Trendlines, Race Maps & The Value Behind xG: The Trends
Jul 31, 2024
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Josh Williams, an expert in football statistics and analysis, dives deep into the fascinating world of football metrics. They explore the significance of post-shot expected goals in assessing goalkeeper performance, breaking down complex shot dynamics. The discussion emphasizes how expected goals can illuminate player value, particularly in Liverpool's recent transfers. Key insights into Liverpool's tactical approaches against major rivals highlight the impact of statistics on performance analysis. Tune in to discover how data shapes modern football!
Post-shot expected goals (PSXG) effectively assesses both goalkeeper performance and finished shot quality, revealing crucial insights into player abilities.
Race charts and trend lines visually capture game dynamics and team performance over time, offering deeper strategic understanding beyond final scores.
Deep dives
Understanding Post-Shot Expected Goals (PSXG)
Post-shot expected goals (PSXG) is a measurement used primarily to evaluate the effectiveness of goalkeepers and the quality of finishes by players. A shot must be on target to generate a PSXG, meaning that missed shots automatically receive a value of zero. This model takes into account factors like shot velocity and angle, allowing for nuanced analysis of a player’s finishing ability. For example, a straightforward tap-in might have a PSXG of 1.00, confirming that the shot is expected to result in a goal, while less straightforward attempts can show lower PSXG values and highlight the goalkeeper's effectiveness.
Evaluating Goalkeeper Performance
Goalkeeper performance can be assessed through statistics such as goals saved above average, which quantifies how many goals they save compared to typical expectations. For instance, during a season, a goalkeeper like Alisson may save 6.54 goals above average, demonstrating his capability in critical situations. Conversely, a goalkeeper like Jason Steele at Brighton can have a negative value, indicating he has allowed more goals than expected, showcasing inconsistent performances. This evaluation allows teams to recognize the value and financial implications of securing elite goalkeeping talent.
Utilizing Race Charts for Game Analysis
Race charts provide visual representations of a game's dynamics, such as expected goals (XG) and the context of the match, including player advantages or disadvantages like red cards. For example, in a match where Wolves were reduced to ten men, race charts illustrated Liverpool's dominance in expected goals, highlighting how situational factors can shift game narratives. Additionally, charts can inform discussions about a team's overall performance beyond the final score, shedding light on moments of missed opportunities and how they correlate with XG figures. These visual tools offer deeper insights into individual player contributions and overall team strategy.
Trend Lines and Performance Insights
Trend lines show performance over a series of matches, indicating whether a team is improving or struggling in areas such as expected goals created and conceded. An analysis of Liverpool's trend line demonstrated their attacking superiority during the previous season, yet underscored the criticisms regarding their finishing. For teams like Newcastle, the data highlighted fluctuations in performance correlating with player injuries and recovery. This analysis serves to unpack complex statistics, demonstrating how teams can benefit from understanding these trends to strategize for future matches.
The Anfield Wrap explain the theory behind the statistics we use in football, looking at trendlines, race maps and the value behind xG. Neil Atkinson is joined by Josh Williams...