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Notes on Psychological Factors and Performance in Elite Soccer Players (Malaysia)

Purpose and Aims

  • Investigate the role of psychological factors on the performance of elite soccer players in the Malaysian Super League.
  • Psychological constructs measured: motivation, confidence, anxiety control, mental preparation, team emphasis, concentration, and cognition (assessed via PSIS-R5).
  • Dependent variable (DV): performance, evaluated over eight weeks using main game performance indicators.
  • Approach: assess relationships between psychological factors (IVs) and performance (DV); determine whether psychological factors jointly or individually predict performance.

Participants and Setting

  • Participants: elite soccer players from one club competing in the Malaysian Super League.
  • Reported mean age: approximately
    • text: ±25 years; exact mean not consistently stated.
  • Sample size: reported as 26 elite players in the narrative; descriptive statistics (Table 1) indicate n = 20 for the dataset presented.
  • Supporting roles: eleven performance analysts and a control person (C.P) assisted in performance analysis.
  • Timeframe: study conducted during the 2014–2015 Malaysian Super League season.
  • Setting: Malaysia; performance tracked over eight weeks.

Measures and Instruments

  • Psychological measures: Psychological Skills Inventory for Sport, PSIS-R5 (Mahoney, Gabriel & Perkins, 1987) – 63 items across seven constructs:
    • Motivation
    • Confidence
    • Anxiety control
    • Mental preparation
    • Team emphasis
    • Concentration
    • Cognition
  • Performance measures: game performance indicators (clearing, crossing, dribble, heading, chasing the loose ball, shooting, foul, through pass) coded as successful (s) or failed (f).
  • Data collection tool: Statwatch application on a tablet used to record performance indicators relevant to game demand.
  • Operational definitions: clearly defined indicators used by coach, controller of analysis, and performance analysts to ensure consistent scoring.
  • Administration timing: PSIS-R5 questionnaire distributed before the competition; scores recorded for each player.

Procedure and Data Collection

  • Data collection process:
    • PSIS-R5 administered pre-season; players scored on psychological constructs.
    • Performance data collected during eight weeks of competition using Statwatch by eleven analysts.
    • Analysis of performances conducted by the controller and reported to the coach at halftime intervals.
  • Data synthesis: performances coded as s/f and aggregated per player over the eight-week period.
  • Descriptive and inferential analyses conducted to examine relationships between psychological factors and performance.

Statistical Analysis

  • Primary analysis: Standard multiple regression to predict performance from psychological factors.
  • Model specifics:
    • DV: Performance
    • IVs: Motivation, Confidence, Anxiety control, Mental preparation, Team emphasis, Concentration, Cognition
    • Alpha level: p ≤ 0.05
  • Regression equation (conceptual):
    ext{Performance} = eta0 + eta1 ext{Motivation} + eta2 ext{Confidence} + eta3 ext{AnxietyControl} + eta4 ext{MentalPreparation} + eta5 ext{TeamEmphasis} + eta6 ext{Concentration} + eta7 ext{Cognition} + ext{error}
  • Model indications reported in the text include both an overall model result and per-variable coefficients as shown in Table 2.
  • Note potential inconsistencies in reporting across sections (see Results).

Descriptive Statistics (Table 1)

  • Table 1 presents means, standard deviations (SD), and sample sizes for the DV and IVs.
  • Performance: mean = 19.60, SD = 8.88, n = 20 (per table).
  • Motivation: mean = 4.48, SD = 0.02, n = 20.
  • Confidence: mean = 3.30, SD = 0.40, n = 20.
  • Anxiety control: mean = 3.12, SD = 0.09, n = 20.
  • Mental preparation: mean = 4.00, SD = 0.05, n = 20.
  • Concentration: mean = 3.18, SD = 0.07, n = 20.
  • Cognition: mean = 3.30, SD = 0.08, n = 20.
  • Note: there is an inconsistency with the stated sample size in the text (n = 26) vs. the table (n = 20).

Regression Results (Table 2) and Model Fit

  • Reported model information (Table 2):
    • Model fit: R = 0.948,\, R^2 = 0.898,\, ext{Adjusted } R^2 = 0.839,
      F(7,12) = 15.11,\, p > 0.05.
    • This indicates the model explains approximately R^2
      ext{(approximately 89.8% of the variance in Performance)}.
  • However, the text also states a regression equation with:
    • F(7,12) = 15.109,\, p < .001 and R^2 = 0.90.
    • Note the inconsistency: one section reports p < .001, another reports p > .05 for the same model; both claim R^2 ≈ 0.90. This should be interpreted with caution.
  • Table 2 coefficients (predictors of Performance):
    • Motivation: B = 196.30,\, eta = 0.36,\, SE = 94.18,\, t = 2.08,\, p = 0.059.
    • Confidence: B = 84.70,\, eta = 0.40,\, SE = 43.63,\, t = 1.94,\, p = 0.076.
    • Anxiety Control: B = 47.88,\, eta = 0.47,\, SE = 26.36,\, t = 1.82,\, p = 0.094.
    • Mental Preparation: B = 51.16,\, eta = 0.32,\, SE = 24.25,\, t = 2.11,\, p = 0.057.
    • Team Emphasis: B = 35.29,\, eta = 0.19,\, SE = 39.00,\, t = 0.91,\, p = 0.383.
    • Concentration: B = 25.52,\, eta = 0.19,\, SE = 31.05,\, t = 0.82,\, p = 0.427.
    • Cognition: B = 33.00,\, eta = 0.30,\, SE = 23.24,\, t = 1.42,\, p = 0.181.
  • Interpretation: Although the model has a high overall fit (R^2 ≈ 0.90), none of the individual IVs reach conventional statistical significance (all p > 0.05 in Table 2).
  • The standardized beta coefficients are all positive, suggesting each factor moves Performance in a positive direction, but lack of statistical significance limits confidence in individual predictors.

Correlations Among Variables (Table 3)

  • Table 3 presents the correlation matrix among Performance and the seven IVs.
  • Reported correlations (Performance with each IV):
    • Motivation: r = 0.57
    • Confidence: r = 0.14
    • Anxiety control: r = 0.89
    • Mental preparation: r = 0.71
    • Team emphasis: r = 0.65
    • Concentration: r = 0.77
    • Cognition: r = 0.42
  • Note: The asterisk denotes significance at p < 0.05 (as indicated in the table). Some values (e.g., 0.14) may not be significant despite a small sample; the exact significance per variable isn’t consistently described outside the table.
  • Overall takeaway: There are positive relationships between performance and several psychological factors, with the strongest observed correlation with Anxiety control (r ≈ 0.89) and Concentration (r ≈ 0.77).

Visualizations (Figures 1–7)

  • Figure 1: Relationship between Performance and Motivation – positive linear trend with error bars.
  • Figure 2: Relationship between Performance and Confidence – positive linear trend with error bars.
  • Figure 3: Relationship between Performance and Anxiety control – strong positive trend with error bars.
  • Figure 4: Relationship between Performance and Mental preparation – positive trend.
  • Figure 5: Relationship between Performance and Team emphasis – positive trend.
  • Figure 6: Relationship between Performance and Concentration – positive trend.
  • Figure 7: Relationship between Performance and Cognition – positive trend.
  • Across Figures 1–7, the authors report positive linear relationships between each psychological construct and performance, with error bars indicating variability.

Discussion and Interpretation

  • Context: Psychology’s rising value in professional soccer; clubs recognizing psychological factors can aid performance (Raglin 2001).
  • Key constructs and definitions:
    • Motivation: external (extrinsic) vs internal (intrinsic) drivers (Bull & Sham, 1996; Seipp, 1991).
    • Confidence: trust or certainty in ability; two types (Patrick, 2014): reactive vs proactive.
    • Anxiety: somatic (physiological arousal), cognitive (worries), state anxiety (situational), trait anxiety (enduring tendencies); arousal should be balanced (Macleod, 1990; Taylor, 1996).
    • Mental preparation: readiness to perform, focus, ball control under competition (Taylor, 1996).
    • Team emphasis: interaction between individual and team; team dynamics influence individual performance (Unnithan et al., 2012).
    • Cognition: thoughts and their relationship to performance; positive cognitive strategies help focus and performance (Nideffer & Sagal, 1993).
  • Contextual examples and literature:
    • Elite clubs like Derby County (England) and Ajax (Netherlands) have integrated psychological assessment to improve performance (Vestberg et al., 2012).
    • Prior research emphasizes psychological skills as part of the broader set of factors influencing performance (MacNamara, Button & Collins, 2010; Helsen et al., 2000).
    • The study aligns with the broader view that performance in elite soccer is multifactorial, including physical, physiological, and psychological components.
  • The main finding: there is a strong relationship between psychological factors and performance; however, psychological factors alone do not deterministically predict performance in elite soccer players.
  • Theoretical synthesis: five-factor model of performance proposed by Rosch, Hodson, & Peterson (2000) includes technical, tactical, physiological, psychological, and team factors; psychology contributes but is not exclusively determinative.
  • Practical implications: coaches can leverage psychological skills training to address weaknesses and tailor interventions to individual players, recognizing that behavior and performance arise from multiple interacting factors.
  • Illustrative analogy: even highly skilled players may perform suboptimally if psychological factors are misaligned; conversely, strong psychological readiness can support peak performance, but is not a sole driver.

Implications for Practice

  • For coaches and practitioners:
    • Use PSIS-R5 or similar instruments to identify individual psychological profiles.
    • Implement targeted psychological skills training focusing on the strongest correlates (e.g., anxiety control, mental preparation, concentration).
    • Monitor changes over time and in response to competition demands; align psychological interventions with physical and tactical preparation.
  • Emphasize holistic development: physical conditioning, tactical understanding, and psychological readiness together contribute to high performance.
  • Be cautious about over-relying on psychological factors as the sole predictor of success; consider situational, team, and physiological variables as well.

Limitations and Future Research

  • Limitations acknowledged by authors:
    • Sample drawn from a single club; potential limitations in generalizability.
    • Discrepancies in reported sample size (n = 26 in text vs. n = 20 in tables).
    • The regression results show high model fit but lack of statistical significance for individual predictors, suggesting potential multicollinearity or insufficient power.
    • Eight-week observational window; longitudinal changes beyond this period are not captured.
  • Recommendations for future research:
    • Investigate effects by level of participation and gender differences in soccer performance.
    • Expand to multiple clubs and leagues to enhance generalizability.
    • Explore interactions among psychological factors and with physical/tactical variables.
    • Examine potential moderating/mediating roles of team dynamics and coaching practices.

Ethical Considerations and Disclosures

  • The authors report no conflicts of interest.
  • Ethical considerations implied by standard sports psychology research practices (informed consent, confidentiality) are assumed but not detailed in the text.

Connections to Foundational Principles and Real-World Relevance

  • The study connects to foundational sport psychology concepts: motivation, confidence, anxiety management, and cognitive strategies as keys to performance.
  • Real-world relevance: professional clubs increasingly invest in psychological services to support athlete development and performance under pressure.
  • The research aligns with a broader, multidisciplinary view of athletic excellence, integrating psychology with physical and tactical preparation.

Quick References to Key Findings (numerical highlights)

  • Regression model overview: approximately R^2 ext{ around } 0.90; reported as R^2 = 0.898 (Table 2) and R^2 ext{ near } 0.90 (text) with F(7,12) ext{ around } 15.11.
  • Model significance discrepancy:
    • Textual claim: F(7,12) = 15.109,\, p < 0.001
    • Table claim: F(7,12) = 15.11,\, p > 0.05
  • Individual predictor p-values (Table 2):
    • Motivation: p = 0.059
    • Confidence: p = 0.076
    • Anxiety Control: p = 0.094
    • Mental Preparation: p = 0.057
    • Team Emphasis: p = 0.383
    • Concentration: p = 0.427
    • Cognition: p = 0.181
  • Correlations with Performance (Table 3):
    • Motivation: r = 0.57
    • Confidence: r = 0.14
    • Anxiety Control: r = 0.89
    • Mental Preparation: r = 0.71
    • Team Emphasis: r = 0.65
    • Concentration: r = 0.77
    • Cognition: r = 0.42
  • Strongest observed individual correlations with performance: Anxiety Control (0.89) and Concentration (0.77).

Key Takeaway

  • There is a consistent, positive association between psychological factors and performance in elite soccer players, and the variables collectively relate to performance. However, psychological factors alone did not deterministically predict performance in the regression analysis within this study, highlighting the multifactorial nature of elite sport performance and the need for integrated training approaches.