Daniele Conte

Mental fatigue: Impairment of technical performance in small-sided soccer games

PURPOSE To assess the effects of mental fatigue on physical and technical performance in small-sided soccer games. METHODS Twenty soccer players (age 17.8 ± 1.0 y, height 179 ± 5 cm, body mass 72.4 ± 6.8 kg, playing experience 8.3 ± 1.4 y) from an Australian National Premier League soccer club volunteered to participate in this randomized crossover investigation. Participants played 15-min 5-vs-5 small-sided games (SSGs) without goalkeepers on 2 occasions separated by 1 wk. Before the SSG, 1 team watched a 30-min emotionally neutral documentary (control), while the other performed 30 min of a computer-based Stroop task (mental fatigue). Subjective ratings of mental and physical fatigue were recorded before and after treatment and after the SSG. Motivation was assessed before treatment and SSG; mental effort was assessed after treatment and SSG. Player activity profiles and heart rate (HR) were measured throughout the SSG, whereas ratings of perceived exertion (RPEs) were recorded before the SSG and immediately after each half. Video recordings of the SSG allowed for notational analysis of technical variables. RESULTS Subjective ratings of mental fatigue and effort were higher after the Stroop task, whereas motivation for the upcoming SSG was similar between conditions. HR during the SSG was possibly higher in the control condition, whereas RPE was likely higher in the mental-fatigue condition. Mental fatigue had an unclear effect on most physical-performance variables but impaired most technical-performance variables. CONCLUSIONS Mental fatigue impairs technical but not physical performance in small-sided soccer games.

Physiological and Technical Demands of No Dribble Game Drill in Young Basketball Players.

Abstract Conte, D, Favero, TG, Niederhausen, M, Capranica, L, and Tessitore, A. Physiological and technical demands of no dribble game drill in young basketball players. J Strength Cond Res 29(12): 3375–3379, 2015—This study assessed the physiological and technical demands of no dribble game drill (NDGD) in comparison with a regular drill (RD). Twenty-three young basketball players performed RDs and NDGDs in a random order. All basketball rules were followed for RDs, whereas dribbling was not permitted for NDGDs. The independent variable was the drill condition, and the dependent variables were percentage of maximal heart rate (%HRmax), rate of perceived exertion (RPE), Edwards training load (TL), and the following technical actions (TAs): pass (total, correct, wrong, and percent of correct passes), shot (total, scored, missed, and percent of made shots), interception, steal, turnover, and rebound. Wilcoxon signed-rank tests were applied to assess differences between NDGD and RD conditions for each dependent variable, and the level of statistical significance was set at p ⩽ 0.05. Results showed higher values for %HRmax (p = 0.007), Edwards TL (p = 0.006), and RPE (p = 0.027) in NDGD compared with RD condition. Technical action analysis revealed higher values in NDGD than RD for total (p = 0.000), correct (p = 0.000), and wrong pass (p = 0.005), and interception (p = 0.001), whereas no significant differences were found for the other TAs. The main finding of this study was that NDGD condition elicited a greater physiological demand and a higher number of passes and interceptions than the RD one. Basketball coaches should consider the NDGD as a viable method to increase the physiological load of their training sessions and to teach passing skills in a game-based situation.

Determinants of the effectiveness of fast break actions in elite and sub-elite Italian men’s basketball games

The aim of this study was to examine the determinants of successful and unsuccessful fast-break (FB) actions in elite and sub-elite basketball games. Fifteen 1st-division (elite) and fifteen 3rd-division (sub-elite) Italian men’s championship games were analysed across two seasons (2012/2013 and 2013/2014). A binary logistic regression analysis was performed, and the fast-break outcome (successful vs. unsuccessful) was adopted as the dependent variable separately in both elite and sub-elite games. FB execution (initiation, advance and completion phases), typology (primary and secondary break) and the number of players involved (equal number or superiority) were used as independent variables. The results showed that the rate of success of FB actions was 63.5% and 59.7% in elite and sub-elite games, respectively. Moreover, successful FBs were more likely to be completed in the lane in relation to unsuccessful ones in both elite and sub-elite games (p<0.05). Finally, descriptive statistics showed that both elite and sub-elite teams executed FBs similarly. This study highlighted that completion zone was the only predictor of a successful fast break in basketball, while the typology and number of players involved did not predict fast break effectiveness. Moreover, elite and sub-elite teams executed fast break actions similarly. These findings might be useful for basketball coaches to optimize the training of FB actions.

Effect of different number of players and training regimes on physiological and technical demands of ball-drills in basketball

Abstract This study aimed to analyse the effects of two factors (number of players and training regimes) on players’ physiological and technical demands in basketball ball-drills. Twenty-one young basketball players performed four different ball-drills (two levels for each factor). The number of players involved was 2vs2 and 4vs4, while ball-drill regimes were continuous and intermittent. Physiological demand was assessed using the percentage of maximal heart rate (%HRmax), Edwards’ training load and rating of perceived exertion (RPE). Furthermore, the following technical actions were collected: dribbles, steals, rebounds, turnovers, passes (total, correct, wrong and % of correct pass) and shots (total, scored, missed and % of made shot). A 2 × 2 (number of players × regime) two-way ANOVA with repeated measures was applied for physiological parameters and technical actions. The 2vs2 condition showed higher %HRmax (P < 0.001), Edwards’ training load (P < 0.001), RPE (P < 0.001), number of dribbles (P < 0.001), rebounds (P < 0.001), passes [total (P = 0.005) and correct (P = 0.005)] and shots [total (P < 0.001) scored (P < 0.001) and missed (P < 0.001)] than 4vs4. Moreover, the continuous regime revealed higher %HRmax (P < 0.001), Edwards’ training load (P < 0.001), RPE (P = 0.006) and dribbles (P < 0.001) than the intermittent regime. This study showed that both number of players and regime are useful variables able to modify basketball ball-drills workload.

Scoring Strategies Differentiating between Winning and Losing Teams during FIBA EuroBasket Women 2017

This study aimed to examine the scoring strategies differentiating between winning and losing teams during FIBA EuroBasket Women 2017 in relation to different game scores. Data were gathered for all games of FIBA EuroBasket Women 2017 from the official website. The investigated scoring strategies were fast break points (FBP); points in the paint (PP); points from turnover (PT); second chance points (SCP); and points from the bench (PB). Games were classified with cluster analysis based on their score difference as close, balanced, and unbalanced and the differences in the scoring strategies between winning and losing teams were assessed using magnitude-based statistics. Results revealed no substantial differences in FBP in any investigated cluster. Furthermore, winning teams showed a substantially higher number of PP and PT (in close and unbalanced games) and SCP (in balanced and unbalanced games) compared to losing teams. Finally, winning teams scored substantially lower and higher number of BPs in close games and unbalanced games, respectively, compared to losing teams. In conclusion, all the investigated scoring strategies discriminate between winning and losing teams in elite women’s basketball except for FBP. These results provide useful information for basketball coaches to optimize their training sessions and game strategies.

A comparison of traditional and modified Summated-Heart-Rate-Zones models to measure internal training load in basketball players

ABSTRACT The Summated-Heart-Rate-Zones training load (SHRZ TL) model is used to measure internal loading; however, a major limitation of this approach is the use of broad heart rate (HR) zones to quantify exercise intensity. Therefore, this study aimed to compare SHRZ TL outcomes derived using the traditional model and modified approaches using smaller HR zones. HR responses were monitored in 15 semi-professional basketball players during preparatory training to calculate SHRZ TL using the traditional approach with 10%HRmax zones (SHRZ10) and modified approaches with 5%HRmax zones (SHRZ5) and 2.5%HRmax zones (SHRZ2.5). Significant (P < 0.001) differences were evident in SHRZ TL between SHRZ10 (254.2 ± 41.7 AU) and SHRZ5 (275.9 ± 43.3 AU, unclear, small) as well as SHRZ2.5 (286.7 ± 44.3 AU, very likely, moderate). Use of SHRZ2.5 provides novel insight regarding internal loading in basketball players and may carry greater sensitivity for detection of maladaptive and adaptive responses to training.

Investigating the game-related statistics and tactical profile in NCAAdivision I men’s basketball games

The aim of this study was to analyze the game-related statistics and tactical profile in winning and losing teams in NCAA division I men’s basketball games. Twenty NCAA division I men’s basketball close (score difference: 1-9 points) games were analyzed during the 2013/14 season. For each game, the game-related statistics were collected from the official teams’ box scores. Number of ball possessions, offensive and defensive ratings and the Four Factors (effective field goal percentage; offensive rebounding percentage, recovered balls per ball possession, free throw rate) were also calculated. The tactical parameters evaluated were: ball reversal, dribble in key area, post entry, on-ball screen, off-ball screen, and hand off. Differences between winning and losing teams were calculated using a magnitude-based approach. Winning teams showed a likely higher percentage of 3-point goals made, number of defensive rebounds and steals and a very likely higher number of free throws made and free throws attempted. Furthermore, winning teams showed a likely higher team offensive rating and effective field goal percentage and a very likely higher free throw rate compared to losing teams. Finally, the results revealed a likely higher number of ball reversals and post entries in winning teams compared to losing teams. This study highlighted the game-related statistics and the tactical actions differentiating between winning and losing teams in NCAA Division I men’s basketball close games. Coaches should use these results to optimize their training sessions, focusing on those variables that might increase the possibility to win close games.

Performance profile of NCAA Division I men’s basketball games and training sessions

This study aimed to analyse live and stoppage time phases, their ratio, and action played on half and full court in college basketball games. Differences were assessed for the entire games and between halves. Moreover, differences of the live/stoppage time ratio were analysed between games and game-based conditioning drills. Ten games as well as fifteen defensive, fourteen offensive and six scrimmage-type drills of the same division I mens college team (13 players) were analysed using time-motion analysis technique. Live and stoppage time were classified in five classes of duration: 1-20, 21-40, 41-60, 61-80, >80 seconds. Half court actions started and finished in the same half court. Full court actions were classified as transfer (TR) phases when at least 3 teammates crossed the mid-court line. TR phases were then classified in 5 classes of frequency: 1TR, 2TR, 3TR, 4TR, and >4TR. The results revealed no statistically significant differences between games or between halves for the considered parameters. The only significant difference was observed for live/stoppage time ratio between halves (p<0.001). Furthermore, a significant difference of the live/stoppage ratio was found between games and game-based drills (p<0.01). Post-hoc analysis demonstrated significant differences of scrimmage-type drills in comparison to games, and defensive and offensive drills (p<0.05), whereas no differences emerged for the other pairwise comparisons. The absence of differences between games in the analysed parameters might be important to characterize the model of performance in division I mens college games. Furthermore, these results encourage coaches to use game-based conditioning drills to replicate the LT/ST ratio documented during games.

Dribble Deficit: A novel method to measure dribbling speed independent of sprinting speed in basketball players

ABSTRACT Basketball tests assessing dribbling speed predicated on total performance times are influenced by sprinting speed. This study examines an approach termed Dribble Deficit to counter this limitation by examining the relationships between sprinting and dribbling speed during linear and change-of-direction (COD) tasks measured using total performance time and Dribble Deficit. Ten semi-professional basketball players completed linear sprints and COD sprints with and without dribbling. Dribble Deficit was calculated as the difference between the best time for each dribbling trial and corresponding non-dribbling trial for linear and COD sprints. Large to very large significant relationships (P < 0.05) were evident between linear sprint and dribble times (R = 0.64–0.77, R2 = 0.41–0.59), and between COD sprint and dribble times (R = 0.88, R2 = 0.77). Conversely, trivial-small relationships were evident between linear sprint time and linear Dribble Deficit (R = 0.01–0.15, R2 = 0.00–0.02). A non-significant, moderate, negative relationship was observed between COD sprint time and COD Dribble Deficit (R = −0.45, R2 = 0.20). These findings indicate Dribble Deficit provides a more isolated measure of dribbling speed than tests using total performance times. Basketball practitioners may use Dribble Deficit to measure dribbling speed independent of sprint speed in test batteries.

The effect of block and traditional periodization training models on jump and sprint performance in collegiate basketball players

This study investigated the effect of block periodization (BP) and traditional periodization (TP) approaches on jumping and sprinting performance in collegiate basketball players during an 8-week pre-season period. Ten collegiate male basketball players (mean±SD; age: 21.5±1.7 years; body mass: 83.5±8.9 kg; stature: 192.5±5.4 cm) from the same team were equally assigned to a training group (BP or TP). BP and TP were designed with different numbers of power sessions (BP=8; TP=16) and recovery days (BP=14; TP=8). Counter-movement jump (CMJ) and 20-m sprint performance was measured prior to training commencement (baseline) and every 2 weeks thereafter (week 2, week 4, week 6 and week 8). Within-group, between-group and individual changes were assessed using magnitude-based statistics. Substantially higher (likely positive) CMJ scores were evident in week 8 compared to baseline, week 2 and week 4 with BP training. Substantially higher CMJ values were only observed in week 2 (likely positive) compared to baseline, with TP training. Sprint data showed likely negative differences in week 6 compared to baseline in both TP and BP, with no substantial differences in week 8. The only performance difference between TP and BP training was in CMJ in week 8 (very likely negative). Individual analysis showed that only three athletes demonstrated a negative predicted score (i.e. lower sprinting time) in BP, while all players following the TP model demonstrated positive predicted scores. BP training showed substantially higher jumping performance compared to TP, while no improvement in sprinting performance was observed in either training approach. Basketball coaches should consider using BP training rather than TP to train players’ jumping abilities.