Pre-performance routines are individualized tasks that are intended to prepare the athlete for correct execution. While the efficacy of pre-performance routines appears established, debate exists concerning temporal consistency. The current study examined pre-performance routine times and degree of difficulty of the top 16 state divers in the mid-western United States. Each of the 16 participants in the study performed 10 different dives with varying difficulty and scores. Significance was found between the top eight finishers and bottom eight finishers in mean pre-performance time. The top eight finishers had a mean pre-performance time of 6.18 seconds and the bottom eight finishers mean pre-performance time was 4.93 seconds. Significance was also revealed across the degree of difficulty of dives (easy, moderate, and hard) and their pre-performance times. Results support previous findings that suggest duration of pre-performance routines increase as difficulty increases, resulting in improved performance.
**Key Words:** Pre-performance routines, diving, duration
Pre-performance routines are intended to enhance performance by eliminating distractions and helping performers transfer thoughts from task-irrelevant to task-relevant cues (13). Pre-performance routines can occur in any type of sport; it appears to be most beneficial with self-paced tasks and closed-skill sports (e.g., tennis, bowling, and golf) (4). Pre-performance routines have been examined in a variety of fashions and across many sports. Two avenues of research that have emanated have examined the behavioral consistency and/or the temporal consistency of pre-performance routines.
The majority of pre-performance routine research has investigated behavioral consistencies that include specific movement patterns before and during execution of skills (e.g., dribbling a basketball, practice swings, etc.). Results of behavioral consistencies amongst pre-performance routines offer varying conclusions. For instance, Czech, Ploszay, and Burke (3) exmined the behavioral consistency of pre-shot routines in basketball free throw shooting. Results were not significant between routine or non-routine groups, however, the authors found a six percent increase in the free-throw percentage as the behavioral consistency of the pre-performance routine increased. In the most in-depth pre-performance routine research to date, Lonsdale and Tam (8) examined both temporal patterns and behavioral consistency of free-throw shooters of fifteen NBA players during the playoffs. Results revealed that players who adhered to behavioral routines were significantly (12.47%) more consistent free-throw shooters than those who were consistent with respect to duration alone.
The duration of pre-performance routines and performance outcomes also appears to be equiovical (1,5,7,8,14). Wrisberg & Pein (14) naturalistically observed the duration of collegiate basketball players pre-performance routines for free-throw shooting. They found a negative correlation (r = -0.41) between their free-throw percentage and routine duration. Similarly, Bell and colleagues (in-press) examined the temporal consistency of putting routines of collegiate golfers. The authors examined two separate NCAA Division I collegiate golf tournaments. The within-subject design across fifteen golfers revealed that deviation in pre-performance time resulted in a significant decrease in putting performance.
On the other hand, Jackson (5) examined 572 place kicks across 13 participants during the 1999 Rugby Union World Cup. The author examined difficulty of kicks, concentration times, and physical preparation times. Results revealed no differences amongst the best and worst kickers, but more importantly as situational pressure increased, players had longer concentration times (5). These results extended previous results suggesting that temporal consistency of pre-performance routines varies (6). In addition, research with elite tennis players and their pre-service routines showed a lack of temporal consistency amongst service routines with no significant difference in outcomes (4).
Varying results across behavioral and temporal consistencies of pre-performance routines may be due to the idiosyncratic tendencies across sports. For instance, examination of rugby kickers found that pre-performance routines were altered due to external factors such as time-outs and substitions (5). In addition, while no consistent service routines were found amongst elite tennis players, the authors only examined the first tennis serve (4). Tennis serving allows two service opportunties and within the professional ranks, first serves are intended for winning and/or establishing the point, which may cause more performance errors altogether. Delving further, Lonsdale & Tam (8) did not distnguish their analysis between type of free-throw attempts (e.g., one and one, two-shot, or one shot attempt) which may also have impacted results.
The sport of competitive diving is unique, and provides an excellent testbed for examining pre-performance routines. Each dive has a pre-determined degree of difficulty (DD) that increases with the number of twists and somersaults (10). Since difficulty and situational differences may account for increases in pre-performance times in other sports (5), analysis of pre-performance routine duration with specific difficulty ratings is warranted. The sport of diving actually operationally defines preparation time as any movement prior to take-off, which is the approach steps in a forward dive and the movement of the board for a reverse dive (10). Thus, due to the lack of any discernable behavioral measures, examining temporal patterns of pre-performance routines in divers is advantageous.
Research has yet to examine the pre-performance routines of a closed-skill, self-paced sport such as diving. The purpose of the current study was to examine the duration of pre-performance routines of high-school divers during a major competition to determine the extent of the significance, if any, with relation to the difficulty and outcome of the dive. Due to the lack of consistent findings across various sports, no formal hypothesis was formulated regarding the potential relationship between pre-performance routine and outcome. However, coinciding with results from Jackson (5) and Jackson and Baker (6), it was hypothsized that increased degree of difficulty dives would result in longer routine durations.
Participants were 16 female high-school level divers during a state championship meet. There were six seniors, four juniors, five sophomores, and one freshman. The authors used naturalistic observation in which the participants were unknowingly observed. Due to sensitive material for the demographics, no anthropometric data (e.g., height/weight) was made public, thus none was collected.
The research study took place at an indoor Division I collegiate aquatic facility. All dives took place on a one-meter springboard with 16 participants performing all 10 dives.
#### Design & Procedures
The current study involved direct observation by two researchers in which the participants were unknowingly being observed. The variable of pre-performance time (PPT) initiated when both feet of the participant were set in a fixed position on the diving board. The PPT ended when the participant took the first step towards the end of the board for a front approach or when the arms began to swing on a reverse dive. These two criteria were selected due to their consistency amongst all routines (10).
Degree of difficulty (DD) was recorded for each diver and was separated into three categories (easy, moderate, and hard). Degree of difficulty is the perceived difficulty in accordance with the local state high school association guidelines and is established prior to each competition year.
Easy Dives – Individual dives with a degree of difficulty ranging from 0-1.8.
Moderate Dives – Individual dives with a degree of difficulty ranging from 1.9-2.1.
Hard Dives – Individual dives with a degree of difficulty from 2.2 or higher.
Last, each diver compiled a Total Dive Score (TDS) for each dive. Each individual dive is given a score based upon 7 judges hired by the state high school athletic association. The highest two and the lowest two judge scores were dropped from the scoring. The remaining three scores were added together and multiplied by the degree of difficulty for that particular dive to form a total dive score.
(Judge score 1 + Judge score 2 + Judge score 3) x Degree of Difficulty = Total Dive Score
#### Data Collection Procedure
All ten rounds of dives were observed directly by two researchers. The researchers used a stopwatch to time the length of pre-performance routine to the tenth of a second. To help ensure reliability of measurement, the slower of the two times was used. Any times from the researchers that deviated from each other by over 5 tenths (.5) of a second were not used. The researchers also hand wrote the total dive score for each particular dive. Each measurement was put into a spreadsheet at the time of the study. Participants were given an identification label so that inferences could be made later in the study.
#### Data Analysis
The researchers used a median split strategy similar to Jackson (5) to identify the best and worst performers. In order to investigate differences in PPT for the highest and lowest scoring performers, the divers were separated into the top and bottom halves, using their total scores. The mean PPT values of the groups were then compared using an independent samples t-test to determine whether there were significant differences in time taken prior to dive for the highest and lowest scoring individuals.
In addition, a mixed effects analysis of covariance (ANCOVA) was used to examine the relationship between PPT and total dive score (TDS), as well as to compare the mean total dive score across the three dive difficulty conditions (Easy, Moderate and Hard). Sidak’s pairwise multiple comparison procedure was used to follow up a statistically significant dive difficulty effect (11). As well as testing the major effects of interest in this study, the mixed effects model also accounted for the repeated measures (10 dives) for each competitor.
Sixteen participants completed 10 rounds of dives. Total PPT was (M= 5.53, SD = 2.76 seconds) across 160 total dives. Results revealed a significant difference between the top eight finishers and bottom eight finishers at p < 0.05The eight participants with the highest dive scores displayed PPT (M= 6.18, SD= 2.93 seconds) which was significantly longer than the PPT (M=4.93, SD=2.42 seconds) of eight participants with the lowest scores Means and standard deviations across all 10 dives for the two groups are presented in Table 1.
Results from the mixed effects model appear in Table 2. Both PPT and DD were treated as fixed effects, while the diver was treated as a random effect in this analysis. The slope relating PPT to the total score was statistically significant and positive, b= 0.089, SE= .028, df =155, p= .002, 95% CI [.033, .144] indicating that the longer the PPT the higher the total score on a given dive. This model also revealed a significant difference between levels of DD on the mean final score.
Table 3 shows the mean and standard deviation of total dive score (TDS) for each of the degree of difficulty (DD) groups. As described previously, in order to determine which means were significantly different across DD, Sidak’s (11) method for multiple comparisons was used. Statistically significant differences across levels of DD were found for all comparisons except between the hard-to-moderate groups. The easy to moderate and easy to hard DD groups had significantly different means (p<0.001), as did the moderate to easy and hard to easy DD groups (p<0.001).
Pre-performance routines have been noted across various sports and in different fashions (13). However, research is equivocal regarding duration and performance outcomes. To date, research has yet to examine pre-performance routines that account for specific degrees of difficulty. The purpose of this study was to examine possible relationships between the duration of diver’s pre-performance routine, degree of difficulty, and outcome.
Results revealed that the top eight finishers took significantly longer in the preparation time than the bottom eight finishers of the competition. There was over a one second difference (1.25 seconds) between the two groups, which is contrary to recent research suggesting no difference in preparation times between the best and worst performers (5).
In support of the hypothesis, results indicate that the degree of difficulty had a significant effect on pre-performance times, as dives increased in difficulty, pre-performance times also increased. These findings appear consistent with current research in that preparation times increased with regard to difficulty (5, 6).
Contrary to other pre-performance routine research (8), the sport of diving appears to distinquish pre-performance routines as cognitive rather than behavioral due to the lack of any movement prior to takeoff (10). Thus, it is safe to assume that the pre-performance routines by the divers consisted of strictly cognitive preparation (e.g., self-talk, imagery) as opposed to any observable behavioral tendancies (e.g., dribbling a basketball). Although speculative, due to the methodology and scores of the dives, more difficult dives seemed to require additional mental processing as opposed to easier dives with little thought (12).
Methodologically, one should consider the closed skill of competitive diving. Perhaps after the first several rounds, some divers could not significantly advance in the standings and merely “went through the motions” on the springboard. On the other hand, the top-positioned divers may have taken more preparation time as result of their scores and positions. Unfortunately, due to the lack of qualitative measurements of the divers themselves, this limitation should be acknowledged. In addition, the lack of insight into the athlete experience appears to be a major limitation of all recent pre-performance routine research (1,4,5,8,9).
Wrisberg and Pein (14) state that the skilled performer will demonstrate a more consistent routine than a less skilled performer despite individual differences. While Wrisberg and Pein (14) examined basketball players across an entire season, the current study only directly examained one major competition. The changes in pre-performance time in the current study may be attributed to the previous diving and competition experience. It may also be neccesary to suggest the small sample contributed to these findings.
Whereas the sport of diving lends credence to the temporal consistency of pre-performance routines, further research is needed. A triangulation of data collection may yield greater results. Specifically, a within-subject design that examines both the duration of routines and behavioral components, and obtains qualitative inquiries from divers appears to offer a concrete strategy of data collection. Most important is the data collection of repeated measures across an entire season (14).
To date, the current study is the first to examine divers’ pre-performance routines. Consistent with previous research, as difficulty increased, performers had longer pre-performance routines (5). There was also a significant difference in pre-performance routines between the top eight finishers and the bottom eight finishers. In contradiction to past research results (1,8), longer preparation times may be indicative of improved performance. Lastly, examining the temporal consistency of pre-performance routines for a self-paced skill appears to provide insight into concentration times and, in turn, effective performance.
### Applications in Sport
Cohn (2) states that within any routine is the sport itself, along with actual nature of the required task. Whereas, it is difficult to transfer these findings across sports that incorporate behavioral tendencies (e.g., golf, rugby, basketball), athletes should nonetheless develop consistent pre-performance routines. Consistent with previous research, the most important aspect of pre-performance routines appears to be an appropriate attentional focus (8). Coaches across all sports should help athletes incorporate effective attentional cues (e.g., internal/external) within their routine depending on the skill level of the performer (for a review see Lindor & Singer, 7). As mentioned previously, future pre-performance routine research should incorporate a triangulation of data that encompasses temporal, behavioral, and qualitative data within applied sport settings.
#### Table 1
Mean (standard deviation) PPT* of All Dives Examined from the Top 16 Finishers
|Category||Number of Dives||PPT (seconds) SD (seconds)|
|All Drivers||160||5.53 (2.76)|
|Top 8 Finishers||80||6.18 (2.93)|
|Bottom 8 Finishers||80||4.93 (2.42)|
* PPT=Pre-performance time
#### Table 2
Effects of PPT* and DD** Groups with Type III Tests of Fixed Effects with the Score as the Dependant Variable
|Source||Numerator df||Denominator df||F||P|
**Note:** Dependent Variable is Score
* PPT=Pre-performance time
** DD=Degree of difficulty
#### Table 4
Total Dive Score means of DD* Groups
Note: Means that do not share subscripts (e.g., a, b) differ at p
#### Graph 1
Total Dive Score means of DD* Groups
![Mean score](/files/volume-13-number-4/5/graph-1.jpg “Mean score”)
Note: * Significance at 001.
### Corresponding Author
Robert J. Bell, Ph.D
Ball State University
Muncie, In 47306
### Author Bios
Robert J. Bell, Ph.D
Ball State University
W. Holmes Finch, Ph.D
Ball State University
Zach Whitaker, M.A.
Santa Clara Diving