AVSL 2023 Player Statistics: Women
15 matches used here. Data last updated: 14-Sep-2023
Points scored during a team's power play are worth 2 points.
Minimum 15 serves included here.
Key
| Statistic | Explanation |
|---|---|
| Jump serve % | Percentage of serves by this player that were jump serves |
| Serve efficiency | (number of aces + number of serves rated positive - number of errors - number of serves rated negative) / (number of serves) |
| Point win % | Percentage of points won by the serving team when this player was serving |
| Expected point win % | The expected point win percentage based on the server's serve ratings and the dataset-wide win percentage by rating. For example, 'negative' serves might correspond to a dataset-wide point win of 30%, and 'ace' to 100%. If a given server had one 'negative' serve and one ace, their expected point win % would be 65% |
Minimum 15 receptions included here.
Key
| Statistic | Explanation |
|---|---|
| Reception efficiency | (number of receptions rated perfect or positive - number of errors - number of overpasses) / (number of receptions) |
| Perfect/positive % | Percentage of receptions rated good or perfect |
| Sideout % | Percentage of points won by the receiving team when this player received the serve |
| Expected sideout % | The expected sideout percentage based on the receiver's pass ratings and the dataset-wide sideout % by rating. For example, 'perfect' receptions might correspond to a dataset-wide sideout % of 70%, and 'poor' to 40%. If a given receiver had one 'perfect' reception and one 'poor' one, their expected sideout % would be 55% |
Minimum 15 attacks included here.
Key
| Statistic | Explanation |
|---|---|
| Attack efficiency | (number of kills - number of blocks - number of errors) / (number of attacks) |
| Point win % | Percentage of points won by the attacking team when this player attacked (at any time during the point) |
| First attack kill % | Percentage of reception attacks that were kills |
Blockers who were front row for a minimum of 20 opposition attacks included here.
Key
| Statistic | Explanation |
|---|---|
| N opposition attacks | Total number of opposition attacks while this blocker was front row |
| Block kill % | Block kills by this blocker as a percentage of N opposition attacks while this blocker was front row |
| Rallies won % | Percentage of points won by blocking team while this blocker was front row |
| Opp. kill % | Opposition attack kill percentage while this blocker was front row |
| BP% R#+ | Percentage of points won by the blocking team while serving and this blocker was front row, and opposition reception was positive or perfect |
This is not an official Volleyball Australia product. The statistics reported here are generated from scouted match files and might differ from the official statistics.
The data files were provided by Josh Cowan, Hugh Nguyen, Terry A'Hearn, and Edwin Kwek.
For more volleyball analytics see the Science Untangled apps.
Data last updated: 14-Sep-2023
AVSL 2023 Player Statistics: Men
15 matches used here. Data last updated: 14-Sep-2023
Points scored during a team's power play are worth 2 points.
Minimum 15 serves included here.
Key
| Statistic | Explanation |
|---|---|
| Jump serve % | Percentage of serves by this player that were jump serves |
| Serve efficiency | (number of aces + number of serves rated positive - number of errors - number of serves rated negative) / (number of serves) |
| Point win % | Percentage of points won by the serving team when this player was serving |
| Expected point win % | The expected point win percentage based on the server's serve ratings and the dataset-wide win percentage by rating. For example, 'negative' serves might correspond to a dataset-wide point win of 30%, and 'ace' to 100%. If a given server had one 'negative' serve and one ace, their expected point win % would be 65% |
Minimum 15 receptions included here.
Key
| Statistic | Explanation |
|---|---|
| Reception efficiency | (number of receptions rated perfect or positive - number of errors - number of overpasses) / (number of receptions) |
| Perfect/positive % | Percentage of receptions rated good or perfect |
| Sideout % | Percentage of points won by the receiving team when this player received the serve |
| Expected sideout % | The expected sideout percentage based on the receiver's pass ratings and the dataset-wide sideout % by rating. For example, 'perfect' receptions might correspond to a dataset-wide sideout % of 70%, and 'poor' to 40%. If a given receiver had one 'perfect' reception and one 'poor' one, their expected sideout % would be 55% |
Minimum 15 attacks included here.
Key
| Statistic | Explanation |
|---|---|
| Attack efficiency | (number of kills - number of blocks - number of errors) / (number of attacks) |
| Point win % | Percentage of points won by the attacking team when this player attacked (at any time during the point) |
| First attack kill % | Percentage of reception attacks that were kills |
Blockers who were front row for a minimum of 20 opposition attacks included here.
Key
| Statistic | Explanation |
|---|---|
| N opposition attacks | Total number of opposition attacks while this blocker was front row |
| Block kill % | Block kills by this blocker as a percentage of N opposition attacks while this blocker was front row |
| Rallies won % | Percentage of points won by blocking team while this blocker was front row |
| Opp. kill % | Opposition attack kill percentage while this blocker was front row |
| BP% R#+ | Percentage of points won by the blocking team while serving and this blocker was front row, and opposition reception was positive or perfect |
This is not an official Volleyball Australia product. The statistics reported here are generated from scouted match files and might differ from the official statistics.
The data files were provided by Josh Cowan, Hugh Nguyen, Terry A'Hearn, and Edwin Kwek.
For more volleyball analytics see the Science Untangled apps.
Data last updated: 14-Sep-2023