# Comparison and evolution: seeing the athlete in the context of the match > Compare up to 4 practical shooting athletes: season-by-season progress, radar chart, time vs points correlation and hit factor side by side. Free. Resumo (pt-BR): **Comparativo e evolução: enxergar o atleta no contexto da prova**. Compare até 4 atletas de tiro prático: evolução por temporada, gráfico radar, correlação tempo × pontos e hit factor lado a lado. Grátis no Scoring Services. This file: https://scoring.services/pages/athlete-evolution.md HTML page: https://scoring.services/pages/athlete-evolution (pt-BR), https://scoring.services/pages/athlete-evolution?lang=en, https://scoring.services/pages/athlete-evolution?lang=es Open the tool: [Compare athletes](https://scoring.services/tools) Comparing athletes only makes sense with the same division and category filters. Evolution only makes sense with a consistent historical series. This page brings the two concepts together and points you to the right tools. ## Open comparison now Public form with Plotly on the home page. [Compare athletes](https://scoring.services/tools) ## Quick actions - [5 steps to compare](https://scoring.services/pages/comparative-graphs.md): Tutorial in the IPSC guide. - [Radar chart](https://scoring.services/pages/athlete-evolution.md): Visual competitive profile. - [IPSC Guide](https://scoring.services/pages/ipsc-guide.md): Technical index by topic. ## What you get on this page - Side-by-side comparison (hit factor, time, points). - Historical evolution by year and modality. - Radar and correlation chart for competitive profile. ## Quick summary - Side-by-side comparison (hit factor, time, points). - Historical evolution by year and modality. - Radar and correlation chart for competitive profile. - See the sections below and the shortcuts to apply to your match or broadcast. ## Comparison in the same match The classic flow: select match, division and up to four athletes; generate PSBL graphs and tables. On the website, use /tools (main form). In the IPSC guide, /pages/comparative-graphs and /pages/comparative-graphs detail the step-by-step instructions in the IM hub. ## Evolution over time Filters by year, discipline and division feed into trend graphs — useful for seeing if changing equipment or training has changed average hit factor. APIs: /get_athletes_for_evolution, /generate_evolution_graph. Educational content at /pages/ipsc-analysis-guide. ## Radar and correlation The radar graph summarizes dimensions (HF average, best worst stage, consistency). Time×points correlation helps you see if you buy a score with risk. Pages: /pages/athlete-evolution and /pages/athlete-evolution. ## Performance Classified Details After comparing, open /pages/athlete-search for adaptive benchmarking and reading the performance classification in the chosen match. ## Evolution vs snapshot of a match A match answers “how I was today”; evolution crosses several stages at /atleta. Combine with /pages/ranking-elo-ipsc for level trending. ## IPSC radar graph for competitive profile reading The radar chart transforms several indicators into a single view of the athlete's profile, facilitating technical comparison. ## What the radar shows in practice The radar graph aggregates, on different axes, the average hit factor (HF), best and worst HF between stages and the number of stages — useful to see at a glance whether the athlete is stable (“closed” polygon) or depends on peaks in a few stages (irregular shape). HF is points divided by time on the stage, using the same criteria as the regulations applied to the match. ## How to turn radar into action Use the radar to identify imbalances: athlete with strong peaks and low consistency, or regular athlete without technical ceiling gain. ## Practical value for evolution Radar reading helps the athlete quickly identify performance patterns and prioritize adjustments based on real match data. ## Interpret the polygon Irregular shape = dependence on few stages; balanced polygon = consistency. Combine with /pages/athlete-evolution. ## IPSC Correlation Analysis for Technical Decision The correlation between time and points helps identify whether the athlete is losing performance due to pace, precision or balance. ## How correlation supports the athlete The documentation highlights correlation analysis in the graphs tab. It helps to see if increasing the pace is dropping points or if there is room for acceleration with control. ## Practical use in the post-match With correlation, athlete and coach validate hypotheses with data: where to reduce time without losing quality and where to prioritize precision to avoid penalties. ## Content applied to the training routine This theme helps athletes and coaches make more objective decisions, using the relationship between time and points to define priorities for the next cycle. ## Correlation and pacing decision If increasing the pace drops points in the correlation, prioritize precision in the next sessions. If there is room, practice transitions. Combine with /pages/performance-heatmaps and /pages/ipsc-analysis-guide. ## Frequently asked questions ### How many athletes can I compare? Up to four in the hub's documented comparison; the form in /tools follows the same multiple selection logic. ### Do comparative and evolution use the same data? Same aggregate bank of imported evidence; different filters (single match vs time series). ### Export graphics? In the IM hub, PNG export is available in several views — see documentation at /docs. ### How many athletes can I compare at once? Up to four in the main /tools stream and in the match hub graphics. See also /pages/comparative-graphs. ### Radar replaces analysis with stages? No. Radar summarizes profile; analysis by stage deepens the diagnosis. ### Who should use radar? Athletes, coaches and organizers who need to quickly compare profiles. ### Where do I access the radar? In the graphics tab within the athlete comparison in the match hub. ### Does the radar replace the results table? No. It summarizes dimensions for quick comparison; numerical details are located in /pages/athlete-search and /pages/stage-data-analysis. ### What metrics does the radar chart compare? The comparative profile uses average hit factor, best HF, worst HF and athlete's number of stages — useful for comparing consistency between competitors. Complete comparison at /pages/comparative-graphs. ### Is high correlation always good? It depends on the context. The goal is to understand the direction of the relationship and how it affects the competitive outcome. ### Do I need to know statistics to use it? No. Visualization already facilitates interpretation and the platform offers context for reading. ### Where to apply this learning? In training planning between events, with review by stage and division. ### Do I need to login to check match results? Most IPSC consultations and guidance are public. Import and management flows use login.scoring.services; what is open without registration is in /pages/ipsc-results. ### What does correlation analysis show in IPSC? The statistical relationship between Time and Points for each athlete along the stages. Correlation close to zero indicates balance; very negative suggests that accelerating drops points. See also the profile at /pages/athlete-evolution and the map at /pages/performance-heatmaps. ## Related guides - [IPSC comparative graphs — analyze rivals like PractiScore Competitor](https://scoring.services/pages/comparative-graphs.md) - [IPSC radar graph for competitive profile reading](https://scoring.services/pages/radar-graphs.md) - [Practical Shooting Statistics: From Raw Number to Training Decision](https://scoring.services/pages/shooting-stats.md) ## Reference for agents - [Como a plataforma funciona](https://scoring.services/docs/platform.md) - [llms.txt](https://scoring.services/llms.txt) - [llms-full.txt](https://scoring.services/llms-full.txt) Cite match numbers as imported analysis data, not federation homologation.