Authors: Mark Mitchell, Samuel Wathen, and Robert Orwig
Corresponding Author:
Mark Mitchell, DBA
Professor of Marketing
Associate Dean, Wall College of Business
NCAA Faculty Athletics Representative (FAR)
Coastal Carolina University
P. O. Box 261954
Conway, SC 29528
mmitchel@coastal.edu
(843) 349-2392
Mark Mitchell, DBA is Professor of Marketing at Coastal Carolina University in Conway, SC.
Samuel Wathen, PhDis Professor of Management at Coastal Carolina University in Conway, SC.
Robert Orwig, DBA is Associate Professor of Management at the University of North Georgia in Dahlonega, GA.
Evaluating the Impact of Two-Game Road
Trips in College Sports: Does a Travel
Partner Scheduling Approach Affect Team Competitiveness?
ABSTRACT
Some NCAA athletic conferences have implemented a geographic travel partner strategy when scheduling league games. Teams are organized into two-team clusters. A visiting team comes to the region and plays both opponents during one road trip before returning to campus. Prior research reveals NBA teams tend to have a lower winning percentage when playing back-to-back games on back-to-back evenings. This study examines the performance of college sports teams on two-game road trips to see if the NBA pattern exists in college sports. Game results (and winning percentages) from the Sun Belt Conference for the 2016-17 season are evaluated over four sports (women’s soccer, women’s volleyball, women’s basketball, and men’s basketball). Team performance in Game 2 was comparable to Game 1 in women’s soccer, women’s basketball, and men’s basketball. Game 2 performance was improved in women’s volleyball. There was not a significant reduction in road team performance in Game 2 of two-game road trips when the quality of the opponent was introduced into the analysis of women’s soccer, women’s volleyball and women’s basketball. However, men’s basketball teams tended to win more often during Game 1 rather than Game 2 when playing comparable opponents. The travel partner scheduling model maximizes player rest, reduces travel time, and minimizes missed class time. This study suggests its implementation does not impact team competitiveness, particularly during Game 2 as found in the NBA. Conference personnel and university athletic administrators may take comfort that their drive to control costs and enhance the student-athlete experience is not impacting the competitiveness of their teams.
Keywords: Team winning percentages, game scheduling, travel partner scheduling, home team advantage
INTRODUCTION
Beginning with the 2018-19 season, the Colonial Athletic Association (CAA) implemented a ‘travel partner’ scheduling strategy for Women’s Basketball, pairing each team with a geographic travel partner for league games. This format allows for the scheduling of back-to-back Friday and Sunday games with both games played either at home or on the road. For example, the University of North Carolina at Wilmington played at the College of William & Mary (Williamsburg, VA) on Friday and later at Elon University (Burlington, NC) on Sunday (Washburn 2018). For the same weekend, their travel partner (The College of Charleston) played an opposite and concurrent schedule at Elon on Friday and at William & Mary on Sunday. According to Mapquest, the Elon and William & Mary are approximately 250 miles apart (5).
The Sun Belt Conference has used the travel partner scheduling format since 2015 (2). In fact, geographic proximity to an existing conference member (Appalachian State University) was an important variable in the selection of the most-recent addition to the conference (Coastal Carolina University in 2016). A press release from the Sun Belt Conference on that day outlined this geographic strategy this way (10):
With the addition of Coastal Carolina, the Sun Belt Conference will now have a symmetrical, geographic structure that is unparalleled in the history of the conference. The league will have two universities in Alabama (South Alabama and Troy), Arkansas (Arkansas State and Little Rock), Georgia (Georgia Southern and Georgia State), Louisiana (UL Lafayette and UL Monroe) and Texas (UT Arlington and Texas State) to go with Appalachian State in North Carolina and Coastal Carolina in neighboring South Carolina.
When announcing the Men’s Basketball schedule for 2016-17, Conference Commissioner Karl Benson noted (11):
“This is an exciting time for the Sun Belt Conference as we have created a membership structure that makes perfect sense with six sets of travel partners located in seven states,” Sun Belt Conference commissioner Karl Benson said. “Not only does the 12 team league allow for an 18-game regular season but it will allow for a much more manageable travel schedule for our men’s and women’s student-athletes that will result in less missed class time and much more time back on their respective campuses rather than on airplanes and buses.”
Further in the same press release (11), the conference communication notes that “each team will only travel four times for two-game road trips during the upcoming season. Travel partners will be utilized for two-game road trips throughout the conference schedule to maximize rest, minimize travel times and limit missed class time for men’s and women’s basketball student-athletes. Men’s and women’s basketball programs will each take just one, single-game road trip all season. Those single-game road trips will be for rivalry games.”
In the book “Scorecasting: The Hidden Influences Behind How Sports are Played and Games are Won,” authors Tobias Moskowitz and Jon Wertheim note that home teams win 62% of their games in the National Basketball Association (NBA). However, they note that not all road games are equal. Occasionally, NBA teams will play on back-to-back nights in separate cities. And, when doing so, these teams seem to be ‘a step slow.’ On average, NBA teams playing on back-to-back nights win 36% of these second-day games (for both home and away games). NBA Hall of Famer Charles Barkley referred to these second-day games as “throwaways.” He once described such games this way: “You show up because they pay you to show up. But, deep in your belly, you know you ain’t gonna win.” (6, p. 125).
For these back-to-back games, some NBA teams started resting players given their perceived competitive disadvantage. In March 2017, NBA Commissioner Adam Silver stated that the issue of resting players “is an extremely significant issue for our league” as fans complained that their favorite players were being rested on a night these fans showed up just to watch these visiting team stars play (8). For illustration, the Cleveland Cavaliers played 15 such games during that 2016-17 regular season. For these 2-city back-to-back games, the Cavaliers had a record of 5-10 (a 0.33 winning percentage). Backing out these 15 games from the team’s overall record of 51-31, we see the Cavaliers were 46-21 (a 0.69 winning percentage) in the remainder of games that provided at least one day of rest between games (1).
As illustrated above, the scheduling of back-to-back contests may affect team competitiveness, particularly during the second game of the road trip. With few exceptions (such as women’s volleyball when destinations are relatively close), college sports schedules usually allow a rest day between contents. Still, these student-athletes are ‘on the road’ which means hotels, restaurants, and being removed from their normal school routines. And, we must acknowledge the substantial differences in team travel between NBA professionals and NCAA student-athletes, particularly the presence of bus trips, non-charter air flights, and the obvious differences in hotel and restaurant accommodations.
The purpose of this manuscript is to analyze team performance on two-game road trips in one conference for a variety of sports for an entire sports season. Win-loss records will be analyzed in addition to some measure of competitive strengths of the teams. With the results, coaches and athletic administrators can formulate strategies to improve team performance or, if viewed differently, to minimize the ‘effects of the road’ on their teams.
METHODS
Where possible, the Sun Belt Conference (SBC) adheres to the travel partner scheduling strategy. The twelve member schools are divided into six two-team travel partner clusters:
- Carolinas: Coastal Carolina University / Appalachian State University
- Georgia: Georgia Southern University / Georgia State University
- Alabama: Troy State University / University of South Alabama
- Louisiana: University of Louisiana Lafayette / University of Louisiana Monroe
- Arkansas: Arkansas State University / University of Arkansas Little Rock
- Texas: Texas State University / University of Texas at Arlington
As an illustration, let’s assume the Texas schools are paired with the Georgia schools for a weekend. Texas State University would play at Georgia State University on Thursday and then travel to Georgia Southern University for a Saturday game before returning to Texas. Conversely, the University of Texas Arlington would play a mirror-image schedule. That is, they would play at Georgia Southern University on Thursday and then at Georgia State University on Saturday before returning to Texas.
The earlier comments by former NBA player Charles Barkley suggest teams may not perform as well during the second game of a two-game road trip. This question will be empirically tested here. In the Sun Belt Conference, the primary sports using the two-game road trip are women’s soccer, women’s volleyball, women’s basketball, and men’s basketball. With the addition of the 12th member school (Coastal Carolina University) for the 2016-17 season, data is available on the performance of each SBC team in its home and away conference games during the first year of full implementation. Win-loss records will be analyzed in each sport to compare performance in Game 1 versus Game 2 of each two-game road trip. Given the presence of a favored team (such as a team with a better season record to date), a measure of competitive strength of each team is added to the analysis. A Game 2 loss to a heavily-favored team differs from a Game 2 loss to an underdog (based on performance to date that season).
The Sun Belt Conference provides a longitudinal look at the results of all its sanctioned sports on its website (9). For each athletic competition, researchers can identify: Date, Home Team, Visiting Team, and Final Score. Analysis of date allows researchers to determine if the game was a single-game or part of a two-game road trip for that team. The following example pattern would be self-evident in the schedule/data: Play Thursday at Appalachian State University, Play Saturday at Coastal Carolina University. In total, we would see both single game road trips and two-game road trips. For comparison purposes, the results of both types of games are evaluated. However, the focus for this study is the two-game road trip and, specifically, team performance during the second game played.
It must be noted that the relatively small sample size (or number of observations in each cell) prohibit the use of more sophisticated statistical methods in this study. Rather, we will compare winning percentages per contest and winning percentages under certain game scenarios. Still, we believe we can make valid conclusions from the data.
The Comforts of Home (for Home Teams)
Historically, there has been some advantage to sports teams playing in their home stadiums and communities. These advantages can include: a raucous crowd of fans, a familiar environment, the lack of travel to the game destination, and other factors. Over the last 10 years, on average, home teams have won the majority their home games in the following sports (6, p. 112):
- NBA = 61%
- Major League Baseball = 54%
- NFL = 57%
- NHL = 56%
- Major League Soccer (USA) = 69%
- NCAA College Football = 63%
- NCAA Men’s Basketball = 69%
Jamieson (3), reporting a meta-analysis of studies on home field advantage, noted that home field advantage tends to be strongest for basketball, hockey, and soccer and less for football and baseball. It should be noted that, for NCAA sports these records also include non-conference competition. In scheduling their non-conference games, some institutions choose non-peers for such games, and often provide an appearance fee for that team. For example, The Ohio State University Men’s Basketball team was 10-0 in home non-conference games in 2017 by hosting the following teams: North Carolina Central; Providence College; Western Carolina; Jackson State; Marshall; Fairleigh Dickinson; Florida Atlantic; Connecticut; Youngstown State; and UNC Asheville (12). For this reason, this study is enhanced by its focus on peer-competition (i.e., conference members) and an assumption of greater competitive parity among the participants.
Travel Partners in NCAA Sports
Recent research by the Knight Commission on Intercollegiate Athletics (4) found that athletics expenses are rising at an annual rate of approximately 7% and that revenues (from current sources) are not expanding as quickly. NCAA research (7) found spending for athletics increased 43 percent between 2004 and 2008 while revenue increased by 33% during the same period. Against this backdrop, member institutions are looking at (a) new revenue sources, and (b) sensible cost reductions. As noted earlier, scheduling two games in a geographic area can help reduce operating costs while concurrently reducing lost class time for student-athletes. Consider these two options for a team from South Carolina to play two teams in Texas or Arkansas.
- FIRST Single Game Trip: Day 1 = Fly to area; Day 2 = Game; Day 3 = Fly home.
- SECOND Single Game Trip: Day 1 = Fly back to area; Day 2 = Game; Day 3 = Fly home.
- Total Days = 6
Now, let’s assume the same team plays two games in that region or state on same road trip.
- 2-Game Road Trip: Day 1 = Fly to Area; Day 2 = Game 1; Day 3 = Bus to second site; Day 4 = Game 2; Day 5 = Fly home.
- Total Days = 5
As illustrated above, the school incurs the cost of one airfare per person to play two games. And, students miss one fewer day of class for each trip (five days as opposed to six days). Further, Watkins (14) found there was not a significant relationship between longer road trips and home court advantage in Big 12 men’s basketball. Applied to this study, this suggests a South Carolina school is not at a greater competitive disadvantage when scheduling these longer distance two-game road trips.
Conference USA, a neighboring Division I FBS Conference with 14 member schools, uses a similar pattern of scheduling with the following travel partner paired institutions:
- Florida Atlantic / Florida International
- UT El Paso, UT San Antonio
- Marshall / Western Kentucky
- UAB / Middle Tennessee State
- Rice / North Texas
- Southern Miss / LA Tech
- Charlotte / Old Dominion
The Power 5 Conferences (ACC, Big 10, Big 12, PAC 12, and SEC) tend not use this format. Other Group-of-5 conferences use selected travel partners (such as the Mountain West, Mid- American, and American Athletic) but the Sun Belt and Conference USA rely more heavily on this geographic strategy for scheduling purposes.
RESULTS AND DISCUSSION
The data was extracted from the website and input into EXCEL to track the won-loss records of the various teams and institutions. From this information, the researchers could identify the won-loss records of both HOME and VISITING teams for each contest. Independent of the strength of the opponents, the won-loss records (and winning percentages) for both HOME and VISITOR teams for each sport is provided in Table 1 (women’s soccer), Table 2 (women’s volleyball), Table 3 (women’s basketball) and Table 4 (men’s basketball). First, we see the following winning percentages for all contests:
- Women’s Soccer: Home teams win 54% of all games; visiting teams win 30% of all games; the remaining games ended in a tie.
- Women’s Volleyball: Home teams win 51% of all games; visiting teams win 49% of all games.
- Women’s Basketball: Home teams win 57% of all games; visiting team win 43% of all games.
- Men’s Basketball: Home teams win 66% of all games; visiting team win 34% of all games.
| Type of Contest | Home Team Record | Visiting Team Record |
| All SBC Games | 29-16-9 (0.54 winning %) | 16-29-9 (0.30 winning %) |
| SBC Single Games | 6-4-2 (0.50 winning %) | 4-6-2 (0.33 winning %) |
| SBC Game 1 of 2-Game Trip | 11-7-3 (0.52 winning %) | 7-11-3 (0.33 winning %) |
| SBC Game 2 of 2-Game Trip | 12-5-4 (0.57 winning %) | 5-12-4 (0.23 winning %) |
| Number of 2-0 Road Trips | Number of SPLIT Road Trips (1-1, 1-0-1, 0-1-1) |
Number of 0-2 Road Trips |
| 3 (14%) | 11 (53%) 7 = Win/Tie First Game 4 = Win/Tie Second Game |
7 (33%) |
| NOTE: Soccer matches can end in ties. For this reason, the winning percentages between home and visiting teams do not add up to 100%. | ||
| Type of Contest | Home Team Record | Visiting Team Record |
| All SBC Games | 49-47 (0.51 winning %) | 47-49 (0.49 winning %) |
| SBC Single Games | 8-7 (0.53 winning %) | 7-8 (0.47 winning %) |
| SBC Game 1 of 2-Game Trip | 23-17 (0.58 winning %) | 17-23 (0.42 winning %) |
| SBC Game 2 of 2-Game Trip | 18-23 (0.44 winning %) | 23-18 (0.56 winning %) |
| Number of 2-0 Road Trips | Number of 1-1 Road Trips | Number of 0-2 Road Trips |
| 12 (30%) | 15 (38%) 6 = Win First Game 9 = Win Second Game |
13 (32%) |
| Type of Contest | Home Team Record | Visiting Team Record |
| All SBC Games | 52-46 (0.57 winning %) | 46-52 (0.43 winning %) |
| SBC Single Games | 5-7 (0.42 winning %) | 7-5 (0.58 winning %) |
| SBC Game 1 of 2-Game Trip | 29-19 (0.60 winning %) | 19-29 (0.40 winning %) |
| SBC Game 2 of 2-Game Trip | 28-20 (0.58 winning %) | 20-28 (0.42 winning %) |
| Number of 2-0 Road Trips | Number of 1-1 Road Trips | Number of 0-2 Road Trips |
| 9 (19%) | 21 (44%) 10 = Win First Game 11 = Win Second Game |
18 (37%) |
| Type of Contest | Home Team Record | Visiting Team Record |
| All SBC Games | 71-37 (0.66 winning %) | 37-71 (0.34 winning %) |
| SBC Single Games | 9-3 (0.75 winning %) | 3-9 (0.25 winning %) |
| SBC Game 1 of 2-Game Trip | 30-18 (0.63 winning %) | 18-30 (0.37 winning %) |
| SBC Game 2 of 2-Game Trip | 32-16 (0.67 winning %) | 16-32 (0.33 winning %) |
| Number of 2-0 Road Trips | Number of 1-1 Road Trips | Number of 0-2 Road Trips |
| 8 (17%) | 18 (37%) 10 = Win First Game 8 = Win Second Game |
22 (46%) |
When we shift the analysis to the second game of a two-game road trip, the following summary statements are offered:
- Women’s Soccer: visiting teams won 33% of Game 1 contests and 23% of Game 2 contests.
- Women’s Volleyball: visiting teams won 42% of Game 1 contests and 53% of Game 2 contests.
- Women’s Basketball: visiting teams won 40% of Game 1 contests and 42% of Game 2 contests.
- Men’s Basketball: visiting teams won 37% of Game 1 contests and 33% of Game 2 contests.
As illustrated above and in Tables 1-4, there was not a significant reduction in road team performance in Game 2 of two-game road trips. Game 2 outcomes for road teams were comparable in women’s soccer, women’s basketball, and men’s basketball. And, Game 2 performance (i.e., winning percentage) was improved in women’s volleyball. When a team split a road trip (i.e., one win / one loss), women’s volleyball teams showed a marked higher likelihood to win Game 2 to complete their road trip rather than winning Game 1 to start their road trip.
Analysis of Opponent Quality
Over a season of competition, a team will typically play 3 types of contents: (1) games between comparable teams – no favorite to win; (2) games where one team is slightly favored to win; and (3) games where one team is heavily favored to win. As the old saying goes, “that’s why we play the games” … these mathematical likelihoods do not always occur. Teams have unexpected wins and unexpected losses. Arguably, all teams have the potential to experience each outcome over the life of a season.
One measure of competitive parity for use is the “Final Standings in Conference Play.” This after-the-fact analysis provides a ranking of the team’s body of work over the season. From this measure, overall stronger teams can be identified and the actual outcomes of the games can be classified and evaluated. For a 12-team league, there tends to be 3 clusters of teams: (1) Upper (2) Middle, and (3) Lower. This division of teams allows for a breakdown of games into 3 clusters:
- No Clear Favorite: 2 comparable teams compete. Win, Lose, or Tie … you played a comparable opponent.
- One Slightly Favored Team: teams are 1 cluster apart (such as an UPPER playing a MIDDLE or a MIDDLE playing a LOWER).
- One Heavily Favored Team: teams are 2 clusters apart (such as an UPPER playing a LOWER).
By season’s end, the clustering of Sun Belt Conference Schools by Sport is presented in Table 5.
Table 5: Clustering of Teams – Season Ending Standings| Women’s Soccer | Women’s Volleyball | Women’s Basketball | Men’s Basketball |
| South Alabama (1) (7-3) Coastal Carolina (2) (6-2-2) Little Rock (3) (6-3-1) |
Coast. Carolina (T1) (15-1) ARK State (T1) (15-1) Texas State (3) (13-3) |
Little Rock (1) (17-1) UT Arlington (2) (14-4) Troy (3) (12-6) |
UT Arlington (1) (14-4) GA State (2) (12-6) Arkansas State (T3) (11-7) GA Southern (T3) (11-7) TX State (T3) (11-7) |
| App. State (T4) (4-4-2) Louisiana (T4) (4-4-2) UL Monroe (T4) (4-4-2) Arkansas State (7) (4-5-1) |
UT Arlington (4) (10-6) Little Rock (5) (8-8) So. Alabama (T6) (7-9) GA Southern (T6) (7-9) GA State (T8) (6-10) Louisiana (T8) (6-10) |
Louisiana (T4) (11-7) TX State (T4) (11-7) GA Southern (6) (9-9) GA State (T7) (8-10) Coastal Carolina (T7) (8-10) |
Louisiana (T6) (10-8) Troy (T6) (10-8) Coastal Carolina (T6) (10-8) |
| Troy (T8) (3-5-2) Texas State (T8) (3-5-2) GA State (10) (2-4-4) GA Southern (11) (3-7) |
Troy (10) (4-12) UL Monroe (11) (3-13) App. State (12) (2-14) |
App. State (9) (6-12) Arkansas State (10) (5-13) South Alabama (11) (4-14) UL Monroe (12) (3-15) |
South Alabama (9) (7-11) Little Rock (10) (6-12) App. State (11) (4-14) UL Monroe (12) (2-16) |
| Source: www.sunbeltsports.org | |||
The focus of this study is road team performance; specifically, road team performance in Game 2 of a two-game road trip. Using these three clusters for each sport, the researchers can determine the following outcomes for both Game 1 and Game 2 for each sport:
- How often did the VISITING TEAM win or lose to a comparable opponent?
- How often did the VISITING TEAM win or lose versus a slightly favored opponent (one cluster apart)?
- How often did the VISITING TEAM win or lose versus a heavily favored opponent (two clusters apart)?
To provide a baseline for comparison, this information is presented for each sport in Table 6 (women’s soccer), Table 7 (women’s volleyball), Table 8 (women’s basketball) and Table 9 (men’s basketball). The following summary statements are offered:
Table 6: Sun Belt Conference – Women’s Soccer (by Final Standings)| Type of Contest | Game 1 | Game 2 | ||
| Home Record | Visiting Record | Home Record | Visiting Record | |
| From Table 1: All Opponents, regardless of strength |
7-11-3 (0.33 winning %) |
5-12-4 (0.23 winning %) |
||
| 2 Comparable Teams (Same Cluster) |
2-1-1 (0.50 winning %) |
1-2-1 (0.25 winning %) |
5-2-1 (0.63 winning %) |
2-5-1 (0.25 winning %) |
| 1 Slightly Favored Team (1 Cluster Separation) |
6-3-2 (0.55 winning %) |
3-6-2 (0.27 winning %) |
5-2-3 (0.50 winning %) |
2-5-3 (0.22 winning %) |
| 1 Heavily Favored Team (2 Cluster Separation) |
3-3-0 (0.50 winning %) |
3-3-0 (0.50 winning %) |
2-1-0 (0.67 winning %) |
1-2-0 (0.33 winning %) |
| Records of Heavily-Favored Teams On the Road |
3-0 | 1-0 | ||
| NOTE: Visiting team performance tended to be better in GAME 1 than GAME 2. | ||||
| Type of Contest | Game 1 | Game 2 | ||
| Home Record | Visiting Record | Home Record | Visiting Record | |
| From Table 2: All Opponents, regardless of strength |
17-23 (0.42 winning %) |
23-18 (0.56 winning %) |
||
| 2 Comparable Teams (Same Cluster) |
7-6 (0.54 winning %) |
6-7 (0.46 winning %) |
4-9 (0.31 winning %) |
9-4 (0.69 winning %) |
| 1 Slightly Favored Team (1 Cluster Separation) |
14-8 (0.64 winning %) |
8-14 (0.36 winning %) |
10-12 (0.45 winning %) |
12-10 (0.55 winning %) |
| 1 Heavily Favored Team (2 Cluster Separation) |
2-3 (0.40 winning %) |
3-2 (0.60 winning %) |
4-2 (0.67 winning %) |
2-4 (0.33 winning %) |
| Records of Heavily-Favored Teams On the Road |
3-0 | 2-0 | ||
| NOTE: Visiting team performance tended to improve in GAME 2 over GAME 1 for comparable and slightly favored teams. Further, heavily favored road teams were expected winners in Games 1 and 2. |
||||
| Type of Contest | Game 1 | Game 2 | ||
| Home Record | Visiting Record | Home Record | Visiting Record | |
| From Table 3: All Opponents, regardless of strength |
19-29 (0.40 winning %) |
20-28 (0.42 winning %) |
||
| 2 Comparable Teams (Same Cluster) |
10-3 (0.77 winning %) |
3-10 (0.23 winning %) |
10-6 (0.63 winning %) |
6-10 (0.37 winning %) |
| 1 Slightly Favored Team (1 Cluster Separation) |
15-11 (0.58 winning %) |
11-15 (0.42 winning %) |
13-11 (0.54 winning %) |
11-13 (0.46 winning %) |
| 1 Heavily Favored Team (2 Cluster Separation) |
4-5 (0.44 winning %) |
5-4 (0.56 winning %) |
5-3 (0.63 winning %) |
3-5 (0.37 winning %) |
| Records of Heavily-Favored Teams On the Road |
5-0 | 3-0 | ||
| NOTE: Visiting team performance was better in GAME 2 when comparable teams played. | ||||
| Type of Contest | Game 1 | Game 2 | ||
| Home Record | Visiting Record | Home Record | Visiting Record | |
| From Table 4: All Opponents, regardless of strength |
18-30 (0.37 winning %) |
16-32 (0.33 winning %) |
||
| 2 Comparable Teams (Same Cluster) |
6-8 (0.43 winning %) |
8-6 (0.57 winning %) |
5-1 (0.83 winning %) |
1-5 (0.17 winning %) |
| 1 Slightly Favored Team (1 Cluster Separation) |
13-5 (0.72 winning %) |
5-13 (0.28 winning %) |
14-10 (0.58 winning %) |
10-14 (0.42 winning %) |
| 1 Heavily Favored Team (2 Cluster Separation) |
11-5 (0.69 winning %) |
5-11 (0.31 winning %) |
13-5 (0.72 winning %) |
5-13 (0.28 winning %) |
| Records of Heavily-Favored Teams On the Road |
5-3 | 5-4 | ||
| NOTE: Visiting team performance tended to be better in GAME 1 than GAME 2 when comparable teams played. This influence did not carry over to games where one opponent was a light or heavy favorite. In fact, home teams beat heavily-favored teams 4 times (Appalachian State State had 2 of these wins). Appalachian State had 4 wins in conference all season. Three (3) of these wins were ‘upset wins’ on their home court. |
||||
- Women’s Soccer: visiting teams tended to perform better in Game 1 than Game 2 overall all three scenarios.
- Women’s Volleyball: visiting teams tended to perform better in Game 2 than Game 1 for comparable and slightly favored teams. Further, heavily favored road teams were more often expected winners in both Games 1 and 2.
- Women’s Basketball: visiting teams tended to perform better in Game 2 when comparable teams played.
- Men’s Basketball: visiting teams tended to perform better in Game 1 than Game 2 when comparable teams played. This influence did not carry over to games where one opponent was a light or heavy favorite.
As illustrated above and in Tables 6-9, there was not a substantial reduction in road team performance in Game 2 of two-game road trips when the quality of the opponent was introduced into the analysis in women’s soccer, women’s volleyball and women’s basketball. However, men’s basketball teams tended to win more often during Game 1 than Game 2 when playing comparable teams. When two evenly-matched teams played Game 2, the home team won 83% of the time. And, heavily-favored road teams were upset in 37% of the time (3 of 8 games) in Game 1 and 44% of the time in Game 2 (4 of 9 games). Interestingly, Sun Belt Conference men’s basketball teams scored 3.25 fewer points (on average) in Game 2 than Game 1. This is consistent with Winston’s (15) finding that NBA teams scored 4 fewer points in back-to-back games. However, only 1 of the 6 games of comparable teams was a 4-point differential in this study. So, scoring 4 more points would have only changed the outcome of one game.
CONCLUSIONS
Athletic administrators scheduling multi-game road trips for their teams may wonder if the scheduling format affects team performance and competitiveness. In this one-season analysis (2016-2017) of one conference (Sun Belt Conference), any influence of the two-game road trip format tends to be sport specific and not broad-based. Team performance in Game 2 was comparable to Game 1 in women’s soccer, women’s basketball, and men’s basketball. Game 2 performance was improved in women’s volleyball. There was not a significant reduction in road team performance in Game 2 of two-game road trips when the quality of the opponent was introduced into the analysis in women’s soccer, women’s volleyball, and women’s basketball. However, men’s basketball teams tended to win more often during Game 1 rather than Game 2 when looking playing comparable opponents.
The travel partner scheduling model maximizes player rest, reduces travel time, and minimizes missed class time. This study suggests its implementation does not impact team competitiveness, particularly during Game 2 of the road trip. As such, athletic administrators do not face a trade-off: save time and money but be lesser-competitive in the back-end of a road trip. Conference personnel and university athletic administrators may take comfort that their drive to control costs and enhance the student-athlete experience is not impacting the competitiveness of their teams.
APPLICATIONS IN SPORT
High school student-athletes are used to playing single games and returning home that evening as their leagues have a relatively small geographic footprint. Essentially, they ride a bus to a neighboring town, compete, and ride back home that evening. These same student-athletes experience increased travel demands when they enter college sports due to the expanded geographic footprint of most collegiate sport conferences. Consider the geographic footprints for the earlier referenced athletic conferences:
- Colonial Athletic Association (Massachusetts to North Carolina)
- Sun Belt Conference (South Carolina to Texas)
- Conference USA (West Virginia to Florida to Texas)
In order to reduce travel costs and missed class time, some conferences have embraced the two-game road trip with regional travel partners. As noted above, any effects of this scheduling format on team competitiveness tend to be sport-specific. Coaches and athletic administrators are looking for ways to enhance the student-athlete experience while ensuring team competitiveness within their conference. Coaches attempt to control any variable they think might give them an advantage. They may pay particular attention to the intensity of team practices, player nutrition, and player rest during road trips to guard against tired athletes during game two of a two-game road trip. A coach may attempt to ‘keep them off of their feet’ or try to rest players and conserve energy. Side travel that introduces extended periods of walking (such as a trip to a local museum or attraction) may also be minimized to conserve player energy.
It is recognized here that this research examined a single conference (Sun Belt Conference) for a single season (2016-17) across four sports. At a minimum, this study can serve as a baseline for further analysis. Power 5 or Autonomy Group Conferences (ACC, BIG 10, BIG 12, PAC 12, and SEC) may be less inclined to use the two-game road trip format for a variety of reasons, including larger travel budgets, larger distance between member schools, and others). However, other NCAA conferences (the “Group of Five” members and other mid-major conferences) face greater pressure for cost control.
The use of two-game road trips provides a cost-effective solution while concurrently reducing student-athlete time away from campus. For this analysis, the two-game road trip does not appear to introduce a systemic and significant home field advantage, particularly for Game 2 contests. Any influences tend to be sport-specific. The feared cost/benefit trade-off of ‘saving money’ versus ‘being competitive on the road’ is not prevalent in this analysis. Conference personnel and university athletic administrators may take comfort in their drive to control costs that they are not diminishing the competitiveness of their teams.
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