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Applied psychologists have long been interested in examining expert performance in complex cognitive domains. In the present article, we report the results from a study of expert cognitive skill in which elements from two historically distinct research paradigms are incorporated -- the individual differences tradition and the expert-performance approach. Forty tournament-rated SCRABBLE players (20 elite, 20 average) and 40 unrated novice players completed a battery of domain-representative laboratory tasks and standardized verbal ability tests. The analyses revealed that elite- and average-level rated players only significantly differed from each other on tasks representative of SCRABBLE performance. Furthermore, domain-relevant practice mediated the effects of SCRABBLE tournament ratings on representative task performance, suggesting that SCRABBLE players can acquire some of the knowledge necessary for success at the highest levels of competition by engaging in activities deliberately designed to maximize adaptation to SCRABBLE-specific task constraints. We discuss the potential importance of our results in the context of continuing efforts to capture and explain superior performance across intellectual domains.

Competitive Scrabble players spend a mean of 4.5 hr a week memorizing words from the official Scrabble dictionary. When asked if they learn word meanings when studying word lists, only 6.4% replied "always," with the rest split between "sometimes" and "rarely or never." Number of years of play correlated positively with expertise ratings, suggesting that expertise develops with practice. To determine the effect of hours of practice (M = 1,904), the authors compared experts with high-achieving college students on a battery of cognitive tests. Despite reporting that they usually memorize word lists without learning meanings, experts defined more words correctly. Reaction times on a lexical decision task (controlling for age) correlated with expertise ratings, suggesting that experts develop faster access to word identification. Experts' superiority on visuospatial processing was found for reaction time on 1 of 3 visuospatial tests. In a study of memory for altered Scrabble boards, experts outperformed novices, with differences between high and low expertise on memory for boards with structure-deforming transformations. Expert Scrabble players showed superior performance on selected verbal and visuospatial tasks that correspond to abilities that are implicated in competitive play.

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I notice scrabble has Elo ratings, but the references are different than chess for example. What would an average scrabble rating be? How about for an Expert, Master or Grandmaster, or novice player?

What actually separates master and expert level players from average ones? From the outside it looks like knowing all of the two and most of the three letter words and common bingo roots is about all there is to study to become a good player. But I imagine that is not really correct.

Above are the results of unscrambling expert. Using the word generator and word unscrambler for the letters E X P E R T, we unscrambled the letters to create a list of all the words found in Scrabble, Words with Friends, and Text Twist. We found a total of 24 words by unscrambling the letters in expert. Click these words to find out how many points they are worth, their definitions, and all the other words that can be made by unscrambling the letters from these words. If one or more words can be unscrambled with all the letters entered plus one new letter, then they will also be displayed.

Use this Scrabble dictionary checker tool to find out whether a word is acceptable in your scrabble dictionary. When you enter a word and click on Check Dictionary button, it simply tells you whether it's valid or not, and list out the dictionaries in case of valid word. Additionally, you can also read the meaning if you want to know more about a particular word.

The potential for near transfer of Scrabble skills has been tested in studies involving the standard word recognition task, lexical decision (LDT; Halpern and Wai, 2007; Hargreaves et al., 2012; Protzner et al., 2016). As in competitive Scrabble, LDT requires that participants work with letter strings and distinguish words from non-words. In the LDT, however, words and non-words are presented one string at a time on a computer screen. Further, while Scrabble requires that players create words that maximize point scores from randomly selected letters, LDT does not. In LDT, Scrabble expertise is associated with faster responses (Halpern and Wai, 2007; Protzner et al., 2016), especially for stimuli presented vertically (Hargreaves et al., 2012). That is, while vertically presented strings are more difficult for all readers to process (Howell and Bryden, 1987), the vertical presentation disadvantage is attenuated for Scrabble experts. This finding was attributed to experience-driven flexibility in orthographic encoding (Hargreaves et al., 2012). Because Scrabble play involves experience with vertical word recognition, Scrabble players develop the ability to efficiently extract orthographic information even from vertically presented stimuli. It is not clear, however, whether this vertical fluency for Scrabble experts is limited to letter stimuli or whether it might transfer to non-letter visual stimuli.

fMRI analysis 1, two-group hypothesis-driven task PLS examining group differences in SDT. On the brain images we illustrate regions with maximal activity differentiation between control and Scrabble groups during the SDT. The brain is displayed in 3-plane view according to neurological convention (L = L). Yellow regions represent increased activity for the control group, and blue regions represent increased activity for the Scrabble expert group. The brain scores bar graph captures the mean brain score for each condition in each group. The error bars indicate the 95% confidence intervals derived from bootstrap estimation. Hor, horizontal presentation; Ver, vertical presentation; SDT, Symbol Decision Task.

fMRI analysis 2, two-group data-driven behavior PLS examining brain-anagramming score correlations in SDT, LV2. On the brain images we illustrate brain-anagramming score correlations during the SDT. The brain is displayed in 3-plane view according to neurological convention (L = L). Regions highlighted in yellow indicate a positive correlation between higher anagramming scores and increased activation across all task conditions for controls. Regions highlighted in blue indicate a positive correlation between higher anagramming scores and increased activation during horizontal no-match and vertical match/no-match for Scrabble experts. The correlation bar graph captures the condition-dependent correlations between our behavior measure (anagramming scores) and the regions identified in the brain images. Hor, horizontal presentation; Ver, vertical presentation; SDT, Symbol Decision Task; LV, Latent Variable.

ERP source model analysis 1, amplitude-anagram score correlations for controls (top) and Scrabble experts (bottom) in the right medial temporal source waveform at 335 ms. Amplitudes are averaged across SDT conditions for each participant and linear fits are also plotted for each group.

Several previous studies in language and other domains have identified differences between the neural networks activated across groups in the absence of differences in task performance (e.g., Bennett et al., 2001; Grady et al., 2010; Hargreaves et al., 2011; McIntosh et al., 2014). In the context of expertise, Maguire et al. (2003) examined expert memorisers and non-expert controls, and reported group differences in the neural regions engaged during both familiar and unfamiliar memory tasks. However, engaging these brain regions during the unfamiliar task did not result in a behavioral advantage for the expert memorisers. These results suggest that experts developed a task strategy that was not available to the controls, and, despite no behavioral benefit, experts employed this strategy in an unfamiliar context. Thus, it is possible that the different neural mechanisms engaged by Scrabble experts during a lexical task, such as visual perceptual and long-term working memory regions, may also be engaged in an unfamiliar non-lexical task that shares similar processing components. As such, we next examined whether Scrabble experts would show far transfer in brain by engaging different neural mechanisms compared to controls during SDT performance.

Our fMRI results showed a significant difference between groups in the regions engaged during the SDT. Specifically, regions engaged by Scrabble experts in the SDT were more widespread, including extensive activity in posterior visual regions, as well as temporal and parietal language regions and their right hemisphere homologs. These results align with the expertise literature, with respect to recruitment of additional regions as well as greater bilateral activity in expert groups (Bilali et al., 2011, 2012; Guida et al., 2012; Proverbio et al., 2013). In contrast, the control group engaged fewer regions, with activity found predominantly in temporal and frontal regions. These findings suggest that Scrabble experts and controls use different neural substrates to support SDT performance, but the findings do not link differences specifically to Scrabble expertise.

To link brain changes directly to Scrabble expertise, we constrained our analyses to show only those brain regions in which changes in activity were associated with a measure of Scrabble expertise: anagramming scores. This analysis identified both commonalities and differences between groups. Commonalities among regions (i.e., regions that were associated with individual differences in anagramming that did not vary by group or task condition) included the left middle temporal and medial frontal gyri, as well as the right precentral gyrus and temporal pole. Thus, our results suggest that for both groups, higher anagramming scores were associated with greater reliance on these regions regardless of orientation or whether stimuli contained matching symbols. The EEG data provided additional insights about the time course of processing in these common regions. For both Scrabble experts and controls, higher anagramming scores were correlated with increased amplitude of the P300 component in the right medial temporal source waveform. The P300 typically peaks around 300 ms post-stimulus at centro-parietal electrodes with neural generators in temporal and parietal regions (Polich, 2007; Dong et al., 2015), consistent with the timing and location of our source locations. This component has been associated with working memory and attentional processing (Patel and Azzam, 2005; Polich, 2007; Portella et al., 2012), and greater P300 amplitudes have been found to correlate positively with working memory capacity (Dong et al., 2015). Interestingly, this finding suggests that regardless of group membership (i.e., expert or control), participants with greater anagramming scores may have greater long-term working memory capacity in the SDT, as evident by greater P300 amplitudes in the right medial temporal lobe. This is consistent with Tuffiash et al. (2007) anagrammatic word-identification skill hypothesis, which proposes anagramming skill to affect domain-specific long-term working memory, although in our case, it applies to all participants with greater anagramming skills, not exclusively to Scrabble experts. However, given the heterogeneity of the timing of the P300 across tasks and modalities in the literature, an alternative explanation is that larger P300 amplitudes may reflect less variability in the participants who are performing the tasks more efficiently. ff782bc1db