# Identification of Key Performance Indicators for T20--A Novel Hybrid Analytical Approach
## 1 Introduction  
Cricket, with its rich history and global fan base [1], has evolved into a multifaceted sport with various components that affect player and team performance [2]. Performance analysis is an essential component in evaluating players, teams, and match strategies, thereby facilitating evidence-based decision making to predict and enhance performance tactically [3, 4, 5]. Performance analysis is the process of recording and analysing players' performances during practices and competitions [6, 7]. It focuses on recording discrete categories of cricket information, such as important biomechanical characteristics, match statistics, and tactical and technical decision-making features [6]. All of this data is used to inform and support the coaching process and, ultimately, to enhance match performance [8, 9]. The methods employed in match analysis usually involve performance data about thebatters' run-scoring capabilities and the bowlers' wicket-taking abilities [10]. Several studies explored the factors that influenced performance in T20 cricket, such as batting, bowling, and fielding [11; 12; 13; 14; 15; 16; 17]. These factors are generally known as performance indicators (PIs) [8]. These performance indicators (PIs) refer to metrics that provide broad aspects of matches, which are used to evaluate and gain useful information on the players' and teams' performances [3; 8; 17]. Key performance indicators (KPIs) are a subset of PIs and are considered critical for assessing the team's performances and successes [8; 18]. These metrics are significantly associated with successful performance and winning a match [8; 18]. To date, there are few studies which determine the KPIs that predict successful performance in professional T20 cricket matches [11; 12; 13; 14; 15; 16; 17]. Current research highlighted that the KPIs, specifically for batting, were scoring more boundaries, scoring more runs in the middle eight overs (7 th-14 th), and achieving a higher run rate during the middle and final overs, namely, 7 th-16 th and 17 th-20 th overs [11; 12; 13; 14; 15; 16; 17]. Furthermore, individual and partnership scores of 50 or more runs had a significant effect on winning a match [12; 13; 15]. Furthermore, the KPIs, specifically for bowling, were taking more wickets during a match [13; 14; 16], how quickly the first three to five wickets were taken [11], losing fewer wickets in both the powerplay phase [12; 15] and between the 7 th-10 th overs of a match [15], taking wickets in the last six overs (15 th-20 th) [14; 16], and bowling more dot balls in a match [12; 13]. [PERSON] and [PERSON] [17] also indicated that fielding run outs and taking catches were also essential KPIs. A total of seven articles were identified that investigated KPIs in cricket, of which five compared match statistics between winning and losing teams [12; 13; 14; 15; 16]. All five studies ranked the KPIs based on effect size. These five studies analysed a range of domestic and international T20 matches, with sample sizes varying from seven to fifty-six matches. The statistical analyses applied in these studies were appropriate but lacked clarity and sufficient detail [12; 13; 14; 15; 16]. Specifically, while comparative statistical tests, such as T-tests, have been used to determine differences in PIs between winning and losing matches [12; 13; 14; 15; 16], conducting multiple T-tests on a large number of PIs significantly increases the likelihood of Type 1 error (i.e., incorrectly rejecting a null hypothesis) due to an inflated proportion of false positive results [19]. The use of T-tests in these studies presents a significant limitation, as it may overlook the potential negative effects resulting from interactions or correlations between various PIs, thus limiting their predictive capabilities [20]. This contrasts with the existing literature focusing on a few pre-selected KPIs in T20 cricket matches [12; 13; 14; 15]. Since cricket is a complex and dynamic sport, selecting KPIs can be challenging [8; 11].