Skip to main content
Log in

Athletes’ perceptions of within-field variability on natural turfgrass sports fields

  • Published:
Precision Agriculture Aims and scope Submit manuscript

Abstract

Natural turfgrass sports field properties exhibit within-field variations due to foot traffic from play, field construction, management, and weather. Little is known about the influences these variations may have on athletes’ perceptions of field playability and injury risk. Information regarding athletes’ perceptions of within-field variability could be fundamental for identifying key surface properties important to athletes, which may also be useful for the progression and implementation of Precision Turfgrass Management on sports fields. A case study using mixed methods was conducted on a recreational-level turfgrass sports field to better understand athletes’ perceptions of within-field variability. Geo-referenced normalized difference vegetation index, surface hardness, and turfgrass shear strength data were obtained to create hot spot maps for identification of significant within-field variations. Walking interviews were conducted in situ with 25 male and female collegiate Club Sports rugby and ultimate frisbee athletes to develop knowledge about athletes’ perceptions of within-field variability. Field data, hot spot maps, and walking interview responses were triangulated to explore, compare, and validate findings. Athletes’ perceptions of within-field variability generally corresponded with measured surface properties. Athletes perceived within-field variations of turfgrass coverage and surface evenness to be most important. They expressed awareness of potential influences the variations could have, but not all athletes made behavior changes. Those who reported changing did so with regard to athletic maneuvers and/or strategy, primarily for safety or context of play. Spatial maps of surface properties that athletes identified could be used for Precision Turfgrass Management to potentially improve perceptions by mitigating within-field variability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Aldahir, P. C. F., & McElroy, J. S. (2014). A review of sports turf research techniques related to playability and safety standards. Agronomy Journal, 106(4), 1297–1308.

    Article  Google Scholar 

  • Aldous, D. E., Chivers, I. H., & Kerr, R. (2005). Player perceptions of Australian Football League grass surfaces. International Turfgrass Society Research Journal, 10, 318–326.

    Google Scholar 

  • Andersson, H., Ekblom, B., & Krustrup, P. (2008). Elite football on artificial turf versus natural grass: movement patterns, technical standards, and player impressions. Journal of Sports Sciences, 26(2), 113–122.

    Article  PubMed  Google Scholar 

  • Bell, G. E., Martin, D. L., Koh, K., & Han, H. R. (2009). Comparison of turfgrass visual quality ratings with ratings determined using a handheld optical sensor. HortTechnology, 19(2), 309–316.

    Article  Google Scholar 

  • Bell, M. J., & Holmes, G. (1988). The playing quality of association football pitches. Journal of the Sports Turf Research Institute, 61, 19–47.

    Google Scholar 

  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.

    Article  Google Scholar 

  • Bremer, D. J., Lee, H., Su, K., & Keeley, S. J. (2011). Relationships between normalized difference vegetation index and visual quality in cool-season turfgrass: I. Variation among species and cultivars. Crop Science, 51(5), 2212–2218.

    Article  Google Scholar 

  • Burillo, P., Gallardo, L., Felipe, J. L., & Gallardo, A. M. (2014). Artificial turf surfaces: Perception of safety, sporting feature, satisfaction and preference of football users. European Journal of Sport Science, 14(Suppl 1), S437–S447.

    Article  PubMed  Google Scholar 

  • Canaway, P. M., Bell, M. J., Holmes, G., & Baker, S. W. (1990). Standards for the playing quality of natural turf for Association Football. In R. C. Schmidt, et al. (Eds.), Natural and artificial playing fields: Characteristics and safety features (pp. 29–47). West Conshohocken, PA: American Society for Testing and Materials.

    Chapter  Google Scholar 

  • Caple, M., James, I., & Bartlett, M. (2012). Spatial analysis of the mechanical behaviour of natural turf sports pitches. Sports Engineering, 15(3), 143–157.

    Article  Google Scholar 

  • Carrow, R. N., Krum, J. M., Flitcroft, I., & Cline, V. (2010). Precision turfgrass management: Challenges and field applications for mapping turfgrass soil and stress. Precision Agriculture, 11(2), 115–134.

    Article  Google Scholar 

  • Cleary, M., Horsfall, J., & Hayter, M. (2014). Data collection and sampling in qualitative research: Does size matter? Journal of Advanced Nursing, 70(3), 473–475.

    Article  PubMed  Google Scholar 

  • Clegg, B. (1976). An impact testing device for in situ base course evaluation. Australian Road Research Board Proceedings, 8, 1–6.

    Google Scholar 

  • Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45, 123–134.

    Article  PubMed  CAS  Google Scholar 

  • Cope, M., & Elwood, S. (Eds.). (2009). Qualitative GIS: A mixed methods approach. London: Sage.

    Google Scholar 

  • Dutilleul, P., Clifford, P., Richardson, S., & Hemon, D. (1993). Modifying the t test for assessing the correlation between two spatial processes. Biometrics, 19, 305–314.

    Article  Google Scholar 

  • Ekstrand, J., Waldén, M., & Hägglund, M. (2004). Risk for injury when playing in a national football team. Scandinavian Journal of Medicine and Science in Sports, 14(1), 34–38.

    Article  PubMed  Google Scholar 

  • Elwood, S. (2010). Mixed methods: Thinking, doing, and asking in multiple ways. In D. Delyster, et al. (Eds.), The handbook of qualitative research in human geography (pp. 94–116). London: Sage.

    Chapter  Google Scholar 

  • Evans, J., & Jones, P. (2011). The walking interview: Methodology, mobility and place. Applied Geography, 31(2), 849–858.

    Article  Google Scholar 

  • Fortin, M. J., & Dale, M. R. (2005). Spatial analysis: A guide for ecologists. Cambridge: Cambridge University Press.

    Google Scholar 

  • Gausman, H. W. (1977). Reflectance of leaf components. Remote Sensing of Environment, 6(1), 1–9.

    Article  Google Scholar 

  • Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189–206.

    Article  Google Scholar 

  • Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59–82.

    Article  Google Scholar 

  • Hagaman, A. K., & Wutich, A. (2017). How Many Interviews Are Enough to Identify Metathemes in Multisited and Cross-cultural Research? Another Perspective on Guest, Bunce, and Johnson’s (2006) Landmark Study. Field Methods, 29(1), 23–41.

    Article  Google Scholar 

  • Hawkins, R. D., & Fuller, C. W. (1999). A prospective epidemiological study of injuries in four English professional football clubs. British Journal of Sports Medicine, 33(3), 196–203.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Jick, T. D. (1979). Mixing qualitative and quantitative methods: Triangulation in action. Administrative Science Quarterly, 24(4), 602–611.

    Article  Google Scholar 

  • Jung, J. K., & Elwood, S. (2010). Extending the qualitative capabilities of GIS: Computer-aided qualitative GIS. Transactions in GIS, 14(1), 63–87.

    Article  Google Scholar 

  • Junge, A., Cheung, K., Edwards, T., & Dvorak, J. (2004). Injuries in youth amateur soccer and rugby players—Comparison of incidence and characteristics. British Journal of Sports Medicine, 38(2), 168–172.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Knipling, E. B. (1970). Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Remote Sensing of Environment, 1(3), 155–159.

    Article  Google Scholar 

  • McClements, I., & Baker, S. W. (1994a). The playing quality of natural turf hockey pitches. Journal of Sports Turf Research Institute, 70, 13–28.

    Google Scholar 

  • McClements, I., & Baker, S. W. (1994b). The playing quality of rugby pitches. Journal of Sports Turf Research Institute, 70, 29–43.

    Google Scholar 

  • McNitt, A. S., & Landschoot, P. J. (2003). Effects of soil reinforcing materials on the surface hardness, soil bulk density, and water content of a sand root zone. Crop Science, 43(3), 957–966.

    Article  Google Scholar 

  • Olsen, W. (2004). Triangulation in social research: Qualitative and quantitative methods can really be mixed. Developments in sociology, 20, 103–118.

    Google Scholar 

  • Orchard, J. (2002). Is there a relationship between ground and climatic conditions and injuries in football? Sports medicine, 32(7), 419–432.

    Article  PubMed  Google Scholar 

  • Orchard, J. W., Chivers, I., Aldous, D., Bennell, K., & Seward, H. (2005). Rye grass is associated with fewer non-contact anterior cruciate ligament injuries than bermuda grass. British Journal of Sports Medicine, 39(10), 704–709.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Osorio, F., & Vallejos, R. (2014). SpatialPack: Package for analysis of spatial data. Retrieved, May 17, 2017 from http://cran.r-project.org/package=SpatialPack.

  • Owen, A., Smith, A. C., Osei-Owusu, P., Harland, A., & Roberts, J. R. (2017). Elite players’ perceptions of football playing surfaces: A mixed effects ordinal logistic regression model of players’ perceptions. Journal of Applied Statistics, 44(3), 554–570.

    Article  Google Scholar 

  • Patton, M. Q. (1990). Qualitative evaluation and research methods. London: Sage.

    Google Scholar 

  • Peñuelas, J., Filella, I., Biel, C., Serrano, L., & Save, R. (1993). The reflectance at the 950–970 nm region as an indicator of plant water status. International Journal of Remote Sensing, 14(10), 1887–1905.

    Article  Google Scholar 

  • Pope, C., & Mays, N. (1995). Reaching the parts other methods cannot reach: An introduction to qualitative methods in health and health services research. British Medical Journal, 311, 42–45.

    Article  PubMed  CAS  Google Scholar 

  • Poulos, C. C., Gallucci, J., Gage, W. H., Baker, J., Buitrago, S., & Macpherson, A. K. (2014). The perceptions of professional soccer players on the risk of injury from competition and training on natural grass and 3rd generation artificial turf. BMC Sports Science, Medicine and Rehabilitation, 6(1), 11.

    Article  PubMed  PubMed Central  Google Scholar 

  • Rennie, D. J., Vanrenterghem, J., Littlewood, M., & Drust, B. (2016). Can the natural turf pitch be viewed as a risk factor for injury within Association Football? Journal of Science and Medicine in Sport, 19(7), 547–552.

    Article  PubMed  Google Scholar 

  • Ronkainen, J., Osei-Owusu, P., Webster, J., Harland, A., & Roberts, J. (2012). Elite player assessment of playing surfaces for football. Procedia Engineering, 34, 837–842.

    Article  Google Scholar 

  • RStudio Team. (2015). RStudio: Integrated Development for R. Retrieved May 17, 2017, from http://www.rstudio.com.

  • Saldaña, J. (2015). The coding manual for qualitative researchers. London: Sage.

    Google Scholar 

  • Sandelowski, M. (1995). Sample size in qualitative research. Research in Nursing & Health, 18(2), 179–183.

    Article  CAS  Google Scholar 

  • Sandelowski, M., & Barroso, J. (2003). Writing the proposal for a qualitative research methodology project. Qualitative Health Research, 13(6), 781–820.

    Article  PubMed  Google Scholar 

  • Smith, B. (2018). Generalizability in qualitative research: Misunderstandings, opportunities and recommendations for the sport and exercise sciences. Qualitative Research in Sport, Exercise and Health, 10(1), 137–149.

    Article  Google Scholar 

  • Stiles, V. H., James, I. T., Dixon, S. J., & Guisasola, I. N. (2009). Natural turf surfaces. Sports Medicine, 39(1), 65–84.

    Article  PubMed  Google Scholar 

  • Straw, C. M., Grubbs, R. A., Tucker, K. A., & Henry, G. M. (2016). Handheld versus mobile data acquisitions for spatial analysis of natural turfgrass sports fields. HortScience, 51(9), 1176–1183.

    Article  Google Scholar 

  • Straw, C. M., & Henry, G. M. (2018). Spatiotemporal variation of site-specific management units on natural turfgrass sports fields during dry down. Precision Agriculture, 19(3), 395–420.

    Article  Google Scholar 

  • Straw, C. M., Samson, C. O., Henry, G. M., & Brown, C. N. (2018). Does variability within natural turfgrass sports fields influence ground-derived injuries? European Journal of Sport Science. https://doi.org/10.1080/17461391.2018.1457083.

    Article  PubMed  Google Scholar 

  • Trenholm, L. E., Carrow, R. N., & Duncan, R. R. (1999). Relationship of multispectral radiometry data to qualitative data in turfgrass research. Crop Science, 39(3), 763–769.

    Article  Google Scholar 

  • Zanetti, E. M. (2009). Amateur football game on artificial turf: Players’ perceptions. Applied Ergonomics, 40(3), 485–490.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Christine Samson, Graduate Student, University of Georgia, Department of Kinesiology, and Dr. Cathleen Brown Crowell, Clinical Associate Professor, Oregon State University, College of Public Health and Human Sciences, for assistance with IRB approval and participant recruiting; Joe Morgan, Sports Turf Manager, University of Georgia Recreational Sports Complex, for field use; Rebecca Grubbs, Graduate Student, University of Georgia, for assistance with qualitative data validation; and all undergraduate students who assisted with collecting field data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chase M. Straw.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Appendix

Appendix

See Table 1.

Table 1 Descriptive statistics of normalized difference vegetation index (NDVI), surface hardness, and turfgrass shear strength in the spring and fall

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Straw, C.M., Henry, G.M., Shannon, J. et al. Athletes’ perceptions of within-field variability on natural turfgrass sports fields. Precision Agric 20, 118–137 (2019). https://doi.org/10.1007/s11119-018-9585-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11119-018-9585-2

Keywords

Navigation