| Literature DB >> 26863212 |
Irene R Faber1,2,3, Marije T Elferink-Gemser4,5, Niels R Faber6,7, Frits G J Oosterveld1, Maria W G Nijhuis-Van der Sanden2.
Abstract
Forecasting future performance in youth table tennis players based on current performance is complex due to, among other things, differences between youth players in growth, development, maturity, context and table tennis experience. Talent development programmes might benefit from an assessment of underlying perceptuo-motor skills for table tennis, which is hypothesized to determine the players' potential concerning the perceptuo-motor domain. The Dutch perceptuo-motor skills assessment intends to measure the perceptuo-motor potential for table tennis in youth players by assessing the underlying skills crucial for developing technical and tactical qualities. Untrained perceptuo-motor tasks are used as these are suggested to represent a player's future potential better than specific sport skills themselves as the latter depend on exposure to the sport itself. This study evaluated the value of the perceptuo-motor skills assessment for a talent developmental programme by evaluating its predictive validity for competition participation and performance in 48 young table tennis players (7-11 years). Players were tested on their perceptuo-motor skills once during a regional talent day, and the subsequent competition results were recorded half-yearly over a period of 2.5 years. Logistic regression analysis showed that test scores did not predict future competition participation (p >0.05). Yet, the Generalized Estimating Equations analysis, including the test items 'aiming at target', 'throwing a ball', and 'eye-hand coordination' in the best fitting model, revealed that the outcomes of the perceptuo-motor skills assessment were significant predictors for future competition results (R2 = 51%). Since the test age influences the perceptuo-motor skills assessment's outcome, another multivariable model was proposed including test age as a covariate (R2 = 53%). This evaluation demonstrates promising prospects for the perceptuo-motor skills assessment to be included in a talent development programme. Future studies are needed to clarify the predictive value in a larger sample of youth competition players over a longer period in time.Entities:
Mesh:
Year: 2016 PMID: 26863212 PMCID: PMC4749309 DOI: 10.1371/journal.pone.0149037
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Characteristics of participants.
| Total group | Non competition | Competition | |
|---|---|---|---|
| Total of participants (n) | 48 | 9 | 39 |
| Participants 2011 (n) | 25 | 4 | 21 |
| Participants 2012 (n) | 23 | 5 | 18 |
| Girls (n) | 24 | 6 | 18 |
| Boys (n) | 24 | 3 | 21 |
| Test age 7 years (n) | 3 | 0 | 3 |
| Test age 8 years (n) | 6 | 2 | 4 |
| Test age 9 years (n) | 20 | 5 | 12 |
| Test age 10 years (n) | 17 | 1 | 16 |
| Test age 11 years (n) | 7 | 1 | 4 |
| M (range) | M (range) | M (range) | |
| Test age (y) | 9.3 (7–11) | 9.1 (8–11) | 9.4 (7–11) |
| Height (cm) | 143 (126–161) | 142 (129–156) | 143 (126–143) |
| Weight (kg) | 35 (22–57) | 35 (26–57) | 35 (22–56) |
| Training experience (months) | 13 (1–48) | 4 (1–6) | 13 (2–36) |
| Current training (hours / week) | 2.7 (1–7) | 1.9 (1–3) | 2.5 (1–7) |
n = number, M = mean.
Descriptive statistics perceptuo-motor skills assessment and logistic regression competition participation.
| Variables | Total (n = 48) | Non competition (n = 9) | Competition (n = 39) | Logistic regression | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| M | SD | Range | M | SD | Range | M | SD | Range | B (SE) | OR (95% CI) | ||
| Sprint (s) | 35 | 3.4 | 29–44 | 35 | 2.4 | 31–37 | 35 | 3.6 | 29–44 | 0.021 (0.112) | 1.021 (0.820–1.271) | 0.852 |
| Agility (s) | 25 | 4.5 | 18–45 | 27 | 3.9 | 21–35 | 25 | 4.6 | 18–45 | -0.100 (0.076) | 0.905 (0.780–1.051) | 0.191 |
| Vertical jump (cm) | 31 | 5.6 | 17–44 | 29 | 4.5 | 19–35 | 31 | 5.9 | 17–44 | 0.059 (0.068) | 1.060 (0.927–1.213) | 0.391 |
| Speed while dribbling (s) | 24 | 6.3 | 15–43 | 25 | 5.5 | 20–37 | 24 | 6.6 | 15–43 | -0.026 (0.056) | 0.975 (0.874–1.088) | 0.648 |
| Aiming at target (points) | 22 | 9.8 | 4–42 | 19 | 6.7 | 8–26 | 23 | 10.3 | 4–42 | 0.048 (0.040) | 1.049 (0.969–1.135) | 0.237 |
| Ball skills (points) | 19 | 6.4 | 5–31 | 17 | 8.2 | 5–29 | 19 | 6.0 | 5–31 | 0.064 (0.059) | 1.066 (0.949–1.197) | 0.280 |
| Throwing a ball (m) | 9 | 1.4 | 7–12 | 9 | 1.2 | 7–11 | 9 | 1.5 | 7–12 | 0.263 (0.254) | 1.301 (0.776–2.182) | 0.318 |
| Eye-hand coordination (points) | 13 | 7.0 | 0–26 | 11 | 4.5 | 2–18 | 13 | 7.5 | 0–26 | 0.053 (0.053) | 1.055 (0.950–1.171) | 0.317 |
| Total score (percentiles) | 466 | 143 | 160–720 | 398 | 102 | 190–520 | 481 | 147 | 160–720 | - | - | - |
| Age at test moment (y) | 9.3 | 1.0 | 7–11 | 9.1 | 0.9 | 8–11 | 9.4 | 1.1 | 7–11 | 0.231 (0.355) | 1.260 (0.628–2.529) | 0.515 |
| Sex | - | - | - | - | - | - | - | - | - | -0.847 (0.777) | 0.429 (0.094–1.964) | 0.275 |
| Training experience (months) | 11 | 9.0 | 1–36 | 4 | 1.9 | 1–6 | 13 | 9.1 | 2–36 | 0.421 (0.167) | 1.523 (1.097–2.115) | 0.012 |
n = number, M = mean, SD = standard deviation, B = regression coefficient, SE = standard error, OR = odds ratio, CI = confidence interval
*p <0.05.
Fig 1Competition score curve per player over five competition periods (= 2.5 years).
Lines represent the individual players.
Predictive validity results for competition performance (univariable and multivariable generalized estimated equations analyses, n = 39).
| Variables | B (SE) | ||
|---|---|---|---|
| Univariable | Best fitting | Multivariable | |
| (Intercept) | - | -175.597 | -93.588 (66,29) |
| Sprint (s) | -10.109 | - | - |
| Agility (s) | -6.055 (3.92) | - | - |
| Vertical jump (cm) | 4.401 | - | - |
| Speed while dribbling (s) | -6.854 | - | - |
| Aiming at target (points) | 4.642 | 2.169 | 2.010 |
| Ball skills (points) | 6.535 | - | - |
| Throwing a ball (m) | 35.255 | 14.554 | 19.562 |
| Eye-hand coordination (points) | 7.300 | 4.787 | 5.510 |
| Age at test moment (y) | 3.103 | - | -1.123 (0.66) |
| Sex | 38.357 (22.97) | - | - |
| Training experience (months) | 2.584 | - | - |
| R2 | 51% | 53% | |
B = regression coefficient, SE = standard error
* p <0.05
** p <0.01