‘Contribution of planned and unplanned training to overall load in elite youth female football players' Presenting Author: Jonathan Taylor Co-Authors: Chris Hurst, Russ Best and Matthew Wright

Context Teesside Sport Girls Centre of Excellence Sport Science Support: Fitness testing Pitch-based conditioning Neuromuscular training Training monitoring Age groups: Under 11 – Under 17 Key issues: Overreaching/Overtraining Purpose of girls centre of excellence – top picture is aim i.e. get players playing for england. How do we monitor all the different types of training/ fitness day to day. We are the only centre that has a systematic approach like this.

Background Planned manipulation of training load = essential to achieve desired adaptations (Borresson and Lambert, 2009). Accurate assessment of training load facilitates training prescription (Wrigley et al. 2012) Lack of research investigating the training load undertaken by young female football players. Furthermore, research acknowledging any external training activities that elite youth athletes engage in is limited. Failure of coaches to acknowledge these activities can be problematic! Early specialization and ever increasing training loads increases injury risk in young athletes (Capranica and Millard-Stafford et al. 2011; Malisoux et al. 2013) More information on the studies to emphasize the need for our study – Only in Male players and only planned training.

Aims Investigate the contribution of ‘planned’ and ‘unplanned’ training to overall load. Investigate within-season variation in training load. Assess compliance rates of the players in providing training data derived from self-report measures. Training Load

Methods Observational 35 female players (aged 13-16 years) required to keep a training diary over a 34-week period. Training load calculated as: Session duration * Global RPE = session-RPE (AU) (Foster et al. 2001). Training coded as ‘football’ and ‘strength and conditioning’ and ‘additional’ (i.e. school-based physical education sessions, or participation in other sports). The contribution of these modes of training to overall training load was calculated. Athlete compliance also assessed.

Statistical analysis Only players providing >17 weeks of data were included in the analysis. Data were analysed using a mixed linear model – most appropriate statistical technique when dealing large data sets with fixed (time-point) and random effects (individual players and training sessions) and in instances where data is missing (Malone et al. 2015) The magnitude of effects was calculated using a customised spreadsheet (Hopkins, 2007) Standardised thresholds for small, moderate and large changes of 0.2, 0.6 and 1.2 standard deviations, respectively were used (Hopkins et al. 2009).

Results Compliance rates Compliance rates of players providing >17 weeks’ of data was 32%. Weekly training load Mean weekly training load was 2157 ± 454 arbitrary units (au). Training mode ‘Likely small’ differences between ‘football’ and ‘strength and conditioning’ (290 au; 90% CL ±75); and ‘additional’ and ‘strength and conditioning’ (227 au; CL ±76). ‘Trivial’ differences were observed between ‘football’ and ‘additional’ training (63; ±76). Larger within, than between player differences observed (559; ES 0.92; ±22; and 203; ES 0.34; ±66 respectively).

Results Figure 1. Mean contribution of training mode to overall load across the season

Strength and Conditioning Results Table 1. Within-season variation in training load (mean load for all players). Phase of Season Total Football Strength and Conditioning Additional Early- (Aug-Nov) 2401 ± 413 974 ± 316 623 ± 136 804 ± 302 Mid- (Nov-Feb) 1888 ± 530 643 ± 351 558 ± 153 687 ± 238 Late- (Feb-April) 2169 ± 185 866 ± 304 443 ± 102 870 ± 211 All data expressed as arbitrary units with mean ± standard deviation presented

Strength and Conditioning Table 2. Effect of the phase of season (Early-, Mid- and Late-) on training load. Difference (au) 90% Confidence Interval Effect Total Early-Mid -462 -282 to -643 Very Likely Small ↘ Mid-Late 411 643 to 187 Very Likely Small ↗ Early-Late -52 165 to 268 Possibly Trivial ↘ Football -319 -213 to -426 Possibly Moderate↘ 249 382 to 117 69.9 -58 to 198 Unclear Strength and Conditioning 55 -35 to 145 -108 -3 to -212 Possibly Small↘ -163 -61 to -264 Likely Small ↘ Additional -73 -124 to 269 251 474 to 27 Likely Small ↗ 178 396 to 40 Possibly Small↗

Conclusions Training loads undertaken by youth female football players may not reflect that planned by coaches. In some instances players may partake in more ‘additional’ than ‘planned’ training Large individual differences in the amount of ‘additional’ activities that athletes engage in. Compliance of youth female players in providing self-reported training load data is a problematic area – this has been highlighted previously (Malisoux et al. 2013). Being able to adapt practice week to week seems necessary

Practical Applications Monitoring training load of great importance within youth female players. Coaches must be aware of individual training schedules to avoid overreaching/overloading players. Ability to adapt practice is crucial. When using self-report measures, strategies to increase compliance of youth players should be implemented to avoid lack of adherence.

Future research… Strategies to increase athlete compliance. Prospective studies regarding the participation in additional sports/activities and success at elite level in female football. The relationship between ‘additional training’ and fitness. The relationship between ‘additional training’ and injury incidence.

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