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Turf Management, Athletic-field Conditions, and Injuries in High School Football

The condition of a playing field is not only of aesthetic importance, but it also may affect play and player safety.
Updated:
December 21, 2022
In This Article

    High School Athletic-Field Conditions and Injuries

    The wide range of turfgrass conditions existing on high school athletic fields in Pennsylvania may reflect: i) procedures used during construction, ii) past and current maintenance practices, iii) intensity of use, or iv) a combination of these factors. The condition of a playing field is not only of aesthetic importance, but it also may affect play and player safety.

    The prevention of athletic injuries, particularly in a violent contact sport such as football, is of major concern to most educational institutions. At the college level, comparison of natural turf and artificial surfaces in regard to football injuries has received attention in recent years, but differences in quality of the turf on grassed fields has been a topic that has received only minor attention.

    Wilcox, Fox, and Beyer (1965) reported a pronounced reduction in practice-field injuries at one high school when practice sessions were moved from a dry and heavily compacted area to a field where the turf had been adequately maintained. Of course, the reduction in injuries may have been influenced by factors not under consideration. Also, conclusions based on data from a single high school may not be valid for other schools. Sanderson (1979) stated that soil compaction of athletic fields is a leading cause of football players' knew injuries. He advocated a full maintenance program of aerification, overseeding¹, fertilization, and weed control to provide a playing surface that would tend to reduce the incidence and severity of injuries.

    Well-controlled studies of the effects of turf management practices on the incidence of injuries in football are needed. The purposes of this study were: i) to evaluate conditions of high school game and practice fields and determine the relation of field conditions to maintenance programs; ii) to determine if a relationship existed between field conditions and the incidence of field-related injuries in high school football, and iii) to provide professional advice concerning turf management programs in an effort to improve the quality of high school football fields.

    Materials and Methods

    Selection of Participants

    In May 1981, all high school athletic trainers who were active members of the Pennsylvania Athletic Trainers' Association were mailed a brief description of the proposed project. Trainers used the enclosed response card to indicate whether their school agreed to participate in the study and whether they were willing to provide the required reports of injury throughout the 1981 football season.

    While most trainers expressed interest in the study, only 12 schools were willing to participate. This sample came from various locations across the state and provided 24 fields (12 game fields and 12 practice fields) for evaluation. Two of the schools did not provide a complete record of injuries, so injury results and correlations involving injuries are based on data from 10 schools. Field-condition and maintenance comparisons reflect evaluations at all 12 schools, however.

    Injury Reporting

    All injuries to football players in the sample schools were reported through the National Athletic Injury/Illness Reporting System (NAIRS), established by The Pennsylvania State University in 1974. NAIRS receives weekly reports, submitted by team trainers or physicians, of injuries and illnesses sustained by members of an athletic team during practice and during competition². In this study injuries and illnesses were classified by NAIRS into four categories, as follows

    1. Minor -- any reportable injury/illness (other than dental or head injuries) that did not prevent an athlete from returning to practice or competition for longer than seven days following the injury or illness.
    2. Significant -- all head and dental injuries (regardless of time lost from play or practice), and any injury/illness that kept an athlete from returning to play or practice for longer than seven days.
    3. Major -- any significant injury/illness that prevented a player's return to practice or competition for 21 days or longer.
    4. Severe -- any permanently disabling injury, such as paraplegia.

    Injuries/illnesses were reported on standard forms to NAIRS and coded into the system' data bank. Trainers of the cooperating schools included in their reports the location of the activity at the time of injury (playing field, practice field, or elsewhere) and their opinions about the likelyhood of a casual relationship of playing surface to the injury (definitely related, perhaps/possibly related, or definitely not related).

    At the end of the season, data collected during the football season of the 12 schools -- nature and category of injuries, condition of the field (wet, frozen, etc.) when the injury occurred, and opinion of the trainer as to the relationship of playing-surface condition to occurrence or severity of the injury -- were compiled for study and analysis by the authors of this study.

    Injury reports from two of the schools were not complete, and these schools were not included in the comparisons of injuries to conditions of playing surfaces.

    Field Assessment

    School representatives provided information about maintenance practices and uses over the previous year. Maintenance practices inlcuded fertilization, liming, aeration (core cultivation), mowing, irrigation, overseeding, and control of weeds, insects, and diseases. Uses included football games and practices, other varsity and intramural sports, physical education classes, band practices, community activities, and other activities. Estimated numbers of occurences for each use wer obtained.

    Game and practice fields were evaluated twice -- first in August, prior to or during preseason football practice, and again in November as the season was ending. Inspections and evaluations were made by two turfgrass specialists from the College of Agriculture. Data were collected on kinds and amounts of turfgrasses, kinds and amounts of weeds, total vegetative cover, turfgrass density, total weed coverage, smoothness of surface, vegetative clumps, and stones on the surface. the recorded ratings represented a concensus. Data for subjective evaluations were assigned code numbers for use in statistical analysis. Evaluators inspected game fields at nine areas (between inbound hashmarks and near each sideline at midfield and near each goal line). Areas inspected on the practice fields were selected to represent obvious differences in the playing surface.

    As part of the initial field inspection, each field was also characterized according to undulations (free-draining swales), depressions (which could hold water), crown or slope, and internal drainage. In contrast to ratings for natural undulations or depressions, the field roughness rating was an indication of holes and other irregularities caused by play. Also during the initial visit, soil samples were taken for determinations of soil textural class, bulk density, pH, and available phophorus (P) and potassium (K). Samples for bulk density represented the more intensively used portions of the fields. The percentages of sand, silt, and clay and the textural class of the surface soil were obtained by particle-size analysis using a hydrometer method (Bouyoucos, 1962). Bulk density, the mass of dry soil per unit bulk volume, was determined from 10 soil cores, each an inch in diameter and 2.5 inches long. Samples from the surface 2.5 inches were used for pH determinations using a 1:1 soil-to-water paste, and for phosphorus (P) and potassium (K) determinations using Bray No. 1 and neutral, normal ammonium acetate extractants, respectively.

    Upon completion of the second evaluation, Penn State specialists prepared a letter that described field conditions and suggested maintenance and/or renovation programs for fields at each school.

    Characterization of Data

    The number of injuries occurring during games, practices, and practice games (with the rate of injuries per 1000 exposures³) was compiled for the total sample of 10 schools and for each individual school. Data were summarized to indicate the number of reported injuries on each field, the relation of injuries to field conditions, and the number of injuries within various body-part categories.

    Spearman rank-order correlations for non-parametric data were determined to ascertain the possible relationships among the incidences of injury, field characteristics, and maintenance practices. Variables used in correlations were as follows:

    Tables.. .

    When field conditions varied across a field, ratings used for correlations were representative of the area between inbound hash marks.

    Results and Discussion

    Reported Injuries

    A total of 210 injuries were reported by the 10 participating schools. Of these injuries, 96 occurred in varsity or junior varsity (JV) games, 4 in practice games, and 110 during scheduled practices. Of these injuries, 152 were classified as minor, 58 were significant. Of the significant injuries reported, 23 were major. No severe injuries were reported. The 10 schools had a total of 35, 5155 exposures during the football season (31,816 and 3, 339 in practices and games, respectively). Rates of injuries per 1000 exposures were 4.21 for minor injuries, 1.59 for significant injuries, and 0.65 for major injuries. A breakdown of these injuries, as reported by school, is presented in Table 1.4

    Numbers and percentages of reported injuries, by type field, are presented in Table 2. Although the number of injuries sustained in practices was about the same as that in games, the number of exposures during practices, based on the average size of squads (practice or game) and the number of sessions (practice of games), was nearly 10 times as great as the number of game exposures. However, the severity of contact and the intensity of play during the game probably were considerably greater than for the practice sessions.

    Of the 210 injuries reported, 12 (5.7 percent) were definitely field-related, 15.2 percent were considered possibly field-related, and 76.7 percent were definitely not field-related (Table 3.) In the judgement of the trainers responsible for recording the data on location at the time of injury, a total of 44 injuries (20.9 percent) may have been caused by poor field conditions. On the basis of these data, it can be estimated that as many as 20 percent of the reported injuries could have been prevented or perhaps rendered less severe by more favorable field conditions. Safety considerations should thus be an incentive for the construction and maintenance of high-quality playing surfaces, for practice as well as for games.

    Injuries are listed, according to the body-parts involved, in Table 4. Within each body-part category, injuries are further classified according to their relation to field conditions. As would be expected, most of the injuries judged to be related to field conditions involved the lower extremities (i.e. hip/leg, knee, and ankle/foot). Also, it should be noted that the majority of injuries to lower extremities were classified as definitely not field-related or, in other words, they were considered by the athletic trainers in attendance at the time of occurrence to be injuries likely to have been sustained regardless of field conditions.

    Field Characteristics

    Field Maintenance

    Data collected on maintenance of game and practice fields indicated considerable variation between fields at a particular school as well as among fields at different schools. Although practice fields were much more intensively used than were the game fields, they received less care.

    Mowing heights were similar on game and practice fields, but game fields received more nitrogen fertilization and more aeration than practice fields (Table 5). Game fields averaged 2.0 lb N/1000 ft² compared to 0.2 lb N/1000 ft² for practice areas.

    Herbicides were used for weed control on 25 percent of the game fields; not one school reported use of weed killers on practice fields. All fields receiving weed-control chemicals were treated with a pre-emergence crabgrass herbicide and a combination herbicide for broadleaf weed control.

    Eighty-three percent of the 24 fields involved in this study were overseeded in the spring. Only 75 percent of the 12 playing fields and 25 percent of the 12 practice fields were aerated. Not one of the schools had access to a disk seeder, and only a few of the schools had access to aerators. Some of the fields were thus overseeded without adequate seedbed preparation. Without the seed-to-soil contact provided by proper preparation of the seedbed, success of the seeding is highly unlikely.

    Field Conditions

    Game fields were in better condition than practice fields. In general, game fields had smoother surfaces, lower bulk densities (less compact soil), fewer weeds, more vegetative cover, and more dense turf (Table 5). The better conditions on the game fields are no doubt a reflection of better construction and maintenance practices. Soils on all fields were medium or fine textured and were distributed among the following textural classes: loam, silt loam, clay loam, silty clay loam, silty clay (Fig. 1). Kentucky bluegrass was the predominant turfgrass species on most fields. Perennial ryegrass had been used to overseed fields; in some instances, the ryegrass population approached or exceeded that of Kentucky bluegrass.

    textural_triangle.jpg

    Weed cover decreased during the season primarily because of the poor wearing qualities of species such as clover and knotweed, and loss of summer annuals such as crabgrass, goosegrass, and knotweed. Lower ratings for vegetative cover during the second of two evaluations were associated with reductions in weed populations. Turf density likewise decreased during the season; most practice and some game fields were nearly or entirely without vegetative cover between the inbound hash marks at the second of two field evaluations.

    Additional or more effective maintenance practices (i.e., aeration, fertilization, overseeding, and weed control) were needed on most of the game fields and on all practice fields surveyed in this study. Practice fields were used more than game fields, but received lower levels of maintenance. All practice fields in this study were considered to be in poor condition, thus presenting surfaces potentially more conducive to player injury.

    Relationships between Various Field Variables

    Correlations were used to indicate a relationship between two variables. Two variables may be correlated because on directly affects the other, or because both are influenced by an external factor. A negative correlation coefficient indicates that one variable decreased as the other increased.

    Statistically significant correlations based on data from all fields are listed in Table 6. In general, correlations indicated that the fields with better maintenance practices also had better field conditions. Good maintenance practices seemed to be a carryover of good construction methods. For instance, factors associated with higher rates of nitrogen (N) fertilization were fewer undulations and depressions, more aeration, lower bulk density, fewer weeds, and greater cover early in the season. Fields with the most depressions also had more undulations, a rougher surface, more stones, less dense turf, less cover, less N fertilization, and severer use.

    Good cover prior to the season was associated with higher N fertilization, more aeration, greater density, less roughness, fewer depressions and stones, and less use. At the conclusion of the season, better cover was associated with good cover in August and November, smoothness, fewer depressions and undulations, lack of stones, less use, and fewer weeds in August.

    The highest correlations with use ratings were the negative correlations with density in August and with cover in August and November. Cover in November gave the best correlation with the overall field rating.

    Correlations were also determined for game fields only (Table 7) and practice fields only (Table 8). Fewer significant correlations occurred when the sample was limited to either game of practice fields; however, the results tended to support the relationships found when all fields were considered. The complexity of interpreting correlations can be illustrated by the negative correlation between aeration and November density for game fields. One might question the result because it seems that a better-aerated field should better support a turfgrass stand. On the other hand, fields that have a less-dense cover are in greater need of aeration, and the data suggest that they are getting more.

    Recommendations for Field Improvement

    Good field conditions were associated with good management programs. Some fields, however, were poor because of construction methods and needed renovation beyond that provided by normal maintenance practices. Suggestions for maintenance and renovation programs were sent to each school following the second field evaluation. Subsequent visits have indicated that those schools that followed these suggestions have substantially improved their fields.

    Methods of getting information about construction, maintenance, and renovation of fields to those in charge of field management must be implemented or improved. Valuable information is published in various forms (Beard, 1984; Daniel, 1982; Harper, 1983; Schmidt, 1984; Shearman, 1982), but it may not be reaching those having the greatest need. Chalmers (1982) reported that a survey of football field managers in Virginia indicated that 78 percent were not happy with the turf quality on their fields and 94 percent wanted to improve the quality of the fields. County extension personnel, Extension specialists, turf consultants, representatives of turf equipment and supply companies, and others involved in turfgrass management can and usually are quite pleased to provide guidance and information about athletic field maintenance problems.

    The quality of construction and maintenance used for school fields may be related to socioeconomic factors within the community. Our results indicated a trend for better maintenance practices on the better constructed fields. Such a trend may have been coincidental, but it also could have been related to income or administrative knowledge and interest within a school district. The subject would be a worthwhile inclusion in future studies of high school athletic fields.

    Literature Cited

    • Beard, J. B. 1984. Better sports fields, Part 2: Maintenance. Grounds Maint. 19(5):10.
    • Bouyoucos, G. J. 1962. Hydrometer method improved for making particle size analyses of soils. Agron. J. 54:464.
    • Chalmers, D. R. 1982. Why not better athletic fields in your community? Tech. Turf Topics (Apr): 7. Virginia Tech, Blacksburg, VA.
    • Daniel, W. 1982. Preparing and maintaining your grass athletic fields. Athl Purch and Facil 6(4):39.
    • Harper, J. C. 1983. Athletic fields: specification outline, construction, and maintenance. Coop. Extens. Ser., Penn State Univ., University Park, PA. 32 pp.
    • Sanderson, W. W. 1979. Football field game plan can help reduce injuries. Athl Purch and Facil 4(5):54.
    • Schmidt, R. E. 1984. Better sports fields. Part 1: Construction. Grounds Maint. 19(4):26.
    • Shearman, R. C. 1982. Athletic field maintenance in a nutshell. Nebraska Turfgrass Found. Turfgrass Bull. 3(3):5. Dept. of Hort., Univ. Nebraska, Lincoln, NE.
    • Wilcox, H., H. Fox, and R. Beyer. 1965. Safer athletic fields. Athl. J. 45(10):34.

    Appendix Tables

    Table 1. Classification of injuries and rates/1000 exposures for 10 participating high schools (1981 scholastic football season).

    School Injury classification Varsity or JV game Varsity practice Practice game Rate/1000 exposures*
    A Minor 4 7 0 1.62
    Significant 3 5 0 1.41
    Major 0 1 0 0.20
    B Minor 2 4 0 2.25
    Significant 6 4 1 3.75
    Major 1 2 0 1.12
    C Minor 2 6 0 2.92
    Significant 1 1 0 0.73
    Major 1 0 0 0.36
    D Minor 3 5 0 2.19
    Significant 3 3 0 1.64
    Major 1 1 0 0.55
    E Minor 4 13 0 5.66
    Significant 2 5 0 2.33
    Major 1 1 0 1.33
    F Minor 12 8 0 3.18
    Significant 4 1 0 0.84
    Major 3 0 0 0.50
    G Minor 5 0 0 1.66
    Significant 0 0 0 0.00
    Major 0 0 0 0.00
    H Minor 21 11 0 17.29
    Significant 3 3 0 3.24
    Major 0 2 0 1.08
    I Minor 0 1 0 0.23
    Significant 2 5 2 2.05
    Major 2 2 1 1.14
    J Minor 18 25 1 15.02
    Significant 1 3 0 1.37
    Major 1 1 0 0.68

    *Mean rates per 1000 exposures for total samples of 10 schools: minor cases = 4.21; significant cases = 1.59; major cases = 0.65.

    An exposure is defined as one student participating in a single practice session or game, without regard to duration of his or her playing or practice time.

    Table 2. Fields, by major use, on which reported injuries occurred (10 high schools reporting, 1981 scholastic football season).

    Number of injuries Percent of injuries
    Practice fields 98 46.7
    Game fields 99 47.1
    Other fields 8 3.8
    Incomplete information 5 2.4
    Total 210 100.0

    Table 3. Relation of reported injuries to field conditions (10 high schools reporting, 1981 scholastic football season).

    Number of injuries Percent of injuries
    Definitely related 12 5.7
    Possibly related 32 15.2
    Definitely not related 161 76.7
    Incomplete information* 5 2.4
    Total 210 100.0

    *Reporting trainer listed the injury without stating possible connection to field conditions.

    Table 4. Body parts injured and the number and percentages of each category judged to be field-related (10 high schools reporting, 1981 scholastic football season).

    Body part injured Definitely related Possibly related Definitely not related Not reported Total
    Number % Number % Number % Number % Number %
    Head/Neck/
    Spine
    0 0.0 2 8.0 22 88.0 1 4.0 25 11.9
    Face/Scalp 1 10.0 0 0.0 9 90.0 0 0.0 10 4.8
    Shoulder/Arm 0 0.0 2 10.5 17 89.5 0 0.0 19 9.0
    Forearm/Hand 1 2.8 3 8.3 30 83.3 2 5.6 36 17.1
    Torso 0 0.0 1 7.1 13 92.9 0 0.0 14 6.7
    Hip/Leg 2 5.4 4 10.8 30 81.1 1 2.7 37 17.6
    Knee 5 15.6 8 25.0 19 59.4 0 0.0 32 15.2
    Ankle/Foot 3 9.4 12 37.5 17 53.1 0 0.0 32 15.2
    Miscellaneous 0 0.0 0 0.0 4 80.0 1 20.0 5 2.4
    Total 12 5.7 32 15.2 161 76.7 5 2.4 210 100.00

    Table 5. Characteristics of game and practice fields of 12 Pennsylvania high schools (1981 scholastic football season).

    Game fields Practice fields
    Variable (unit or code) Range Average Range Average
    Soil properties
    Sand, % 13-52 27 8-41 26
    Silt, % 36-56 47 34-58 44
    Clay, % 12-40 27 21-48 30
    Bulk density, g/cc 1.28-1.58 1.40 1.33-1.64 1.46
    pH 6.6-7.6 7.1 5.7-7.1 6.7
    Available P, lb/A 84-182 143 38-186 110
    Available K, lb/A 343-772 538 312-920 562
    Field Surface
    Undulations, 0 to 4, 4 = extreme 1-3 1.7 2-4 2.5
    Depressions, 0 to 4, 4 = extreme 1-2 1.2 1-4 2.2
    Roughness, 0 to 4, 4 = extreme 1-3 1.9 1-3 2.8
    Stones, 0 to 2, 2 = many 0 0 0-1 0.4
    Vegetative clumps, 0 to 2, 2 = many 1-3 1.4 1-3 1.6
    Vegetative Characteristics
    August cover 0 to 9, 9 = 100% 2-8 6.3 0-7 1.9
    November cover, 0 to 9, 9 = 100% 1-5 3.2 0-7 0.7
    August weeds, 0 to 4, 4 = 76 to 100% 0-4 2.4 1-4 2.8
    November weeds, 0 to 4, 4 = 76 to 100% 0-3 1.3 0-3 1.5
    August density, 0 to 3, 3 = dense 1-2 1.7 0-2 0.8
    November density, 0 to 3 3 = dense 0-1 0.8 0-2 0.4
    Maintenance Factors
    Nitrogen fertilization, lb/1000 ft2 0-5 2.0 0-1 0.2
    Aeration (core cultivation), passes/year 0-50 8.4 0-4 1.0
    Mowing height, inches 1.8-3.0 2.1 1.5-3.0 2.2
    Other
    Other field-related use, 0 to 3, 3 = severe 1-3 1.8 3.0 3.0
    Overall rating, 0 to 3, 3 = excellent 0-3 1.3 0-2 0.2

    Table 6. Significant correlations for data collected from all playing and practice fields (12 Pennsylvania high schools, (1981 scholastic football season).

    Variables Correlation coefficient, r
    Between Soil Properties
    sand vs silt -.46*
    sand vs clay -.73**
    silt vs bulk density -.57**
    Between Surface Characteristics
    undulations vs depressions .64**
    undulations vs roughness .54**
    depressions vs roughness .66**
    depressions vs stones .70**
    roughness vs vegetative clumps .48*
    roughness vs stones .48*
    Between Vegetative Characteristics
    August cover vs November cover .82**
    August cover vs August density .88**
    August cover vs November density .68**
    November cover vs August density .84*
    November cover vs November density .80**
    November cover vs August weeds -.48*
    August weeds vs November density -.42*
    August weeds vs November weeds .65**
    August density vs November density .65**
    Between Maintenance Factors
    N fertilization vs aeration .64**
    Maintenance vs Field Variables
    N fertilization vs bulk density -.44*
    N fertilization vs undulations -.46*
    N fertilization vs depressions -.51*
    N fertilization vs August cover .45*
    N fertilization vs August weeds -.56**
    aeration vs August cover .48*
    aeration vs August weeds -.55**
    mowing height vs available K -.55**
    Soil vs Surface or Vegetative Variables
    sand vs November weeds .53**
    clay vs November weeds -.56**
    bulk density vs August density -.50*
    Surface vs Vegetative Variables
    Undulations vs November cover -.47*
    depressions vs August cover -.57**
    depressions vs November cover -.54**
    depressions vs August density -.61**
    roughness vs August cover -.59**
    roughness vs November cover -.70**
    roughness vs August density -.64**
    roughness vs November density -.52**
    stones vs August cover -.65**
    stones vs November cover -.58**
    stones vs August density -.61**
    vegetative clumps vs November weeds .50*
    Use vs Field Variables
    use vs pH -.49*
    use vs depressions .46*
    use vs stones .44*
    use vs August cover -.80**
    use vs November cover -.72**
    use vs August density -.70**
    use vs November density -.46*
    Overall Rating vs Other Variables
    rating vs undulations -.59**
    rating vs depressions -.55**
    rating vs roughness -.66**
    rating vs stones -.48*
    rating vs August cover .66**
    ratings vs November cover .91**
    ratings vs August density .65**
    ratings vs November density .63**
    rating vs August weeds -.53**
    ratings vs N fertilization .63**
    ratings vs aeration .49*
    ratings vs use -.61**

    *5% level of significance

    **1% level of significance

    Table 7. Significant correlations for data collected from game fields of 12 Pennsylvania high schools, (1981 scholastic football season).

    Variables Correlation coefficient, r
    Between Soil Properties

    sand vs clay

    -.75**
    silt vs bulk density -.78**
    pH vs P -.58*
    pH vs K -.68*
    P vs K .65*
    Between Surface Characteristics
    undulations vs depressions .59*
    Between Vegetative Characteristics
    August cover vs August density .76**
    November cover vs August density .68*
    November cover vs November density .60*
    August density vs November density .63*
    August weeds vs November weeds .76**
    Maintenance vs Field Variables
    N fertilization vs available K .60*
    N fertilization vs August weeds -.82**
    aeration vs November density -.66*
    mowing height vs bulk density .61*
    mowing height vs pH .64*
    Soil vs. Surface or Vegetative Variables
    sand vs vegetative clumps .67*
    sand vs November cover -.60*
    clay vs vegetative clumps -.80**
    clay vs November weeds -.63*
    Surface vs Vegetative Variables
    vegetative clumps vs November cover -.71**
    vegetative clumps vs November density -.70*
    Overall Rating vs Other Variables
    rating vs November cover .68*

    *5% level of significance

    **1% level of significance

    Table 8. Significant correlations for data collected from practice fields of 12 Pennsylvania high schools, (1981 scholastic football season).

    Variables Correlation coefficient, r
    Between Soil Properties
    sand vs clay -.83**
    Between Surface Characteristics
    depressions vs stones .79**
    roughness vs vegetative clumps .61*
    Between Vegetative Characteristics
    August cover vs November cover .70*
    August cover vs August density .77**
    August cover vs November density .60*
    November cover vs November density .82**
    November density vs August weeds -.70*
    Maintenance vs Field Variables
    N fertilization vs pH .59*
    aeration vs August weeds -.70*
    mowing height vs pH -.79**
    Soil vs Surface or Vegetative Variables
    sand vs November weeds .61*
    clay vs August weeds -.61*
    clay vs November weeds -.66**
    bulk density vs August density -.72**
    available P vs November cover -.67*
    available P vs November density -.78**
    available P vs August weeds .67*
    Surface vs Vegetative Variables
    stones vs August cover -.68*
    stone vs August density -.68*
    Overall Rating vs Other Variables
    rating vs November cover .74**
    rating vs August density .58*
    rating vs November density .64*

    *5% level of significance

    **1% level of significance

    J. C. Harper
    Penn State University
    C. A. Moorehouse
    Penn State University
    D. V. Waddington
    Penn State University
    W. E. Buckley
    Penn State University