Expert Performance in Sport Flashcards
Jackson et al. (2006) - poor performance under pressure
Poorer performance in lab-based studies than manipulated pressure
Toma (2017) - poor performance under pressure
Lower free throw success at the end of basketball matches when the score is close
Lidor et al. (2021) - poor performance under pressure
Lower 3-point shot success for open than contested shots in basketball
Senta et al. (2024) - Muscle tension as a direct effect of pressure
- task was to move a lever a specific amount
- had 4 days of learning prior to experiment
- tested in conditions with increasing reward
- some people did better under highest reward conditions, and some did worse
- biceps and triceps muscles tension increased for those who performed worse under pressure
- performance under pressure was correlated with the activation of the sympathetic nervous system
Turner at al. (2014) - implication of task framing on TCTSA (bean bags)
- changed instructions of bean bag throw to manipulate resource appraisal
Challenge group - high self-efficacy, approach focus, high control
Threat group - low self-efficacy, avoidance focus, low control - challenge group did significantly better than threat group
- challenge group had increased cardiac output but lower blood pressure than threat group
Turner at al. (2014) - implication of task framing on TCTSA (climbers)
-changed instructions of climbing video
Challenge group - high self-efficacy, approach focus, high control
- more attended session, higher ratings of self-efficacy and control, higher cardiac output
Threat group - low self-efficacy, avoidance focus, low control
- less attended session, higher ratings of excitement and happiness (unexpected)
Smith et al. (2001) - mental effort and performance in low vs high anxious
- volleyball performance over a season (examining close call sets)
- both high and low anxious expend more mental effort in high pressure situations
- performance decreases in high anxious and increases in low anxious athletes
Janelle et al. (1999) - pressure on central and peripheral tasks
- racing simulator under pressure
- central task = racing simulator
- peripheral task = respond to red lights, ignore green lights
in the competition phase - response to red light increased and lap times were slower
Wilson et al. (2009) - attention to threat-related stimuli (football)
- high pressure increased fixations (26%) and fixation time (56%) to goal keeper
- kicks 14cm closer to centre of goal indicating decreased efficiency
Woodman et al. (2015) - ironic process theory
- male hockey players
- ‘ironic’ errors increased under high anxiety (you are more likely to hit the zone you are trying to avoid)
Gray et al. (2017) - ironic effects and reinvestment
- experienced baseball pitchers
target only group = told to aim at target - no ironic error failures
ironic display group = aim at target but also had an ironic display - increased hits into the ironic zone by 300%
Oudejans & Pijpers (2009) - acclimatisation training
- meta analysis of 14 studies of basketball players
- anxiety manipulation did not create high anxiety situations in training
- after pressure training no decrease in anxiety feeling in competitions BUT performance was better
- suggests techniques have been learnt to cope with pressure / anxiety
Jordet & Elferink-Gemser (2012) - stressors in football matches
- stressors were taken at the end of extra time (n=35)
- 17 were relating to uncertainty over penalty takers and kick order
- 19 were relating to the wait
- 4 related to the walk up to the penalty
Wrisberg & Pein (1992) - importance of routine consistency
- varsity (expert) and intramural (beginner) basketball players
- better players had more ‘internally’ consistent routines
- even when routine time stayed the same, poor performance increased when rhythm varied
Lonsdale & Tam (2008) - routine time and rhythm
- NBA play off games
- most successful when normal routine is followed
- adding or changing behaviour decreased performance
- simply omitting behaviour does not change performance
Jackson & Baker (2001) - routines and task difficulty
- routine / concentration time increased by 50% from easy to difficult rugby kicks
- concentration time strongly relates to ‘post angle’
- relationship between kick difficulty and time spent before kick BUT kickers thought they were spending the same amount of time
Jonny Wilkinson - international rugby and Singer’s 5-step strategy
- routine simplified to 3 simple cues: ‘spot’, ‘line’ and ‘follow through’
- ready (clasped hands as a mental barrier against distractions)
- image (visualise the ball - ‘line’ and ‘follow through’)
- focus (concentrate on a specific part of the ball, and a specific point in the crowd - ‘spot’)
Vine et al. (2011) - ‘quiet eye’ training
- 22 high skilled golfers, 3 & 10 ft putts at high and low pressure
- training included feedback and instruction on eye gaze in relation to the ‘elite prototype’
- QE trained maintained performance under high pressure (24% difference in performance between QE trained or not)
- QE trained had 2 fewer putts per round
- Qe time stops any rushing due to pressure
Allard et al. (1980) - pattern recall
- compared recognition and recall ability for structured and unstructured images of university basketball players and non-players
- expertise effect:
— players better on recognition, but expertise effect disappears when there is no structure in game tactics
Williams et al. (2006) - pattern recognition
- skilled vs recreational footballers tested on recognition test
- test 1 = retain pattern of players but got rid of superficial information (changed players to dots)
- skilled footballers had faster and more accurate recognition (expertise effect)
- test 2 = occulsion of player information (how players interact with each other)
- occulsion mostly affected skilled players because they make ‘meaningful association’ from players visual information
Murphy et al. (2024) - pattern recognition
- tested ability to identify threat (shooter) as play evolves (10 seconds –> 2 seconds before shot is taken)
- shooter identification became progressively earlier as goalkeeper expertise increases
Macquet (2009) - Recognition-Primed Decision Model
- post match interviews with volleyball players watching match footage
- large majority were Level 1 of Klein’s Recognition-Primed Decision Model
Raab & Johnson (2007) - gut instinct
- 60% of handball players ‘take the first’ option when making decisions (and its usually the best one)
Klatt et al. (2019) - decision generation
- German and Brazilian academy footballers
- showed clips of play and then asked to pick decision, then given 45 seconds to pick more options
- quality of first option correlated with number of options generated
- first option usually best, and quality decreases with number of decisions generated