
Washington
3
2
5
2
1
4
2
4
1
0
0.510
Wisc Green Bay
1
1
2
5
4
0
1
2
5
3
-0.140
Youngstown St
0
0
0
4
5
0
1
0
5
5
0.283

After gathering the schedule strength data and HCA data, I used regression analysis to correlate the HCA with the home schedule strength of each team, in an attempt to link easier home schedules with a greater HCA. The graphs for each season are below.

2000-2001 HCA vs. Schedule Strength:

1999-2000 HCA vs. Schedule Strength:

1998-1999 HCA vs. Schedule Strength:

The slopes of the lines indicate that teams with higher HCA percentages tend to an easier home schedule when compared to their away schedules. For example, during the 2000-2001 season, teams that had a schedule ease of 0 (indicating equal toughness of both home and away schedules), had an average HCA of 23.6%. Teams that had a schedule ease of 1 (indicating an easier home schedule than away schedule) had an average HCA of 33.4%. During the 1999-2000 season teams that had a schedule ease of 0 had an HCA of 23.3%, while teams with a schedule ease of 1 had an average HCA of 40.07%. Finally, for the 1998-1999 seasons, teams with a 0 schedule ease had an average HCA of 24.24 %, while teams with a 1 schedule ease had an average HCA of 37.92% In conclusion, the teams that tended to have the greater HCA had an easier schedule at home in comparison to their away game schedule.

Recalculation Without the Lowest 20 Teams for the 2000-2001 Season:

As was stated earlier, this model of examining the HCA is not very accurate for the lowest 20 teams studied, because they do not get a chance to fully exploit the schedule weighting system (because they tend to not play highly ranked teams). I replotted the regression analysis line without the lowest ranked 20 teams in order to see how the best fit line would have changed.

For the HCA vs. Home Schedule graph neglecting the lowest twenty teams increases the slope of the best-fit line, which means that the HCA has an even stronger correlation when the disparity between home and away strength grows (with a weaker home schedule). The disparity between the regression coefficients was .0981 when the lowest ranking 20 teams were included, and .157 when they were omitted. Eliminating the weakest 20 teams makes the data more reliable because the method used to rate the schedules is not perfectly reliable for college teams that play weak teams (the tendency is for low ranked teams to play other low ranked teams). For the 2000-2001 season (neglecting the lowest 20 teams) the average HCA with a schedule ease of 0 was 24.68%, and the average HCA with a schedule ease of 1 was 40.46%. Without factoring in the lowest ranked 20 teams, the average HCA’s increase with schedule ease.

III. Does attendance matter?

The second factor studied was the size of the stadium that the men’s basketball teams were playing in. The way that I investigated this was by using regression analysis, and doing almost the same thing that I did with the team’s schedule strength. I researched the average 2000-2001 attendance for each division 1 school that I am studying, and paired up each team’s HCA with their respective attendance. I made a graphical representation of the data to see if HCA and average attendance correlated within the basketball seasons that I studied. The data and graphs are shown below.

2000-2001 HCA vs. Attendance: 1999-2000 HCA vs. Attendance:
 
School Name
Average Game Attendance
HCA Factor
School Name
Average Game Attendance
HCA Factor
Albany NY
1,148
20.2%
 Arizona
14349
30.8%
Arizona
14,533
23.0%
 Ark Pine Bluff
933
26.2%
Ark Pine Bluff
1,405
11.1%
 Arkansas LR
2029
28.6%
Arkansas LR
3,328
23.8%
 Boston College
3858
36.7%
Boston College
5,341
40.0%
 Chattanooga
4175
31.8%
Chattanooga
3,519
55.0%
 Cornell
1270
3.0%
Cornell
955
2.3%
 Duke
9314
-13.3%
Duke
9,314
-2.5%
 East Tenn St
3497
18.8%
East Tenn St
2,198
30.0%
 Eastern Mich
2262
17.1%
Eastern Mich
1,659
21.4%
 Evansville
8587
50.0%
Evansville
7,148
46.4%
 Florida
9018
28.2%
Florida
10,543
13.9%
 Florida A&M
1103
26.9%
Florida A&M
1,222
27.3%
 Grambling
1124
0.0%
Grambling
2,154
36.8%
 Hartford
647
24.7%
Hartford
1,155
9.8%
 Illinois
13173
31.1%
High Point
1,170
40.0%
 Indiana
15328
35.7%
Illinois
15,469
45.5%
 Iowa St
10142
33.3%
Indiana
14,905
45.7%
 Jackson St
1901
30.3%
Iowa St
12,360
40.0%
 Kansas
16277
47.4%
Jackson St
1,703
20.0%
 Kentucky
23367
50.0%
Kansas
16,179
28.0%
 Long Beach St
2629
0.8%
Kentucky
21,786
37.1%
 Louisiana Tech
1810
32.1%
Long Beach St
2,472
30.3%
 Maine
2820
18.2%
Louisiana Tech
1,903
26.1%
 Manhattan
1149
30.3%
Maine
2,603
35.2%
 Marist
1893
23.8%
Manhattan
1,987
36.5%
 Maryland
14474
49.7%
Marist
2,258
69.2%
 Michigan St
14591
46.2%
Maryland
14,058
11.9%
 Middle Tenn St
3803
31.0%
Michigan St
14,759
33.3%
 Mississippi
5508
70.0%
Middle Tenn St
2,042
15.4%
 Mt St Marys
1690
23.3%
Mississippi
5,687
33.3%
 Navy
2196
16.7%
Mt St Marys
1,426
27.4%
 New Mexico State
7390
31.9%
Navy
2,275
20.0%
 Niagra
1543
43.3%
New Mexico State
6,981
0.0%
 North Carolina
19308
9.7%
Niagra
1,829
1.2%
 North Texas
2340
34.0%
North Carolina
20,836
10.6%
 Oklahoma
10248
21.6%
North Texas
1,542
2.3%
 Old Dominion
4381
40.1%
Oklahoma
10,324
41.7%
 Prairie View
2460
24.2%
Old Dominion
3,263
45.2%
 Princeton
5573
25.0%
Prairie View
2,011
29.7%
 Quinnipiac
973
25.0%
Princeton
5,419
50.4%
 Robert Morris
1185
22.7%
Quinnipiac
1,003
19.6%
 Southern
2560
46.0%
Robert Morris
894
33.7%
 St Marys CA
2676
43.3%
Sacred Heart
505
28.3%
 Stanford
10088
-6.3%
Southern
1,552
40.2%
 SW Missouri St
7646
35.7%
St Marys CA
776
8.3%
 Temple
7925
30.8%
Stanford
7,391
-16.7%
 Texas
9772
42.9%
SW Missouri St
6,700
50.0%
 Texas A&M
4083
41.7%
Temple
7,138
7.1%
 Texas Southern
882
0.0%
Texas
9,081
39.6%
 Troy St
1526
44.9%
Texas A&M
4,119
40.9%
 UCLA
10130
29.5%
Texas Southern
1,266
21.3%
 USC
3801
49.7%
Troy St
1,699
26.6%
 Virginia
6624
42.9%
UCLA
8,765
7.3%
 Washington
6699
-4.9%
USC
5,323
25.5%
 Wisc Green Bay
4031
67.9%
Virginia
8,220
47.9%
 Youngstown St
1963
11.5%
Washington
6,543
8.3%
Wisc Green Bay
3,733
21.2%
Youngstown St
2,728
30.0%

1998-1999 HCA vs. Attendance:
 
School Name
Average Game Attendance
HCA Factor
Arizona
14530
55%
Arkansas LR
2472
53%
Boston College
5009
36%
Chattanooga
4841
25%
Cornell
1319
-5%
Duke
9314
0%
East Tenn St
2891
14%
Eastern Mich
2861
-7%
Evansville
8177
6%
Florida
7724
54%
Florida A&M
1564
34%
Grambling
1756
15%
Hartford
859
21%
Illinois
13398
6%
Indiana
16271
28%
Iowa St
10717
69%
Jackson St
2101
35%
Kansas
16027
22%
Kentucky
23946
42%
Long Beach St
2326
12%
Louisiana Tech
1852
54%
Maine
1950
23%
Manhattan
1185
11%
Marist
2958
30%
Maryland
13377
27%
Michigan St
13913
27%
Middle Tenn St
3417
22%
Mississippi
6458
47%
Mt St Marys
1367
23%
Navy
2273
23%
New Mexico State
6961
37%
Niagara
2538
64%
North Carolina
20966
23%
North Texas
2502
23%
Oklahoma
9226
29%
Old Dominion
4542
32%
Prairie View
2422
11%
Princeton
5407
16%
Robert Morris
1151
37%
Southern
2270
45%
St Marys CA
2089
30%
Stanford
6734
8%
SW Missouri St
7161
26%
Temple
7964
46%
Texas
11179
-3%
Texas A&M
3442
39%
Texas Southern
2004
35%
Troy St
729
17%
UCLA
10739
44%
USC
3310
35%
Virginia
6271
30%
Washington
5319
74%
Wisc Green Bay
3723
39%
Youngstown St
2429
21%

2000-2001 HCA vs. Attendance:


 
 
 
 
 
 
 
 
 
 
 
 
 
 

1999-2000 HCA vs. Attendance:

1998-1999 HCA vs. Attendance:

As can be seen by the best-fit line, there is not a huge correlation between the size of the attendance and the HCA of the team. However, the graph displays that as the attendance rises, the HCA slightly varied with attendance. Extrapolating the data yields an HCA of 26% with no crowd, and an HCA of 30% with a crowd of 20,000 for the 2000-2001 season. For the 1999-2000 season, and the 1998-1999 season, the conclusion was the same. The average attendance of the basketball games only slightly affects a college basketball team’s HCA.

IV. Ranking and HCA?

The next variable that was studied was the rank of the team, and whether or not teams with a greater ranking had a higher HCA than teams with a lower ranking. My hypothesis is that the ranking of a teams shouldn’t affect their HCA, because their rank shouldn’t affect whether or not they win more home games than away games.

2000-2001 HCA vs. Ranking Graph:


 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

1999-2000 HCA vs. Ranking Graph:

1998-1999 HCA vs. Ranking Graph:

The graph shows that teams with better rankings typically have a slightly higher HCA. During the 2000-2001 season, the average HCA for the top 20 teams was 28.38%, the average for the middle 20 teams was 26.88%, and the average for the lowest 20 teams was 25.38%. Although the top ranked teams tended to have a higher HCA than the lower ranked teams, the difference was not that significant during that season. The 1999-2000, and 1998-1999 seasons were a little more drastic. The regression coefficient was greater, and the range of HCA’s varied a little bit more than they did during the 2000-2001 season (1999-2000: 32.36% - 26.06% 1998-1999: 34.2% - 22.2%).

V. Other’s Views

After completing my own analysis of the home court advantage, I consulted a number of other sources in hopes of finding other studies and correlations that were found. Within an article written by Mark Mizruchi, he forms several hypotheses as to why the home court advantage exists, and some of the factors that help increase it. Mizruchi hypothesized that the smaller the SMSA (surrounding city size) the greater the home court advantage would be. He theorized that loyalties would be more focused on the team, and the citizens would have fewer distractions. After testing his data with 23 NBA teams throughout the 1981-82 season, he found that city size does correlate with the home court advantage.

After reading Mizruchi’s findings, I wanted to see if his findings also held true to the undergraduate populations of college; that the smaller the support base, the greater the HCA. I gathered undergraduate data from as many schools as I could, and correlated it with HCA. Graphs and Tables of my findings for the 3 years are shown below.
 
School Name
2001 Undergraduate Population
2000-2001 HCA
1999-2000 HCA
1998-1999 HCA
Albany NY
11,780
20%
17.9%
Arizona
26,404
23%
30.8%
55%
Ark Pine Bluff
3,425
11%
26.2%
11%
Arkansas LR
8,559
24%
28.6%
53%
Boston College
9,190
40%
36.7%
36%
Chattanooga
6,993
55%
31.8%
25%
Cornell
13,590
2%
3.0%
-5%
Duke
6,325
-3%
-13.3%
0%
East Tenn St
9,125
30%
18.8%
14%
Eastern Mich
18,131
21%
17.1%
-7%
Evansville
2,624
46%
50.0%
6%
Florida
32,680
14%
28.2%
54%
Florida A&M
10,691
27%
26.9%
34%
Grambling
4,260
37%
0.0%
15%
Hartford
5,367
10%
24.7%
21%
High Point
2,623
40%
55.4%
Illinois
27,908
45%
31.1%
6%
Indiana
29,383
46%
35.7%
28%
Iowa St
21,503
40%
33.3%
69%
Jackson St
5,471
20%
30.3%
35%
Kansas
20,157
28%
47.4%
22%
Kentucky
16,897
37%
50.0%
42%
Long Beach St
25,153
30%
0.8%
12%
Louisiana Tech
8,921
26%
32.1%
54%
Maine
8,229
35%
18.2%
23%
Manhattan
2,703
37%
30.3%
11%
Marist
4,713
69%
23.8%
30%
Maryland
24,638
12%
49.7%
27%
Michigan St
33,966
33%
46.2%
27%
Middle Tenn St
15,890
15%
31.0%
22%
Mississippi
9,608
33%
70.0%
47%
Mt St Marys
1,708
27%
23.3%
23%
Navy
4,172
20%
16.7%
23%
New Mexico State
12,831
0%
31.9%
37%
Niagra
2,357
1%
43.3%
64%
North Carolina
15,608
11%
9.7%
23%
North Texas
20,449
2%
34.0%
23%
Oklahoma
18,308
42%
21.6%
29%
Old Dominion
12,786
45%
40.1%
32%
Prairie View
5,285
30%
24.2%
11%
Princeton
4,663
50%
25.0%
16%
Quinnipiac
4,843
20%
25.0%
10%
Robert Morris
3,814
34%
22.7%
37%
Sacred Heart
4,029
28%
27.3%
Southern
4,500
40%
46.0%
45%
St Marys CA
1,708
8%
43.3%
30%
Stanford
7,886
-17%
-6.3%
8%
SW Missouri St
14,699
50%
35.7%
26%
Temple
18,394
7%
30.8%
46%
Texas
37,159
40%
42.9%
-3%
Texas A&M
36,229
41%
41.7%
39%
Texas Southern
8,832
21%
0.0%
35%
Troy St
4,602
27%
44.9%
17%
UCLA
25,011
7%
29.5%
44%
USC
15,705
25%
49.7%
35%
Virginia
13,712
48%
42.9%
30%
Washington
16,839
8%
-4.9%
74%
Wisc Green Bay
5,334
21%
67.9%
39%
Youngstown St
10,619
30%
11.5%
21%

 
 
 
 
 
 
 
 
 

2000-2001 HCA vs. Undergraduate Size

1999-2000 HCA vs. Undergraduate Size

1998-1999 HCA vs. Undergraduate Size

The findings from this comparison indicate the opposite of Mizruchi’s findings. The larger the population of undergraduates that the basketball team represents, the larger the home court advantage. I was a little bit surprised with this result. It seemed to me that the smaller the school, the relationship between the fans and the players would be more intimate. After thinking about this for a little while, I came to the conclusion that this assumption was not totally accurate. The average attendance for each of the games was not solely composed of students, but rather of regular ticketholders who might not have a direct affiliation with the college. The statistics of the ratio of students to ticketholders were not available, but I make another hypothesis from the undergraduate population data.

I also theorized that as the ratio of undergraduate students to average game attendance goes up, the home court advantage would also increase. The basis for this hypothesis was that only the most fanatical students would jump through all of the hoops to get into games (like waiting in lines, etc) and the home court advantage would be increased by their passionate presence. The correlation between undergraduate population : average game attendance and HCA is shown below.
 
 
 
 
 
 
 
 
 
 
 
 
 
 

2000-2001 HCA vs. Ratio of Undergraduate Size to Attendance

1999-2000 HCA vs. Ratio of Undergraduate Size to Attendance

1998-1999 HCA vs. Ratio of Undergraduate Size to Attendance

My hypothesis was wrong. As the undergraduate population: attendance ratio increases, the HCA decreases. Similar to the undergraduate vs. HCA data, this data could also be flawed. Analyzing the ratio between undergraduate population and attendance is worthless if the student section at basketball games is small compared to the amount of ticketholders at games. If a school simply doesn’t have a student section (which probably is not true, but helps to prove my point of a small undergraduate population : attendance ratio) then the data would be totally void.

VI. Conclusion:

The home court advantage is a complex subject that is different for every sport. For the 2000-2001, 1999-2000, and 1998-1999 college basketball seasons there are several conclusions that can be drawn from the data that I analyzed. First of all, the home court advantage is affected greatly by the team’s schedule. Teams that play a greater proportion of their "easy" games at home, when compared to their "tough" road games have a much higher HCA than teams with opposite schedules. Using the measure of schedule strength that I invented, teams that had a disparity of 0 during 1999-2000, meaning equal home and away strengths, had an average HCA of 23.3%, while teams with a disparity of 1, indicating a weaker home schedule than away schedule had an HCA of 40.07%. This 17 percent difference was one of the biggest factors that I found that influenced the HCA. Also, this data still includes the lowest 20 ranking teams who have been proven to level out the regression line. Eliminating them from the data further increases the HCA disparity between home and away schedules. Using this data, and the data from the other seasons, an interesting question can be raised; How much of the home court advantage is simply playing easier teams at home? Could the entire notion of the home court advantage be inflated, simply because home schedules have simply been easier than away schedules? The study that I conducted cannot draw these conclusions, simply because I only analyzed one sport, and used only three years in the study. A complex analysis of multiple American sports throughout many years would be needed to draw any definite conclusions about whether or not the home court advantage has been partially a product of scheduling easier teams at home.

My study of the stadium size (average attendance) was not as dramatic as my findings with schedule strength. The slope of the line was small, but rose slightly as attendance increased. My other study of rank indicated that the higher ranked a team is, the greater HCA they will experience. Also, the greater the undergraduate size that a college team represents, the greater the HCA will be (slightly). Finally, something else surprising that I found was that as the ratio of undergraduate students to stadium seats increases, the HCA rapidly decreases. I hypothesized exactly the opposite. I thought that the competition for tickets would weed out the passive fans, and leave only the hardcore vocal fans. No real conclusions can be drawn about this phenomenon, because there is no data about the ratio of student seats to ticketholder seats readily available.

From my data, the ideal team with the greatest HCA would be one that played very easy games at home compared to their away schedule, have a large crowd, a large undergraduate population, a high rank, and a low undergraduate population : average attendance ratio. The home court advantage in the 2000-2001 College basketball season was definitely a pronounced phenomenon with definite identifiable trends.

Notes:

Greenfiled, Mike. "NCAA Basketball Rankings" 2000-2001 <www.teamrankings.com>

Krzyzewski, Mike. Leading With the Heart. New York, NY: Warner Business Books, 2000.

Mizruchi, Mark."Urgency, Motivation, and Group Performance: The Effect of Prior Success on Current Success Among Professional Basketball Teams" Social Psychology Quarterly Vol 54, Issue 2 (1991) 181-189.

Mizruchi, Mark. "Local Sports Teams and Celebration of Community: A Comparative Analysis of the Home Advantage" The Sociologica l Quarterly. Vol 26 Num 4 (1985) 507-518.

Moore, James C. "Spectator Effect on Team Performance in College Basketball." Journal of Sport Behavior Vol 16. Issue 2 (1993): 77-85.

NCAA Online. "2001 National College Basketball Attendance" 2001 <http://www.ncaa.org/stats/m_basketball/attendance/index.html>

Schwartz, Barry and Stephen F. Barsky. "The Home Advantage." Social Forces Vol 55:3 (1977) 641-661.

The Princeton Review. "College Database" December 2001 <www.review.com>.

Varca, Philip E. "An Analysis of Home and Away Game Performance of Male College Basketball Teams." Journal of Sport Psychology Vol 2 (1980): 245-257.

Whyte, William Foote. Street Corner Society. Chicago, IL: The University of Chicago Press, 1943.