TABLE 1.

Summary of the variables collected during the season.

Variables	Definition	Calculation	Supporting literature
Injuries (contact and non-contact)	Contact and non-contact injuries were classified whether they occurred with or without physical contact between players	$$\frac{\text{number of injuries}}{\text{training exposure}}\times 1000\text{\hspace{0.17em}h}$$	Fuller et al. [25]
			Yu & Garret [26]
Illnesses	Condition characterised by the presence of cold-related symptoms (e.g., influenza, fever, sore throat)	$$\frac{\text{number of illnesses}}{\text{training exposure}}\times 1000\text{\hspace{0.17em}h}$$	Putlur et al. [27]
Maturity offset	The time before or after peak height velocity (PHV)	Maturity Offset = – 29.769 + 0.0003007 Leg Length and Sitting Height interaction – 0.01177 X Age and Leg Length interaction + 0.01639 Age and Sitting Height interaction + 0.445 Leg by Height ratio	Mirwald et al.[28]
S-RPE	Subjective internal training load	Training session rating of perceived exertion (RPE) training duration	Foster et al. [29]
			Impellizeri et al. [30]
WL, WL2, WL3, WL4	Cumulative training loads	Sum of the loads of all training sessions and matches over a period of one week (WL), two weeks (WL2), three weeks (WL3), four weeks (WL4)	Jaspers et al. [12]
A:C2, A:C3, A:C4	Acute to chronic workload ratio	$$\frac{\text{acute workload (WL)}}{\text{chronic workload}}$$	Gabbett et al. [43]
		Chronic loads were quantified as the rolling averages for 2, 3 and 4 weeks.	Fanchini et al. [13]
%WL	Week-to-week workload change	Percentage variation of the current WL respect to the previous WL	Fanchini et al. [13]
Z-TQR	Z-score transformation of the TQR values	$$\frac{\text{individual players score-individual player average}}{\text{individual players standard deviation}}$$	Gallo et al. [33]
Z-RPE	Z-score transformation of the RPE values	$$\frac{\text{individual players score-individual player average}}{\text{individual players standard deviation}}$$	Gallo et al. [33]