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If We Build It, Will They Come? The Effect of New Athletic Facilities on Recruiting Rankings for Power Five Football and Men's Basketball Programs

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Title: If We Build It, Will They Come? The Effect of New Athletic Facilities on Recruiting Rankings for Power Five Football and Men's Basketball Programs
Language: English
Authors: Huml, Matt Ryan (ORCID 0000-0002-9951-4495), Pifer, N. David, Towle, Caitlin, Rode, Cheryl R.
Source: Journal of Marketing for Higher Education. 2019 29(1):1-18.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 18
Publication Date: 2019
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Physical Education Facilities, College Athletics, Student Recruitment, Team Sports, Males, College Students, Facility Improvement, School Choice
DOI: 10.1080/08841241.2018.1478924
ISSN: 0884-1241
Abstract: College athletics is currently in the midst of a building boom in which universities are competing with each other to reach an always-increasing standard of lavish athletic facilities. While these facilities are costing in the tens or hundreds of millions of dollars, little research is examining the return on investment for athletic programs. The purpose of this study was to examine the effect of new athletic facilities on recruiting rankings for Power Five football and men's basketball programs. Data was collected on athletic facilities newly constructed or renovated from 2005 through 2015 at Power Five NCAA Division I programs. Using LSDV fixed effects regression models, results found a lack of significant improvement within football and basketball recruiting rankings following the completion of new athletic facilities, but some significance in the two years before the project was completed. Significant control variables also highlighted the effects that coaching changes can have on recruiting.
Abstractor: As Provided
Entry Date: 2019
Accession Number: EJ1218707
Database: ERIC
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  Value: <anid>AN0137166012;ii501jan.19;2019Jun27.04:27;v2.2.500</anid> <title id="AN0137166012-1">If we build it, will they come? The effect of new athletic facilities on recruiting rankings for power five football and men's basketball programs </title> <p>College athletics is currently in the midst of a building boom in which universities are competing with each other to reach an always-increasing standard of lavish athletic facilities. While these facilities are costing in the tens or hundreds of millions of dollars, little research is examining the return on investment for athletic programs. The purpose of this study was to examine the effect of new athletic facilities on recruiting rankings for Power Five football and men's basketball programs. Data was collected on athletic facilities newly constructed or renovated from 2005 through 2015 at Power Five NCAA Division I programs. Using LSDV fixed effects regression models, results found a lack of significant improvement within football and basketball recruiting rankings following the completion of new athletic facilities, but some significance in the two years before the project was completed. Significant control variables also highlighted the effects that coaching changes can have on recruiting.</p> <p>Keywords: Athletic facilities; college athletics; recruiting; arms race</p> <p>We are in the midst of a nation-wide building boom at colleges and universities. Higher education across the United States spent over $11 billion on new facilities in each year from 2010 to 2012, more than double the funding spent in 2000 (Marcus, [<reflink idref="bib25" id="ref1">25</reflink>]). In recent years, this spending has only increased. In 2015, higher education spent over $11.5 billion on facilities upgrades and 21 million square feet of new facilities, a new all-time high (Dodge Research and Analytics, [<reflink idref="bib6" id="ref2">6</reflink>]). The State of New York recently planned to implement $10 billion in new campus construction through 2019 (New York |Building Congress, [<reflink idref="bib33" id="ref3">33</reflink>]). These new facilities are not concentrated in one area, as universities are rapidly building new student unions, residence halls, dining facilities, and other non-academic facilities (Marcus, [<reflink idref="bib26" id="ref4">26</reflink>]).</p> <p>The timing of this rapid build-up of facilities also coincides with significant increases in tuition costs for students pursuing a college degree. Universities are building new facilities with the hope state legislators will provide the necessary funding to cover the costs (Marcus, [<reflink idref="bib25" id="ref5">25</reflink>]). State legislators are often balking at these requests, leading to universities raising tuition costs and fees to pay for the new facilities rather than canceling the project (Marcus, [<reflink idref="bib25" id="ref6">25</reflink>], [<reflink idref="bib26" id="ref7">26</reflink>]). Marcus ([<reflink idref="bib25" id="ref8">25</reflink>]) quoted a director at a national research organization as saying, 'people at universities want to leave a legacy ... you can leave a legacy in terms of improved rankings, you can leave a legacy in winning national football championships, and you can leave a legacy by building a lot of buildings' (p. 1). These options outline the possibility of university administrators combining two of these legacy-leaving activities: building new facilities to support athletic success.</p> <p>Even during this explosion of new educational facilities, the biggest and most expensive facilities being constructed are in the name of intercollegiate athletics (Hobson & Rich, [<reflink idref="bib15" id="ref9">15</reflink>], [<reflink idref="bib16" id="ref10">16</reflink>]). In light of these expenditures, it is becoming necessary for athletic departments to show a return on investment. Such returns could include increased long-term revenues, improved recruiting success (i.e. higher-ranked recruits), improved perception of the campus from incoming non-athlete students (as well as student-athletes), increased improvements in student-athletes already enrolled at the school (i.e. strength gains from better weight room), and many others. In this analysis, changes in recruiting rankings were analyzed as the primary return on investment. The analysis of recruiting performance was viewed as being appropriate given the preliminary role that recruiting plays in on-field success (Caro, [<reflink idref="bib5" id="ref11">5</reflink>]), and the literature that further links athletic success to a variety of institutional benefits (Anderson, [<reflink idref="bib2" id="ref12">2</reflink>]; McEvoy, [<reflink idref="bib30" id="ref13">30</reflink>]; Pope & Pope, [<reflink idref="bib35" id="ref14">35</reflink>]).</p> <p>As such, the purpose of this study is to examine the effect of new athletic facilities on recruiting rankings for Power Five (Atlantic Coast Conference, Southeastern Conference, Big 12, Big Ten, and Pacific-12) football and men's basketball programs. This was accomplished using a series of Least Squares Dummy Variable (LSDV) multiple regression models that looked at the relationship between seasonal changes in recruiting rankings as they related to the time period surrounding the completion of an athletic facilities project. Before that, we will review the reasons university/athletic facilities are being constructed on college campuses and research on institutional selection factors impacting student and student-athlete choice of attendance.</p> <hd id="AN0137166012-2">Literature Review</hd> <p></p> <hd id="AN0137166012-3">Growth of University Facilities</hd> <p>The construction of new facilities on college campuses is carried out for different reasons. The number of students attending college has steadily increased since 2000, requiring greater physical resources for universities to accommodate the growth (National Center for Education Statistics, [<reflink idref="bib32" id="ref15">32</reflink>]). The changing generations of attending students also have different preferences, requiring college campuses to adapt in order to maximize their desirability (Rickes, [<reflink idref="bib40" id="ref16">40</reflink>]). One emerging trend within the rapid growth of new campus facilities is the focus on building multipurpose structures. These new facilities allow for a wide variety of activities, including dining, socializing, studying, recreation and exercise, and relaxation, within the same facility (Brady, [<reflink idref="bib3" id="ref17">3</reflink>]). Coupled with the importance of attracting future students, these facilities provide valuable functionality for student learning. Greater investment in physical facilities has also been shown to increase the student's use of campus resources (Huesman, Brown, Lee, Kellogg, & Radcliffe, [<reflink idref="bib18" id="ref18">18</reflink>]; Reynolds, [<reflink idref="bib39" id="ref19">39</reflink>]). Even for facilities not directly connected to classrooms, such as recreational centers, increased usage has displayed a positive effect on their academic success in college (Huesman et al., [<reflink idref="bib18" id="ref20">18</reflink>]).</p> <p>New facility design is also increasing the flexibility of interior design to cater towards future generations of students. These modifications and upgrades to existing facilities include furniture that can easily be moved to accommodate gatherings and study groups, more diverse and accessible dining options, retail components such as coffee shops, banks, and travel services, and state-of-the-art technology (Brady, [<reflink idref="bib3" id="ref21">3</reflink>]). Millennials now influence space planning, design, and construction and will continue to transform higher education as they return to campus as faculty and staff (Rickes, [<reflink idref="bib40" id="ref22">40</reflink>]). These generational characteristics and traits of Millennials, combined with the awareness of space, are driving physical change on college and university campuses. This influence creates challenges for campus designs that arose during the boomer years, such as requiring a major overhaul of academic support spaces, instructional rooms, libraries, student centers, residence halls, and even dining areas (Howe & Strauss, [<reflink idref="bib17" id="ref23">17</reflink>]). It also highlights the potential future challenges faced by campuses currently re-designing their facilities for the current generation, as future student generations will possess different design preferences, leading to unending campus design changes in an effort to meet the expectations of future students.</p> <p>The building of university facilities is also a strong component of college student recruitment (Magnusen, Kim, Perrewé, & Ferris, [<reflink idref="bib23" id="ref24">23</reflink>]). Successful recruitment of college students is essential to the institution's success, whether by recruiting the brightest students into the university footprint or helping fulfill the institution's mission (Letawsky, Schneider, Pedersen, & Palmer, [<reflink idref="bib22" id="ref25">22</reflink>]). Facilities are also known to impact student satisfaction with their university. Currently enrolled college students self-reported on their satisfaction with a variety of university characteristics, revealing that overall satisfaction with the university was significantly correlated to student satisfaction with their university facilities (Gruber, Fuß, Voss, & Gläser-Zikuda, [<reflink idref="bib14" id="ref26">14</reflink>]). To influence students' choices and align with current students' preferences, universities have been focusing on human scale design and aesthetics during the design of new facilities (Martin, [<reflink idref="bib28" id="ref27">28</reflink>]). In addition, facilities are noticed not only by future students, but by prospective college employees as well. For example, facilities can be crucial to attracting key research personnel, or to providing an environment where knowledge creation can thrive (Price, Matzdorf, Smith, & Agahi, [<reflink idref="bib38" id="ref28">38</reflink>]). On the contrary, another study perceived the facilities build-up on college campuses as a form of 'arms race', functioning as a rising tide by raising the profile of all universities with limited differentiation between schools, therefore negating any benefit from improved facilities (Rickes, [<reflink idref="bib40" id="ref29">40</reflink>]). This narrative has been frequently mentioned regarding the build-up of athletic department facilities.</p> <hd id="AN0137166012-4">Growth of athletic facilities</hd> <p>While controversial, an important public perception entity is the university's athletic department (Fort, [<reflink idref="bib8" id="ref30">8</reflink>]). National Collegiate Athletic Association (NCAA) Division I athletic programs were a $6 billion enterprise in 2010. Attendance for college sporting events has steadily increased for over forty years (Fort, [<reflink idref="bib8" id="ref31">8</reflink>]). Power Five athletic departments, primarily within football and men's basketball, have also seen significant increases in revenues from media rights deals and payouts received for qualifying for widely-publicized postseason events (Fort, [<reflink idref="bib8" id="ref32">8</reflink>]). As intercollegiate athletic success increases, a university often receives an increase in donations flowing into both the university and athletic department, further increasing yet another revenue source (Martinez, Stinson, Kang, & Jubenville, [<reflink idref="bib29" id="ref33">29</reflink>]). Besides the rare exception, intercollegiate athletics is often part of a larger non-profit entity, meaning an increase in revenues which allows the organization to increase their expenses and greater flexibility on where to spend these new revenues.</p> <p>While many NCAA Division I athletic departments have seen significant increases in revenue in recent years, their costs have increased in a similar fashion (Fort, [<reflink idref="bib9" id="ref34">9</reflink>]). At the root of these rising costs are multi-million-dollar coaching contracts, demand for more staff, increased scholarship commitments, and the construction/renovation of athletic facilities that can compete with rival institutions (Brewer, McEvoy, & Popp, [<reflink idref="bib4" id="ref35">4</reflink>]; Huml, Hancock, & Bergman, [<reflink idref="bib19" id="ref36">19</reflink>]; Hutchinson, Nite, & Bouchet, [<reflink idref="bib20" id="ref37">20</reflink>]). While coaching salary increases have caught significant media attention, these increases are much smaller in comparison to the cost of new athletic facilities. When one lavish athletic facility is constructed, the race to assemble a bigger and better facility is already underway as a 'sell' to prospective recruits (Hobson & Rich, [<reflink idref="bib15" id="ref38">15</reflink>]). This type of facilities spending is one of the biggest reasons otherwise self-sufficient athletic departments can run deficits (Hobson & Rich, [<reflink idref="bib15" id="ref39">15</reflink>]). Football stadiums and basketball arenas must now be complemented by practice facilities, upgraded locker rooms, extravagant players' lounges, and luxury suite options (Hobson & Rich, [<reflink idref="bib16" id="ref40">16</reflink>]). In the past decade, many Power Five athletic departments have built baseball stadiums, volleyball courts, soccer fields, golf practice facilities, and ice hockey arenas from revenues largely derived from football and, to a lesser degree, men's basketball programs (Hobson & Rich, [<reflink idref="bib16" id="ref41">16</reflink>]). This is partially due to a limited number of well-known athletic boosters (i.e. Phil Knight – Oregon; T. Boone Pickens – Oklahoma State) willing to provide the necessary funding to ensure their respective universities have the best athletic facilities in the country. For athletic departments without these type of generous donors, facilities upgrades mean turning to students (tuition or fees), government bodies, or lenders to help cover the expenses (Hobson & Rich, [<reflink idref="bib16" id="ref42">16</reflink>]). In counter, Fort ([<reflink idref="bib9" id="ref43">9</reflink>]) discussed how the decisions to increase facility growth within athletic departments are similar to the decision-making process of most businesses, where the increase in spending occurs most frequently at the point that can maximize the organization's benefit. For example, many Power Five schools have seen an increase in athletic department revenues, therefore empowering the school to increase spending within the department in order to further maximize their revenue stream. This would be especially true for schools who can convince prominent donors to 'foot the bill', as the school could then (potentially) increase their revenues without an initial financial commitment.</p> <hd id="AN0137166012-5">Student choice of school</hd> <p>As prospective students apply and consider their college options, university facilities are known to be one of the most important factors in their decision-making processes (Price et al., [<reflink idref="bib38" id="ref44">38</reflink>]; Shah, Nair, & Bennett, [<reflink idref="bib42" id="ref45">42</reflink>]). Indeed, the ability to visit and see a university's available facilities was considered one of the most important tasks for choosing the right school among students visiting college campuses (Galotti & Mark, [<reflink idref="bib12" id="ref46">12</reflink>]). Prospective students also lean on the opinions created by their friends and family, which can also be shaped by the facilities offered by the institution (Price et al., [<reflink idref="bib38" id="ref47">38</reflink>]). Rickes ([<reflink idref="bib40" id="ref48">40</reflink>]) claims the quantity and quality of campus facilities are influential in students' assessments of which particular institution to attend. Another study found quality of campus facilities as the sixth-most important factor (out of 18) when assessing institutional characteristics (Reynolds, [<reflink idref="bib39" id="ref49">39</reflink>]), while a different study found facility-related characteristics only behind price and major-related materials when deciding on a college to attend (Maringe, [<reflink idref="bib27" id="ref50">27</reflink>]). Not all facilities were important to prospective students, as they highlighted the importance of facilities housing their major courses, library, and residence halls compared to others (Rickes, [<reflink idref="bib40" id="ref51">40</reflink>]). Universities also have to be cautious of 'over-promising' their university facilities, as students may visit the campus and be disappointed the facilities did not live up to the expectations created in the promotional materials (Price et al., [<reflink idref="bib38" id="ref52">38</reflink>]). Student demographics and outcomes have also been shown to impact their preferences of university facilities when choosing which school to attend (Reynolds, [<reflink idref="bib39" id="ref53">39</reflink>]). Female students were found to be more critical of academic facilities available to students, as they stressed greater importance on on-campus residential facilities, facilities related to their major, library, instructional spaces, the student center/union, and open spaces; conversely, males were more interested in lab space, classroom technology, and athletic facilities (Reynolds, [<reflink idref="bib39" id="ref54">39</reflink>]).</p> <p>Additionally, students are more willing to consider a university following the on-field success of the institution's athletic programs (McEvoy, [<reflink idref="bib30" id="ref55">30</reflink>]; Pope & Pope, [<reflink idref="bib35" id="ref56">35</reflink>]). Studies have shown both an increase in applications and an increase in the quality of student applying to programs that have achieved success in athletics (Anderson, [<reflink idref="bib2" id="ref57">2</reflink>]; Pope & Pope, [<reflink idref="bib35" id="ref58">35</reflink>]). Also, team success in the school's football program may increase the perception of the school's academic reputation (Anderson, [<reflink idref="bib2" id="ref59">2</reflink>]), which has also been found to be an important determinant of student attendance (Perna, [<reflink idref="bib34" id="ref60">34</reflink>]). Schools also see an increase of applications from student sub-populations that can assist in diversifying their overall student population, such as African American and out-of-state students (Pope & Pope, [<reflink idref="bib36" id="ref61">36</reflink>]). These findings highlight the importance of recruiting highly regarded student-athletes to the institution to increase their likelihood of fielding successful athletic programs.</p> <hd id="AN0137166012-6">Student-athlete choice of school</hd> <p>The long-term success of an athletic program begins with effective recruitment of exceptional student-athletes who represent themselves well not only on the field, but in the classroom as well (Foster & Huml, [<reflink idref="bib10" id="ref62">10</reflink>]; Judson, James, & Aurand, [<reflink idref="bib21" id="ref63">21</reflink>]; Weight & Huml, [<reflink idref="bib44" id="ref64">44</reflink>]). Minimal research has been conducted on the decision-making process for student-athletes when choosing an institution of higher education (Goss, Jubenville, & Orejan, [<reflink idref="bib13" id="ref65">13</reflink>]). Student-athletes consider their potential coaching staff and subsequent scholarship offers when considering their college choices (Adler & Adler, [<reflink idref="bib1" id="ref66">1</reflink>]). Student-athletes also assess their university's academic characteristics, such as the university's academic reputation, degree program offerings, and surrounding community (Letawsky et al., [<reflink idref="bib22" id="ref67">22</reflink>]). Similar to non-athlete students, student-athletes highlighted the importance of campus facilities, and in particular their team-affiliated athletic facilities, in their decision-making processes (Judson et al., [<reflink idref="bib21" id="ref68">21</reflink>]). A study assessing important factors for domestic and international student-athletes found athletic facilities to be the seventh-most important factor (out of 35) when choosing a university (Popp, Pierce, & Hums, [<reflink idref="bib37" id="ref69">37</reflink>]).</p> <p>These previous studies highlight the self-reported results of the decision-making process for student-athletes choosing their university-of-choice, but raise the need for further examination of whether these factors can increase the quality of student-athletes wanting to commit to the university. There are studies showing the quality of athletic facilities is an important deciding factor for prospective student-athletes, yet there is a gap in the field on whether the quality of athletic facilities can attract more talented student-athletes. This topic is becoming a more important question for university and athletic administrators, as the amount of financial resources being committed to these capital projects for intercollegiate athletics has significantly increased in recent years (Brewer et al., [<reflink idref="bib4" id="ref70">4</reflink>]; Huml et al., [<reflink idref="bib19" id="ref71">19</reflink>]). This study can also address the need for greater insight into the student-athlete recruitment process and athletic administrators' hopes of providing a more successful athletic program as it pertains to on-field success, which has previously been perceived as an area needing additional clarity (Judson et al., [<reflink idref="bib21" id="ref72">21</reflink>]).</p> <p>If the improvement of athletic facilities correlates with greater quality of student-athletes wanting to attend the university, it can increase the likelihood of athletic success, and therefore provide additional positive factors to convince future student-athletes (Dumond, Lynch, & Platania, [<reflink idref="bib7" id="ref73">7</reflink>]). This is often echoed by coaches and athletic administrators, who frequently mention how the new athletic facility will help with recruiting student-athletes (Ryan, [<reflink idref="bib41" id="ref74">41</reflink>]). When examining quotes, improved recruiting is often the first thing being mentioned, whether through the new facilities allowing the sport program to recruit with their peers 'on a level playing field' (Whittry, [<reflink idref="bib45" id="ref75">45</reflink>]) or to compete with the best teams in the conference (McGranahan, [<reflink idref="bib31" id="ref76">31</reflink>]).</p> <hd id="AN0137166012-7">Method</hd> <p></p> <hd id="AN0137166012-8">Data</hd> <p>The facilities data for this study were collected from press releases posted on the schools' official athletic webpages following the announcement or completion of a project. The data were initially recorded as the year in which a project was completed and classified within two categories. The first category was termed 'direct' facilities improvements and included projects closely related to student-athletes' athletic performances (e.g. weight rooms and practice facilities, playing field and stadium improvements). The second set included the 'indirect' facility investments that were classified as projects not directly related to athletic performance (e.g. academic centers and dormitories). In total, there were 57 (33 direct, 24 indirect) facility improvements recorded for men's basketball and 107 (72 direct, 35 indirect) for football between the years of 2005 and 2015. These decisions were further confirmed by an active athletic administrator working within major gifts at a Power Five program.</p> <p>The measurable outcome data in this analysis consisted of the composite team recruiting rankings published annually by <emph>247sports.com</emph>. This website serves as a widely-recognized database for recruiting rankings in the NCAA's top sports and is lent additional reliability through its use of a composite measure that aggregates rankings from a variety of sources. The resulting rankings therefore range on a continuous scale from 1 (top-ranked team from a given year in terms of recruits) to <emph>n</emph>, with <emph>n</emph> being the worst-ranked recruiting class from a given season. These archived rankings reliably date back to 2002 for football and 2003 for men's basketball. Another reputable database for sports statistics, <emph>sports-reference.com</emph>, was used to obtain information (winning percentages, coaching changes, etc.) relevant to the control variables that were used in the study.</p> <hd id="AN0137166012-9">Sample</hd> <p>Before conducting the analyses, the data were split into two samples, one consisting of an unbalanced panel of men's basketball data with 43 teams and 593 seasonal observations, and the other containing the football data with 54 teams and 805 seasonal observations. In both samples, an individual observation consisted of a team's recruiting rankings for the given season and other variables (including facility construction) that were applicable to that specific season. The men's basketball panel contained data from the 2004 to 2017 seasons for each program that was included, while the football panel ran from 2003 to 2017. Only Power Five programs that underwent a direct and/or indirect facility construction or renovation project during these respective timeframes were included. For purposes of clarity, it is important to note that the Power Five label is frequently applied to the five most popular and highest revenue-generating NCAA Division-I FBS conferences (SEC, Big Ten, Big 12, Pac-12, and ACC). It is within these high-level conferences where the most money is spent on facilities and where the competition on the recruiting front and playing field is generally the most intense (Fulks, [<reflink idref="bib11" id="ref77">11</reflink>]). As such, the programs within these conferences are positioned as the ideal environment for examining the relationships between facility investments and player recruitment. According to the data collected by this study, nearly $8 billion was spent on direct and indirect facility improvements for Power Five football ($6 billion) and basketball ($2 billion) programs between 2003 and 2016. Whether or not the entities and individuals making these contributions are receiving any sort of return on their investments is part of what makes the current analysis a worthwhile endeavor.</p> <hd id="AN0137166012-10">Variables</hd> <p>The season-to-season differences in recruiting rankings (<emph>RecRANK</emph>) served as the primary dependent variable in this study. Because lower values are representative of more proficient recruiting (e.g. a ranking of 1 is better than a ranking of 50), negative values of this variable were indicative of greater success on the recruitment trail. Nonetheless, the inherent variability in these rankings meant that additional dependent variables could be included in order to supplement the initial measure. These measures included the average <emph>247sports</emph> numerical rating of a program's recruiting class for a given season (<emph>RecAVG</emph>; 0.00 to 1.00, with 1.00 being the best rating) and each program's recruiting ranking within its conference (<emph>ConfRANK</emph>; 1 to <emph>n</emph>, with <emph>n</emph> being the number of teams in the conference). It is also important to note in both samples that the panels were unbalanced due to a program failing to bring in any new or meaningful recruits for a specific season. This meant that a small selection of observations received a ranking of 'NA' and were discarded from the analysis. As such, the year-to-year changes in recruiting rankings skipped any seasons that were not available and resumed with the following year.</p> <p>In terms of the independent variables, the construction and renovation projects were represented categorically in each seasonal observation as being two seasons before (<emph>PRE_2</emph>), one season before (<emph>PRE_1</emph>), one season after (<emph>POST_1</emph>), or two seasons after (<emph>POST_2</emph>) completion in relation to the observed season. In this manner, the variabilities in the recruiting rankings could be assessed in relation to the stage of completion that a given project was at. Separate forms of these variables were present for the direct and indirect improvements (e.g. <emph>POST_1D</emph> and <emph>POST_1I</emph>). Additional independent variables controlled for a team's conference winning percentage in the prior season (<emph>ConfWIN%</emph>), whether or not the coach was new (<emph>NEWCOACH</emph>) or in their second full season (<emph>COACH2</emph>), and whether or not the school had just changed conferences (<emph>NEWCONF</emph>). These variables were included for the underlying impacts they might have on seasonal changes to the recruiting rankings, outside of what was already being accounted for by the facility projects. Although they are not reported, categorical fixed effects for each of the schools in the samples were also incorporated in the least squares dummy variable models. All analyses were conducted using IBM SPSS statistical software version 24.0. A full list of the variables and their descriptions can be found in Table 1.</p> <p>Table 1. Descriptions of independent and dependent variables.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Variable(s)</td><td>Description</td></tr></thead><tbody><tr><td><italic>Independent variables</italic></td></tr><tr><td><italic>ConfWin%</italic></td><td>A team's winning percentage from conference play during the preceding season; used to control for on-field/on-court success potentially leading to better recruits.</td></tr><tr><td><italic>PRE_2D and PRE_2I</italic></td><td>A binary, categorical variable denoting whether an observed season was taking place two seasons prior to the completion of a direct (D) or indirect (I) facility upgrade.</td></tr><tr><td><italic>PRE_1D and PRE_1I</italic></td><td>A binary, categorical variable denoting whether an observed season was taking place one season before the completion of a direct (D) or indirect (I) facility upgrade.</td></tr><tr><td><italic>POST_1D and POST_1I</italic></td><td>A binary, categorical variable denoting whether an observed season was taking place immediately after the completion of a direct (D) or indirect (I) facility upgrade.</td></tr><tr><td><italic>POST_2D and POST_2I</italic></td><td>A binary, categorical variable denoting whether an observed season was taking place two seasons after the completion of a direct (D) or indirect (I) facility upgrade.</td></tr><tr><td><italic>NEWCOACH</italic></td><td>A binary, categorical variable indicating whether or not a new coach was in place for the observed season.</td></tr><tr><td><italic>COACH2</italic></td><td>A binary, categorical variable indicating whether or not a coach was in his second full season at the helm; this way, a fuller effect of his potential impact could be captured.</td></tr><tr><td><italic>NEWCONF</italic></td><td>A binary, categorical variable indicating whether or not a team was new to a conference for an observed season.</td></tr><tr><td><italic>Dependent variables</italic></td></tr><tr><td><italic>RecRANK</italic></td><td>The change in a team's <italic>247sports</italic> national recruiting ranking from the previous season; the top-ranked team assumes a value of 1; as such, negative values indicate improvement.</td></tr><tr><td><italic>RecAVG</italic></td><td>The change in the average <italic>247sports</italic> recruiting ranking for a team's individual signees; each individual player is rated on a scale from 0.00 to 1.00; as such, positive values indicate improvement.</td></tr><tr><td><italic>ConfRANK</italic></td><td>The change in a team's <italic>247sports</italic> conference recruiting ranking from the previous season; the top ranked team in the conference assumes a value of 1; as such, negative values indicate improvement.</td></tr></tbody></table> </ephtml> </p> <hd id="AN0137166012-11">Model</hd> <p>In order to assess whether or not the facilities projects had an effect on programs' recruiting rankings, least squares dummy variable (LSDV) multiple regression models with individual fixed effects for the schools were employed. These fixed effects were necessary in order to reduce omitted variable bias by accounting for the unobservable heterogeneities that likely existed within each program. The models used in this study were derivatives of the following equation:</p> <p>Graph</p> <p>where <emph>i</emph> = 1, ... <emph>n</emph> is the individual (school) index, <emph>t</emph> = 1, ... <emph>T</emph> is the time index, <emph>β</emph> represents the parameters to be estimated, is representative of the various individual error components, and is an indiosyncratic error term assumed to be independent from both the independent variables () and . If the are correlated with the independent variables, as is often the case, then a fixed effects model can be used to estimate the as an additional set of <emph>n</emph> parameters to help control for any school-specific attributes that were not included as variables in the model. For this specific study, the following model was examined:</p> <p>Graph</p> <p>where all of the previously defined variables across each <emph>i</emph> and <emph>t</emph> were used to estimate the <emph>β</emph> parameters, and is representative of school <emph>i</emph>'s fixed effect.</p> <hd id="AN0137166012-12">Results</hd> <p></p> <hd id="AN0137166012-13">Descriptive statistics</hd> <p>Before looking at the results of the regression models, descriptive statistics can help shed light on how the recruiting rankings might change in relation to a facility project. As such, the mean values and standard deviations of the raw, national recruiting rankings within each time period of the facility variables were calculated and presented in Table 2. A preliminary review suggests there were limited differences in the averages across the four time periods in football. In basketball, however, a look at the direct facility improvements shows the rankings declined rather drastically as the project neared completion. Indeed, the average recruiting ranking for basketball teams undergoing a direct facility enhancement in the two seasons prior to completion (<emph>PRE_2</emph>) season was 81.36. In the season leading up to completion (<emph>PRE_1</emph>) the average fell to 46, and again to 41.52 and 41.21 in the first (<emph>POST_1</emph>) and second (<emph>POST_2</emph>) seasons that followed, respectively. Figure 1 further visualizes these findings.</p> <p>Graph: Figure 1. Mean changes in men's basketball recruiting rankings in the time periods surrounding completion of a direct facilities project.</p> <p>Table 2. Descriptive statistics of recruiting rankings across time period and sample.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Time Period</td><td>Direct Football</td><td>Indirect Football</td><td>Direct Basketball</td><td>Indirect Basketball</td></tr><tr><td><italic>μ</italic></td><td>S.D.</td><td><italic>μ</italic></td><td>S.D.</td><td><italic>μ</italic></td><td>S.D.</td><td><italic>μ</italic></td><td>S.D.</td></tr></thead><tbody><tr><td>PRE_2</td><td char=".">28.42</td><td char=".">20.17</td><td char=".">30.66</td><td char=".">19.41</td><td char=".">81.36</td><td char=".">90.85</td><td char=".">63.00</td><td char=".">68.82</td></tr><tr><td>PRE_1</td><td char=".">31.50</td><td char=".">19.89</td><td char=".">33.69</td><td char=".">18.87</td><td char=".">46.00</td><td char=".">35.96</td><td char=".">46.37</td><td char=".">34.29</td></tr><tr><td>POST_1</td><td char=".">30.54</td><td char=".">20.07</td><td char=".">30.40</td><td char=".">15.71</td><td char=".">41.52</td><td char=".">35.27</td><td char=".">44.83</td><td char=".">33.17</td></tr><tr><td>POST_2</td><td char=".">30.25</td><td char=".">19.44</td><td char=".">30.00</td><td char=".">16.31</td><td char=".">41.21</td><td char=".">29.66</td><td char=".">53.08</td><td char=".">47.81</td></tr></tbody></table> </ephtml> </p> <hd id="AN0137166012-14">Empirical findings</hd> <p>Continuing, the LSDV regression models were used to analyze the effects of the independent variables, and in particular the facility projects, on yearly changes in the recruiting efforts of the selected Power Five men's basketball and football programs. The results of these models for the men's basketball teams are presented in Table 3. Looking at the national recruiting rankings in model (column) 1, it shows that both the <emph>PRE_2D</emph> and <emph>PRE_1D</emph> variables, signifying that a direct facility project was two seasons or one season away from completion, are significant. However, their effects move in opposite directions. <emph>PRE_2D</emph> shows that two seasons out from completion, teams tended to have rankings that were significantly worse than the previous season, <emph>β</emph> = 34.303, <emph>t</emph>(<reflink idref="bib538" id="ref78">538</reflink>) = 2.189, <emph>p</emph> = 0.029. The marginal significance of <emph>PRE_1D</emph>, on the other hand, shows that as direct facility projects were nearing their conclusion, the teams' recruiting rankings actually tended to improve, <emph>β</emph> = −30.134, <emph>t</emph>(<reflink idref="bib538" id="ref79">538</reflink>) = −1.918, <emph>p</emph> = 0.056. Shifting to the post-completion variables, neither one year after (<emph>POST_1D</emph>) nor two years after (<emph>POST_2D</emph>) completion of the project were significant. None of the indirect facility project variables were significant either. In fact, the only other independent variable to attain significance when looking at men's basketball national recruiting ranking (<emph>RecRANK</emph>) as the dependent variable was that a new coach was hired (<emph>NEWCOACH</emph>), which suggested that teams' recruiting classes tended to be about 22 rankings worse in their first season with a new coach, holding all other variables constant.</p> <p>Table 3. Results of the LSDV regression models for men's basketball.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>(1)</td><td>(2)</td><td>(3)</td></tr><tr><td><italic>β</italic></td><td>S.E.</td><td><italic>β</italic></td><td>S.E.</td><td><italic>β</italic></td><td>S.E.</td></tr></thead><tbody><tr><td>Constant</td><td char=".">−13.023</td><td char=".">22.85</td><td char=".">−0.006</td><td char=".">0.037</td><td char=".">−0.978</td><td char=".">1.373</td></tr><tr><td><italic>ConfWin%</italic></td><td char=".">0.015</td><td char=".">0.196</td><td char=".">0.000</td><td char=".">0.000</td><td char=".">0.001</td><td char=".">0.012</td></tr><tr><td><italic>PRE_2D</italic></td><td char=".">34.303**</td><td char=".">15.671</td><td char=".">0.006</td><td char=".">0.026</td><td char=".">0.690</td><td char=".">0.942</td></tr><tr><td><italic>PRE_1D</italic></td><td char=".">−30.134*</td><td char=".">15.712</td><td char=".">0.053**</td><td char=".">0.026</td><td char=".">0.220</td><td char=".">0.944</td></tr><tr><td><italic>POST_1D</italic></td><td char=".">−4.249</td><td char=".">15.678</td><td char=".">0.027</td><td char=".">0.026</td><td char=".">−0.139</td><td char=".">0.942</td></tr><tr><td><italic>POST_2D</italic></td><td char=".">1.287</td><td char=".">15.679</td><td char=".">−0.031</td><td char=".">0.026</td><td char=".">0.080</td><td char=".">0.942</td></tr><tr><td><italic>PRE_2I</italic></td><td char=".">−6.074</td><td char=".">18.402</td><td char=".">0.013</td><td char=".">0.030</td><td char=".">−0.387</td><td char=".">1.106</td></tr><tr><td><italic>PRE_1I</italic></td><td char=".">−7.543</td><td char=".">18.411</td><td char=".">−0.014</td><td char=".">0.030</td><td char=".">0.376</td><td char=".">1.107</td></tr><tr><td><italic>POST_1I</italic></td><td char=".">1.383</td><td char=".">18.392</td><td char=".">−0.004</td><td char=".">0.030</td><td char=".">−0.295</td><td char=".">1.105</td></tr><tr><td><italic>POST_2I</italic></td><td char=".">11.343</td><td char=".">18.406</td><td char=".">0.002</td><td char=".">0.030</td><td char=".">1.187</td><td char=".">1.106</td></tr><tr><td><italic>NEWCOACH</italic></td><td char=".">21.952**</td><td char=".">10.494</td><td char=".">−0.019</td><td char=".">0.017</td><td char=".">1.407**</td><td char=".">0.631</td></tr><tr><td><italic>COACH2</italic></td><td char=".">−15.009</td><td char=".">10.482</td><td char=".">0.014</td><td char=".">0.017</td><td char=".">−1.642***</td><td char=".">0.630</td></tr><tr><td><italic>NEWCONF</italic></td><td char=".">−28.422</td><td char=".">25.364</td><td char=".">−0.034</td><td char=".">0.041</td><td char=".">−0.809</td><td char=".">1.524</td></tr><tr><td><italic>R<sup>2</sup></italic></td><td char="."> 0.040</td><td char=".">0.028</td><td char=".">0.035</td></tr></tbody></table> </ephtml> </p> <p>Notes: (<reflink idref="bib1" id="ref80">1</reflink>) = <emph>RecRANK</emph>; (<reflink idref="bib2" id="ref81">2</reflink>) = <emph>RecAVG</emph>; (<reflink idref="bib3" id="ref82">3</reflink>) = <emph>ConfREC</emph>. *Significant at 90% level of confidence; **Significant at 95% level of confidence; ***Significant at 99% level of confidence; program fixed effects not reported but available upon request.</p> <p>Inserting the average national recruiting ranking (<emph>RecAVG</emph>) and conference recruiting ranking (<emph>ConfRANK</emph>) as the dependent variables (models 2 and 3 in Table 3), no major differences were noted. The average rating of the individual recruits in a given recruiting class, as seen in <emph>RecAVG</emph>, improved significantly in the season leading up to facility completion, <emph>β</emph> = 0.053, <emph>t</emph>(<reflink idref="bib538" id="ref83">538</reflink>) = 2.058, <emph>p</emph> = 0.04, suggesting the average rating of recruits improved by about 5% as projects wound down. In terms of inter-conference recruiting rankings, none of the facility-related variables were significant. However, the coach being newly hired (<emph>NEWCOACH</emph>) and the coach being in their second year (<emph>COACH2</emph>) variables were highly significant. While the <emph>NEWCOACH</emph> variable indicated that teams tended to regress within their conference in terms of recruiting when a coach was in his first season, it was interesting to note that in coaches' second seasons – likely the first full year in which they were able to get on the recruiting trail – men's basketball teams tended to significantly improve their inter-conference rankings, <emph>β</emph> = −1.642, <emph>t</emph>(<reflink idref="bib538" id="ref84">538</reflink>) = −2.607, <emph>p</emph> = 0.009.</p> <p>Shifting the focus to football, Table 4 shows the results of the three football-related models, beginning with the effects of the variables on the seasonal variations in national recruiting rankings (<emph>RecRANK</emph>). In this primary model, the two years before project completion (<emph>PRE_2D</emph>) variable is marginally significant, suggesting that two seasons before a project was completed, teams tended to improve between 3 and 4 positions in the recruiting rankings, <emph>β</emph> = −3.712, <emph>t</emph>(<reflink idref="bib739" id="ref85">739</reflink>) = −1.717, <emph>p</emph> = 0.086. The only other significant variables in the initial model were the team's winning percentage within conference (<emph>ConfWin%</emph>) and the coach being in their second year (<emph>COACH2</emph>) variables, the latter of which reaffirms what was seen in the men's basketball sample; that is, coaches significantly improved recruiting during their second season at the helm. The significance of a previous season's conference winning percentage also reaffirms what was found in a study by Caro ([<reflink idref="bib5" id="ref86">5</reflink>]), where on-field success was shown to have the expected positive impact on recruiting.</p> <p>Table 4. Results of the LSDV regression models for football.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>(1)</td><td>(2)</td><td>(3)</td></tr><tr><td><italic>β</italic></td><td>S.E.</td><td><italic>β</italic></td><td>S.E.</td><td><italic>β</italic></td><td>S.E.</td></tr></thead><tbody><tr><td>Constant</td><td char=".">8.269</td><td char=".">4.663</td><td char=".">−0.007</td><td char=".">0.007</td><td char=".">1.390***</td><td char=".">0.813</td></tr><tr><td><italic>ConfWin%</italic></td><td char=".">−9.259***</td><td char=".">2.888</td><td char=".">0.012***</td><td char=".">0.004</td><td char=".">−1.498</td><td char=".">0.504</td></tr><tr><td><italic>PRE_2D</italic></td><td char=".">−3.712*</td><td char=".">2.161</td><td char=".">0.001</td><td char=".">0.003</td><td char=".">−0.517</td><td char=".">0.377</td></tr><tr><td><italic>PRE_1D</italic></td><td char=".">3.031</td><td char=".">2.164</td><td char=".">−0.003</td><td char=".">0.003</td><td char=".">0.479</td><td char=".">0.377</td></tr><tr><td><italic>POST_1D</italic></td><td char=".">−0.073</td><td char=".">2.148</td><td char=".">0.002</td><td char=".">0.003</td><td char=".">−0.097</td><td char=".">0.375</td></tr><tr><td><italic>POST_2D</italic></td><td char=".">−0.229</td><td char=".">2.147</td><td char=".">−0.002</td><td char=".">0.003</td><td char=".">0.181</td><td char=".">0.374</td></tr><tr><td><italic>PRE_2I</italic></td><td char=".">−2.224</td><td char=".">3.056</td><td char=".">0.001</td><td char=".">0.004</td><td char=".">−0.337</td><td char=".">0.533</td></tr><tr><td><italic>PRE_1I</italic></td><td char=".">1.833</td><td char=".">3.047</td><td char=".">−0.004</td><td char=".">0.004</td><td char=".">0.458</td><td char=".">0.532</td></tr><tr><td><italic>POST_1I</italic></td><td char=".">−3.449</td><td char=".">3.045</td><td char=".">0.009**</td><td char=".">0.004</td><td char=".">−0.615</td><td char=".">0.531</td></tr><tr><td><italic>POST_2I</italic></td><td char=".">−1.585</td><td char=".">3.079</td><td char=".">−0.004</td><td char=".">0.004</td><td char=".">−0.555</td><td char=".">0.537</td></tr><tr><td><italic>NEWCOACH</italic></td><td char=".">2.610</td><td char=".">1.666</td><td char=".">−0.005**</td><td char=".">0.002</td><td char=".">0.486*</td><td char=".">0.291</td></tr><tr><td><italic>COACH2</italic></td><td char=".">−11.266***</td><td char=".">1.737</td><td char=".">0.011***</td><td char=".">0.002</td><td char=".">−1.895***</td><td char=".">0.303</td></tr><tr><td><italic>NEWCONF</italic></td><td char=".">−5.015</td><td char=".">4.974</td><td char=".">0.005</td><td char=".">0.007</td><td char=".">0.079</td><td char=".">0.868</td></tr><tr><td><italic>R<sup>2</sup></italic></td><td char="."> 0.097</td><td char=".">0.094</td><td char="."> 0.090</td></tr></tbody></table> </ephtml> </p> <p>Notes: (<reflink idref="bib1" id="ref87">1</reflink>) = <emph>RecRANK</emph>; (<reflink idref="bib2" id="ref88">2</reflink>) = <emph>RecAVG</emph>; (<reflink idref="bib3" id="ref89">3</reflink>) = <emph>ConfREC</emph>. *Significant at 90% level of confidence; **Significant at 95% level of confidence; ***Significant at 99% level of confidence; program fixed effects not reported but available upon request.</p> <p>Both the team's winning percentage within conference (<emph>ConfWin%</emph>) and the coach being in their second year (<emph>COACH2</emph>) variables retained significance across the team's average recruiting ranking (<emph>RecAVG</emph>) and average conference recruiting ranking (<emph>ConfRANK)</emph> models, while the newly hired coach (<emph>NEWCOACH</emph>) variable also attained significance in the expected direction opposite to coach in their second season (<emph>COACH2</emph>). In the second model containing average recruiting ranking (<emph>RecAVG</emph>) as the dependent variable, one year after project completion (<emph>POST_Y1I</emph>) gave the only evidence in the entire study that an indirect facility enhancement could improve an athletic program's recruiting efforts, <emph>β</emph> = 0.009, <emph>t</emph>(<reflink idref="bib739" id="ref90">739</reflink>) = 2.025, <emph>p</emph> = 0.043, albeit with a limited increase of just 0.9%. This finding and the marginally significant second year before project completion of a direct facility upgrade (<emph>PRE_2D</emph>) variable in model 1 aside, there was little consistent evidence of facility investment projects having any type of impact on football recruiting rankings. Overall, the results tended to support the findings that were initially reported in the descriptive statistics; that is, there were no abnormal fluctuations in football recruiting rankings in the four years that blanketed the completion of a facilities project.</p> <hd id="AN0137166012-15">Discussion</hd> <p>The trend of universities across the United States of building or upgrading facilities is showing few signs of abating; as such, it is important to understand the impact these facilities have toward attracting new students to campus. For several years, athletic departments have been continuously building bigger and better facilities for current and future student-athletes. Athletic programs, particularly football, are often considered the 'front porch' of the university. To this extent, a university is known first by its athletic accomplishments and then by its academic achievements (Fort, [<reflink idref="bib8" id="ref91">8</reflink>]). Therefore, having the best athletic facilities has been deemed imperative in order to compete and be successful.</p> <p>Nonetheless, while a large number of athletic programs have been building or completing facilities projects, this study found little to no impact on the recruiting of potential football or men's basketball recruits from the construction of new facility projects. Our findings echo a similar study that assessed the age of an athletic facility on the choices of prospective student-athletes, finding no significant relationship (Magnusen, McAllister, Kim, Perrewé, & Ferris, [<reflink idref="bib24" id="ref92">24</reflink>]). The direct football projects represented, by far, the largest number of projects during the time period of the study, yet their near-term returns in recruiting did not appear significant. In a surprise, <emph>PRE_2D</emph> was reported as marginally significant, finding that team recruiting rankings were slightly improved during the two-year mark before a facility project was completed. There were no significant differences for direct football projects during the year before facility completion, nor the first and second year after the facility was completed. Indirect projects were not found to be statistically significant outside of a small, 0.9% improvement in a class's rating in the season that followed a project's completion. While not a focus of our study, other independent variables did create significant differences as they pertain to team recruiting rankings. For example, the team's conference winning percentage in the previous year (<emph>ConfWin%</emph>) and the two seasons that followed a coaching change (<emph>NEWCOACH</emph> and <emph>COACH2</emph>) were found to be significant.</p> <p>On the other hand, men's basketball had slightly different results in terms of facility impacts. Similar to football, there were significant differences during the two years before a direct benefits project was completed. Differences were that, two years before the project's completion, team recruiting rankings became significantly worse. In the year before the facility was completed, however, the results were marginally significant in the opposite direction as team recruiting rankings and ratings improved. One potential explanation for these reverse findings is that schools may be initiating these projects following a down year or in conjunction with wide-scale improvements to the program. As men's basketball projects are often shorter in duration, it is not unreasonable to assume that the year preceding project completion (<emph>PRE_1D</emph>) is capturing the momentum that arises when these plans are panning out. No significant differences were reported for indirect projects, both before and after a project was completed. Looking at other independent variables, only a new coaching change (<emph>NEWCOACH</emph>) was found to be statistically significant, with team recruiting rankings getting significantly worse in their first year. The team's conference winning percentage (<emph>ConfWin%</emph>) and the second year after a coaching change (<emph>COACH2</emph>) were not statistically significant, aside from the latter being significant when looking at conference rankings as the dependent variable.</p> <p>These findings have numerous implications. The authors found several articles quoting football coaches who described their new facility construction projects as 'game changers' that would allow them to compete with the pre-eminent programs in their conference or region (Whittry, [<reflink idref="bib45" id="ref93">45</reflink>]). For many schools, this pitch is likely used on prominent boosters to convince them of the necessity of their donation and how they will help their sport programs improve their recruiting rankings and, indirectly, on-field success. Another unfortunate possibility is the potential of athletic administrators convincing their board of trustees to approve significant financial loans on the premise of how new and/or improved facilities would lead to improved on-field success for their football programs. While this study does not examine the potential recruiting ranking 'attrition' that could be faced by programs not upgrading their athletic facilities, it does dampen the belief that new football facilities lead to improved football recruiting rankings, particularly in the near term.</p> <p>Disregarding the revenue implications of the investigated projects, such as new stadiums or renovations/expansions, these findings do raise the question about value for indirect facility projects for the institution. With coaches and administrators quoted on how facilities are going to provide a return on improved recruiting, this study raises concerns as to whether these indirect facilities are the best way to spend additional monies, or whether affluent donors should be convinced to provide the necessary financial means, in order to build. These facilities can provide some residual educational benefits to student-athletes, depending on the project, but the lack of improved recruiting strikes a blow to their value, or may require institutions to explore whether specific projects are more fruitful for recruiting returns than others. This finding requires greater reflection on Fort's ([<reflink idref="bib9" id="ref94">9</reflink>]) principal/agent perspective; will universities reduce or cease construction on these types of indirect projects due to the lack of 'return'? Are they measuring some other form of benefit? Or maybe these projects are pushed towards athletic department donors with the 'fear factor' of falling behind their peers and/or conference affiliates?</p> <p>Another alternative explanation of the findings is that the addition of completed football and basketball facilities could have little to no effect on recruiting rankings because a large number of schools made upgrades around the same time. Prospective student-athletes would have many upgraded or new facilities to select from, meaning these elaborate projects would no longer become a deciding factor in their decision to attend. This situation personifies the saying, 'the rising tide lifts all boats,' as many universities are upgrading their facilities and negating the expected benefit. In essence, the results of this study support the conjecture that the numerous football-related projects begin to cancel each other out. With so many schools building football facilities, the only way to garner increased recruiting success may be to pursue uncommon facility upgrades. For example, a university may want to pursue creating/renovating more unique projects, such as athlete-only dorms or food halls, if they identify that their competitors are not addressing those facilities on their campuses.</p> <p>Unexpectedly, the significant differences pertaining to facility construction were confined to the one- or two-year time periods <emph>before</emph> the facility was completed (and only for facilities with direct benefits for their sport). This finding may imply that the institution reaps more recruiting-related benefits from the promotion of a future facility than once the facility is completed and presented in physical form to interested recruits. The differences between football, with significant differences being reported two years before the facility is completed, and basketball, with significant improvement occurring during the year before the facility is completed, may be due to the nature of their facility projects. Some of the football projects analyzed for this study necessitated a multi-year commitment in order to complete, such as football stadium expansion. These seemed less prevalent on the basketball side, with many projects focused on a new weight room or improvements to the indoor practice facility and locker room. This may explain the two years before direct facility completion (<emph>PRE_2D</emph>) improvement for football and the year before direct facility completion (<emph>PRE_1D</emph>) improvement for basketball. With many universities breaking down their facility projects into multiple phases, athletic departments may already be capturing this benefit by trying to lengthen the period where they can discuss the facilities upgrades to prospective recruits in basketball and football.</p> <p>It was further seen that direct facilities improvements had a larger impact on football and men's basketball recruiting rankings than indirect facility improvements. These types of facilities are likely more appealing to prospective student-athletes because they are perceived to directly affect the athletic performance of the student-athlete. Academic facilities and dormitories are necessary for all student-athletes, but are not as important to the athletic success of a football or men's basketball player. This might be why the indirect facilities improvements had less of an impact than the direct. Recruiting in men's basketball is different from football, in that a very small number of scholarship spots are awarded each year. This could lead to increased variability in the recruiting rankings and ratings that were examined as the outcome variables in this study.</p> <hd id="AN0137166012-16">Future research and limitations</hd> <p>While this study examined the impact of facility construction and renovations on recruiting rankings, there is much research that can still be done to better contextualize the build-up of facilities in collegiate athletics. For example, future studies might look at athletic programs that made decisions to upgrade facilities more recently, specifically football, compared to those that were at the forefront of the trend. It might be possible to further examine what features are being added to new facilities in an effort to differentiate, or improve, the newer facilities compared to previously constructed buildings used by other universities. Certain programs are now feeling the need to add barber shops, pool tables, and other 'luxury' amenities to ongoing facilities projects (Hobson & Rich, [<reflink idref="bib16" id="ref95">16</reflink>]); as such, it is worth seeing whether or not these increased expenditures are making a difference. Even if these lavish facilities have the potential for swaying the opinion of prospective student-athletes, coaches may not be properly leveraging these resources (Treadway et al., [<reflink idref="bib43" id="ref96">43</reflink>]). While challenging, a future study may want to further examine the effectiveness of coaches to harness the potential of new facilities to convince prospective recruits to choose their athletic program.</p> <p>This study also controlled for other program changes, such as the hiring of a new head coach and/or the team's success in the previous year's in-conference schedule. Many of these independent variables were found to be statistically significant. It is not surprising that on-field success and coaching changes altered recruiting success, but further examination in these areas is warranted, particularly as it relates to recruiting and coaching changes. Media members in recent years have talked frequently about the second-year coaching jump in men's football, and the findings of this study positioned improved recruiting as a potential driver of this phenomenon.</p> <p>A similar study could also further examine the study on the 'arms race' v. principals and agents discussion. While this study focused on athletic departments that are creating new facilities, a future study could examine the time periods where athletic departments do not partake in facility improvements and the subsequent effect on recruiting rankings. Part of the 'arms race' argument is predicated on the belief of schools that if they do not maintain the activities being pursued by their competitors, they will fall behind. Much of the previous attention has been focused on athletic department expenditures and the subsequent outcomes, but not on the lack of expenditures and subsequent outcomes. Going further, much of the attention on new facilities has been regarding new athletic facilities, leaving a gap in the literature regarding facilities designed for the general student population. With significant expenditures across all areas of college campuses, this would be a worthwhile venture for future researchers.</p> <p>Further examinations may also prove beneficial because this study does not come without limitations. The authors specifically examined new athletic facilities and tried to control for a handful of variables that are thought to impact recruiting rankings. That said, there is statistical 'noise' in the fact of recruiting being impacted by numerous activities that are more difficult to identify or quantify, such as university or athletic-related scandals, assistant coaches or other personnel staff leaving, programs being impacted by a strong or weak recruiting class in relation to the university's geographical location, or many other issues.</p> <p>Basketball recruiting is also a different process compared to football recruiting, and vice versa. Most importantly, football coaches are often filling 20–25 open scholarship spots, whereas basketball recruiting can be more volatile, with some years possessing no open scholarships and others with five or more scholarships available. Finally, this study did not report a robust explained variance, or <emph>R</emph> value, therefore limiting the value extracted from these results. This is likely because of the many different processes and outcomes that affect recruiting on a yearly basis. A future study may also want to examine the periods of time where athletic programs are not creating or revising their athletic facilities. With much of the attention focusing on the influence of new facility construction, it is just as important to measure the moments where an athletic program is not utilizing new facilities as a measure to influence prospective recruits. Even with this noise, we believe the number of instances of new/renovated facilities recorded for this study helps quieten some of this 'noise' to provide valuable insight into the impact of new facilities on recruiting. Perhaps future studies could expand into even larger samples, moving out of the Power Five and devising methods that are able to capture facility construction and renovation projects more thoroughly.</p> <p>In closing, university-wide facility spending will likely continue to increase as new and upgraded facilities attempt to meet the current needs of student-athletes and the student body as a whole. As expenses continue to outpace revenues, universities and athletic departments are going to be under increased scrutiny on how donations and tuition dollars are spent on facilities for students, as well as athletic-related facilities for prospective and current student-athletes. This study found minimal evidence that football facilities have a direct impact on near-term recruiting efforts; in basketball, however, there was some evidence that recruiting improves in the build-up to project completion. Future studies would be wise to take note of this study's recommendations and limitations as they delve further into this phenomenon.</p> <hd id="AN0137166012-17">Disclosure statement</hd> <p>No potential conflict of interest was reported by the authors.</p> <hd id="AN0137166012-18">ORCID</hd> <p> <emph>Matt Ryan Huml</emph> <ulink href="http://orcid.org/0000-0002-9951-4495">http://orcid.org/0000-0002-9951-4495</ulink> </p> <ref id="AN0137166012-19"> <title> References </title> <blist> <bibl id="bib1" idref="ref66" type="bt">1</bibl> <bibtext> Adler, P. A., & Adler, P. (1991). Backboards & blackboards: College athletes and role engulfment. New York, NY : Columbia University Press.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref12" type="bt">2</bibl> <bibtext> Anderson, M. L. (2017). The benefits of college athletic success: An application of the propensity score design. 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  Data: If We Build It, Will They Come? The Effect of New Athletic Facilities on Recruiting Rankings for Power Five Football and Men's Basketball Programs
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  Data: <searchLink fieldCode="AR" term="%22Huml%2C+Matt+Ryan%22">Huml, Matt Ryan</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-9951-4495">0000-0002-9951-4495</externalLink>)<br /><searchLink fieldCode="AR" term="%22Pifer%2C+N%2E+David%22">Pifer, N. David</searchLink><br /><searchLink fieldCode="AR" term="%22Towle%2C+Caitlin%22">Towle, Caitlin</searchLink><br /><searchLink fieldCode="AR" term="%22Rode%2C+Cheryl+R%2E%22">Rode, Cheryl R.</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Marketing+for+Higher+Education%22"><i>Journal of Marketing for Higher Education</i></searchLink>. 2019 29(1):1-18.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Label: DOI
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  Data: 10.1080/08841241.2018.1478924
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0884-1241
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: College athletics is currently in the midst of a building boom in which universities are competing with each other to reach an always-increasing standard of lavish athletic facilities. While these facilities are costing in the tens or hundreds of millions of dollars, little research is examining the return on investment for athletic programs. The purpose of this study was to examine the effect of new athletic facilities on recruiting rankings for Power Five football and men's basketball programs. Data was collected on athletic facilities newly constructed or renovated from 2005 through 2015 at Power Five NCAA Division I programs. Using LSDV fixed effects regression models, results found a lack of significant improvement within football and basketball recruiting rankings following the completion of new athletic facilities, but some significance in the two years before the project was completed. Significant control variables also highlighted the effects that coaching changes can have on recruiting.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2019
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1218707
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1218707
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/08841241.2018.1478924
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 18
        StartPage: 1
    Subjects:
      – SubjectFull: Physical Education Facilities
        Type: general
      – SubjectFull: College Athletics
        Type: general
      – SubjectFull: Student Recruitment
        Type: general
      – SubjectFull: Team Sports
        Type: general
      – SubjectFull: Males
        Type: general
      – SubjectFull: College Students
        Type: general
      – SubjectFull: Facility Improvement
        Type: general
      – SubjectFull: School Choice
        Type: general
    Titles:
      – TitleFull: If We Build It, Will They Come? The Effect of New Athletic Facilities on Recruiting Rankings for Power Five Football and Men's Basketball Programs
        Type: main
  BibRelationships:
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      – PersonEntity:
          Name:
            NameFull: Huml, Matt Ryan
      – PersonEntity:
          Name:
            NameFull: Pifer, N. David
      – PersonEntity:
          Name:
            NameFull: Towle, Caitlin
      – PersonEntity:
          Name:
            NameFull: Rode, Cheryl R.
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2019
          Identifiers:
            – Type: issn-print
              Value: 0884-1241
          Numbering:
            – Type: volume
              Value: 29
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Journal of Marketing for Higher Education
              Type: main
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