# Structured Summarization of League of Legends Match Data Optimized for Large Language Model Input
## 4 Experiments
### Quantitative Evaluation
#### 4.2.2 Component-Level Analysis  
The compacted match data generated by the LoL-MDC were divided into four main components: match overview, team and player statistics, timeline view, and selected key events. Tables 3 and 4 summarize the compacted sizes and token counts for these components in the NA and KR regions for the 14.22 patch, respectively. This analysis highlights the relative size of each component and their adaptability for different configurations.  
Team and player statistics consistently accounted for the largest portion of the compacted data. In the NA region, this component averaged 2197.53 bytes, corresponding to approximately 900 tokens in cl100k_base and 889 tokens in o200k_base. In the KR region, the size was slightly larger at 2286.33 bytes, with 956 tokens in cl100k_base and 913 tokens in o200k_base. The increased size in the KR region is primarily due to linguistic differences, such as longer champion names and player IDs in Korean.  
In contrast, match overview was consistently the smallest component across both regions. It averaged about 220 bytes and 79 tokens regardless of tokenizer or region. This component contains metadata such as the match ID, game title, patch version, participating teams, and match duration. Its small size reflects its role as a concise summary of the match's context.  
The timeline view and selected key events occupied intermediate positions in terms of size. In the NA region, the timeline view averaged 681.31 bytes, translating to approximately 349 tokens in both tokenizers. The selected key events averaged 735.96 bytes, corresponding to 246 tokens in c100k_base and 242 tokens in o200k_base. The KR region followed a similar pattern, with the timeline view averaging 773.86 bytes and the selected key events averaging 866.91 bytes.  
The sizes of these components, particularly the timeline view and selected key events, demonstrated the flexibility of their size. For example, the size of the timeline view depends  
\begin{table}
\begin{tabular}{l c c} \hline
**Metric** & **14.21 NA** & **14.22 NA** \\ \hline Raw Size (bytes) & 173,284.81 & 149,324.22 \\ Compacted Size (bytes) & 4219.55 & 3929.28 \\ Raw Token Count (cl100k\_base) & 89,410.73 & 75,849.92 \\ Compacted Token Count (cl100k\_base) & 1721.49 & 1591.07 \\ Raw Token Count (o200k\_base) & 88,589.34 & 75,008.02 \\ Compacted Token Count (o200k\_base) & 1705.87 & 1576.12 \\ \hline \end{tabular}
\end{table}
Table 1: Averaged data size and token counts for North America (NA) matches in English.  
\begin{table}
\begin{tabular}{l c c} \hline
**Metric** & **14.21 KR** & **14.22 KR** \\ \hline Raw Size (bytes) & 162,954.40 & 163,989.32 \\ Compacted Size (bytes) & 4226.73 & 4240.62 \\ Raw Token Count (cl100k\_base) & 83,914.27 & 84,477.72 \\ Compacted Token Count (cl100k\_base) & 1743.96 & 1750.54 \\ Raw Token Count (o200k\_base) & 83,032.83 & 83,598.03 \\ Compacted Token Count (o200k\_base) & 1689.48 & 1694.96 \\ \hline \end{tabular}
\end{table}
Table 2: Averaged data size and token counts for Korea (KR) matches in Korean.  
on the time intervals used to aggregate data; shorter intervals result in finer-grained data but increase the size, whereas longer intervals reduce granularity and compact the representation. Similarly, the size of the selected key events is directly influenced by the number of events recorded. Saving only a few key events minimizes its size, whereas recording more events increases the component's footprint. This adaptability allows the LoL-MDC to balance data granularity with token limitations.