Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Data benchmarking as a tool for effective coaching in volleyball

5 views

Published on

Sports Analytics Workshop 2017
Data benchmarking as a tool for effective coaching in volleyball

Published in: Sports
  • Be the first to comment

  • Be the first to like this

Data benchmarking as a tool for effective coaching in volleyball

  1. 1. 2nd AUEB Sports Analytics Workshop Athens 7- 8 November 2017
  2. 2. Data benchmarking as a tool for effective coaching in Volleyball Sotiris Drikos PhD, AUEB Group Sports Analytics Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  3. 3. Athletes perform Performance analyzed Past results Accounted for Coach plans practice Coach conducts practice Coach Observes Coaching process in its observational, analytical and planning phases (Franks et al., 1983). Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  4. 4. Planning Observation (Methods) Interpretation & Discussion Quantitative & Qualitative Analysis Performance Provide feedback The role of performance analysis in the cyclical processes of coaching (adapt form Carling, Williams & Reilly, 2005) Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  5. 5. Planning Observation (Methods) Interpretation & Discussion Quantitative & Qualitative Analysis Performance Provide feedback The role of performance analysis in the cyclical processes of coaching (adapt form Carling, Williams & Reilly, 2005) Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions P e r f o r m a n c e A n a l y s i s •Technical Effectiveness •Tactical patterns of play •Performance Profiling •Comparison with past performances •Comparison with opponents
  6. 6. Implement Best practices Measure Results Compare to Competition Identify Opportunities to improve Select implementation tools Conduct training Management: Continuous improvement cycle Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  7. 7. Implement of best practices Performance Measure Results Performance Analysis Compare to Competition Identify Opportunities to improve Interpretation Select implementation tools Provide feedback/ Planning Conduct training Creation of Benchmarks Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  8. 8. • Benchmark is a reference point for comparisons established from the value οf a performance indicator • Performance Indicator (PI) is a selection, or combination, of action variables that aims to define some or all the aspects of sport performance (Hughes & Bartlett, 2002). • Data benchmarking concerns quantitative comparisons of performance outcomes across different sections and/or different time periods (Bartlett, Gratton, & Rolf, 2006). • Benchmarking requires an understanding of what is important to the organization (a team in our case). Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  9. 9. Variables Performance Indicators Benchmarks Variables Performance Indicators Benchmarks Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions Variables Performance Indicators Benchmarks
  10. 10. • In coaching the use of data benchmarking can: – identify top performers and what makes them succeed, – set the right performance standards, – select proper players and – manage athletes and teams more effectively. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  11. 11. • Determinization of skills & tactical choices affect sport performance (Marcelino et al.,2008) • In Volleyball team’s performance in skills connected directly with the game result (Marchelino et al., 2009) and with sport success in a championship (Drikos et al., 2009). • Quantification of important performance indices in a championship (Lobietti et al., 2006) • Volleyball consists of 6 main skills: Serve, pass, attack (1 & 2), Block, Setting & Dig Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  12. 12. Pass SettingAttackBlock DigServe Volleyball skills and PIs Attack 1 Attack 2 Scoring Skills Non Scoring Skills Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  13. 13. • Performance data from each team of Greek Volleyleague from 2005-06 until 2015-16 (Ν= 131). • Skills: Serve, Pass, Attack 1 (after pass), Attack 2 (after defense), Block. • Evaluation scale consists of 6 levels. • 14 variables (5 indices) – Serve: Lost, aces (SER= lost/ aces) – Attack 1: Kills, errors & blocked (A1ER=kills/errors+blocked) – Attack 2: Kills, errors & blocked (A2ER=kills/errors+blocked) – Pass: Excellent, good, overpass, errors (PER= Excellent + good/ errors + overpass) – Block: kill/set (Block/set) Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  14. 14. • Performance data from each team of Greek Volleyleague from 2005-06 • Correlation of indices Serve & Attack with athletic success with data from one season (Drikos et al., 2009) • Indices SER, AER. SR= 0,272 AER - 0,087 SER SR= Sets won/Total sets AER=Attacks won/ (Attack lost + Attacks blocked) SER=Serves Lost/ Serves won Ranking (Spearman) Points in ranking (Pearson) Set ratio -.974** .989** Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions R2 = 88.4%
  15. 15. • Reliability of the data collection and entry was checked by an independent observer with Adjusted Κ Cohen and it was Adjusted Κ= .85, very good (Altman, 1991). • Multiple Regression Analysis • Μ.ΑN.Ο.VA. and follow-up discriminant analysis. • Aim is to: – Check previous model – Determine: • differences among teams of final positions 1-4, 5-8 & 9-12 • Skills which classify with success the data. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  16. 16. 88.40 80.30 85.20 90.50 91.60 82.20 86.80 92.60 67.90 91.40 0 10 20 30 40 50 60 70 80 90 100 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 R2 (%) Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  17. 17. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  18. 18. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions 0.065 0.060 0.053 0.155 0.154 0.161 Group 1 Group 2 Group 3 SRV Aces / SRV total SRV Errors/ SRV total
  19. 19. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions 0.600 0.580 0.558 0.102 0.110 0.121 Group 1 Group 2 Group 3 PASS (5+6) / PASS total PASS (1+2)/PASS total
  20. 20. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions 0.552 0.514 0.482 0.157 0.185 0.21 Group 1 Group 2 Group 3 AΤΤ1 Kill / ATT1 total AΤΤ1 error+blocked /ATT1 total
  21. 21. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions 0.495 0.452 0.426 0.183 0.210 0.211 Group 1 Group 2 Group 3 AΤΤ2Kill/ ATT2 total AΤΤ2 error+blocked / ATT2 total
  22. 22. 2.62 2.33 2.13 Group 1 Group 2 Group 3 Block/set Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  23. 23. Group 1 1-4 (N=44) Group 2 5-8 (N=44) Group 3 9-12 (N=43) Post Hoc Scheffe Post Hoc Scheffe SRV Aces .065±.01 .06±.01 .053±.01 G1>>>G3 G2>G3 SRV Errors .155±.02 .154±02 .161±02 PASS (5+6) .60±.05 .58±.05 .558±.05 G1>G2, G1>>G3 PASS (1+2) .102±.02 .11±.02 .121±.02 G1>G3 Block/set 2.62±.3 2.33±.2 2.13±.5 G1>>>G2,G3 G2>G3 AΤΤ1 Kill .552±.03 .514±.02 .482±.03 G1>>>G2,G3 G2>>>G3 AΤΤ1 error .157±.01 .185±.01 .21±.02 G1>>>G2,G3 G2>>>G3 AΤΤ2 Kill .495±.07 .452±.02 .426±.03 G1>>>G2,G3 AΤΤ2 error .183±.02 .21±.02 .211±.02 G1>>>G2,G3 Group “A” significantly differs from Group “B” with p value: less than 0.001 ("A>>>B"), between 0.001 and 0.01 ("A>>B"), between 0.01 and 0.05("A>B"). Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  24. 24. Indices Group 1 1-4 (N=44) Group 2 5-8 (N=44) Group 3 9-12 (N=43) Post Hoc Scheffe Post Hoc Scheffe PER 6.05±1.4 5.68±1.5 4.87±1.5 G1>G3 A1ER 3.56±0.5 2.80±0.2 2.49±0.3 G1>>>G2,G3 G2>>G3 SER 2.44±0.3 2.58±0.4 3.06±0.5 G1>>>G3 G2>>>G3 Block/set 2.63±0.2 2.33±0.3 2.13±0.4 G1>>G2,G3 G2>G3 A2ER 2.74±0.6 2.18±0.3 2.04±0.3 G1>>G2,G3 Group “A” significantly differs from Group B with p value: less than 0.001 ("A>>>B"), between 0.001 and 0.01 ("A>>B"), between 0.01 and 0.05("A>B"). Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  25. 25. >|.3| Indices Coefficients PER .227 A1ER .869 SER -.408 Block/set 451 A2ER .574 Group 1-4 Group 5-8 Group 9-12 Group 1-4 87.5% 7,5% 3% Group 5-8 5% 70% 25% Group 9-12 0% 30.8% 69.2% √ √ √ √ √ Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  26. 26. • Teams in final ranking which took positions 1-4 performed better in all skills than teams in positions 9-12. • Teams 1-4 were better than teams 5-8 in all skills on the net (attack 1&2, block). • Teams 5-8 comparing to teams 9-12 performed better in Attack 1 (after pass), serve and block. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  27. 27. • Success in Volleyball can be explained with skill indices because of the good fit of the model. • Effective use of benchmarking for measuring and improving Performance. Benchmarks are a tool for effective coaching. • Suggestions for coaches: with the use of indices it is easier to quantify the target of drills: – 6 passes on the target for 1 error or overpass, – 5 errors in serve for 2 aces – 4 kills in attack after pass for 1 error or blocked attack – 3 kills in attack after dig for 1 error or blocked attack). Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions
  28. 28. Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions •Literature • Bartlett, R., Gratton, C., & Rolf, C. G. (2006). Encyclopedia of international sports studies (Vols. 1 A-E). New York: Routledge. • Carling, C., Williams, A.M., and Reilly, T. (2005). The Handbook of Soccer Match Analysis. London, UK: Routledge. • Drikos, S., Kountouris, P., Laios, A., & Laios, I. (2009). Correlates of team performance in Volleyball. International Journal of Performance Analysis of Sports, 9(2), pp. 149-156. • Franks, I. M., & Miller, G. (1991). Training coaches to observe and remember. Journal of Sport Sciences(9), pp. 285-297. • Hughes, M., & Bartlett, R. M. (2002). The use of performance indicators in performance analysis. Journal of Sports Science(20), pp. 739-754. • Lobietti, R., Michele, R., & Merni, F. (2006). Relationships between performance parameters and final ranking in professional Volleyball. In H. Dancs, M. Hughes, & J. Ekler (Ed.), World Congress of Performance Analysis in Sports 7. Szombathely: Berzenyi College. • Marcelino, R., Mesquita, I., & Alfonso, J. (2008). The weight of terminal actions in Volleyball.Contributions of the spike,serve and block for the teams' ranking in the World League 2005. International Journal of Performance Analysis in Sport, 8(2), pp. 1-7. • Marcelino, R., Mesquita, I., & Sampaio, J. (2009). Home advantage and set outcome in high-level volleyball. Journal of Sports Sciences(26), pp. S66- S67.
  29. 29. Thank you for your attention! Data benchmarking as a tool for effective coaching in Volleyball •Management & Coaching •Performance indicators & benchmarks •Data •Method •Results •Conclusions •The End

×