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Fielding Statistics: A New Approach
- Thread starter viriya
- Start date
viriya
International Captain
Impact is good.
viriya
International Captain
Attempting to take what you're saying more seriously, the statistics that I display like drop rate % has no impact factor - it's just the chance of you dropping a catch given an opportunity. The rating itself is not just a measure of a fielder ability, but also of his impact. Is that more clear?
Athlai
Not Terrible
Impact is good *****.
viriya
International Captain
It factors in the impact the fielder had in the game. Why do you need to prove something? You realize a ratings system consists of certain subjective criteria right? If you are bent on no impact measure just focus on the drop % and be happy. Even if I had 0 weight for impact the rating is still based on the weights I give to different factors, so I don't know what you think I'm trying to prove.
Daemon
Request Your Custom Title Now!
I mentioned it in the other thread as well but why reward a player more for doing literally nothing differently?
If you make the exact same diving catch to dismiss two different players, you've done absolutely nothing differently in both situations. It just so happened that one was a better player. Why does one make you a better fielder than the other?
If you make the exact same diving catch to dismiss two different players, you've done absolutely nothing differently in both situations. It just so happened that one was a better player. Why does one make you a better fielder than the other?
viriya
International Captain
It makes sense to me to credit a fielder with a 25% higher rating for a great catch to get rid of Kane compared to Mills. I think impact (even if it's something a fielder can't control) is what makes an event memorable and important, and that's my way of taking account of that. Based on what I've seen in this thread and the other, I'd say a majority disagrees with me but not everyone - some see the point at least. I'm not trying to make people happy here.
viriya
International Captain
For the 1000th time, it makes that catch more important. I don't just measure ability - it's impossible to do that anyway.
cnerd123
likes this
Ok what's the point of it then?
RossTaylorsBox
Cricket Web: All-Time Legend
Thought I'd try and do a rather crude analysis of catching in tests only, based on the numbers on the website. I make the following assumptions about the data:
- all the parsed data is accounted for and is the ground truth (probably not the case but the best we have)
- the drop rate percentage relates to the number of simple chances dropped (according to viriya, tough drops are ignored)
I only include fielders who have had 15 or more catching chances and wicketkeepers who have had 50 or more catching chances. It should be noted that Brendon McCullum and ABDV aren't included in my analysis because I cannot separate the catches and drops for fielding and keeping roles. I'm not sure how difficult it is to do this but keeping and non-keeping roles should definitely be analysed separately. In any case, this leaves 50 fielders and 10 wicketkeepers.
There is another huge caveat: the website only shows the best and worst fielders so a large amount of data is missing and the averages I use are likely to be skewed. Basically, it's a bad sample. On the other hand, (although I haven't seen the data) perhaps a lot of the missing fielders are ones that have a low amount of catching chances. If I can get all that data I can refine the results further.
The analysis focuses on dropping of simple chances only. It could therefore be interpreted as "The Most/Least Dependable Catchers". Clearly for a full analysis the taking of tough chances should be included to get a more accurate idea of catching in general. This could be done if I had individual data for the number of tough chances a fielder gets. It does not take into account batsman ability as I assume it is irrelevant. Some preliminary statistics:
- The total drop rate for all fielders is 19.2% and 7.9% for all wicketkeepers. It seems rather high. This could be due to a number of factors - Cricinfo commentary not reflecting the actual status of drops, parsing issues or missing data for fielders. Take this with a grain of salt.
- Standard deviations for the drop rates of fielders and keepers are 10.7% and 3.5% respectively. So the data is quite varied. Unsurprising given the data is taken from the best and worst fielders.
Lowest drop rates (most dependable catchers):
1. Herschelle Gibbs - 2.6% from 39 chances
2. Jamie How - 5.3% from 19 chances
3. Kane Williamson - 5.6% from 36 chances
4. Harbhajan Singh - 5.9% from 17 chances
5. Andrew Symonds - 6.25% from 16 chances
6. Daniel Vettori - 6.25% from 16 chances
7. Chris Rogers - 6.7% from 15 chances
8. Sourav Ganguly - 6.7% from 15 chances
9. Ashwell Prince - 7.1% from 42 chances
10. Martin Guptill - 8.6% from 35 chances
Highest drop rates (least dependable catchers):
1. Umar Gul - 47.1% from 17 chances
2. Kirk Edwards - 37.5% from 16 chances
3. Peter Siddle - 36.8% from 19 chances
4. Umar Akmal - 36.8% from 19 chances
5. Runako Morton - 34.8% from 23 chances
6. Daniel Flynn - 33.3% from 15 chances
7. Imran Farhat - 33.3% from 33 chances
8. Ishant Sharma - 33.3% from 27 chances
9. Shakib al Hasan - 31.8% from 22 chances
10. Steven Smith - 30% from 30 chances
For keepers:
1. B.J. Watling - 2.1% from 95 chances
2. Prasanna Jayawardene - 4.7% from 150 chances
3. Mark Boucher - 4.9% from 224 chances
4. Brad Haddin - 6.4% from 265 chances
5. Mushfiqur Rahim - 8.75% from 80 chances
6. MS Dhoni - 8.9% from 280 chances
7. Denesh Ramdin - 9.5% from 189 chances
8. Matt Prior - 10.1% from 266 chances
9. Kamran Akmal - 10.5% from 133 chances
10. Adam Gilchrist - 14.3% from 84 chances
Surprising that Steve Smith and Adam Gilchrist both have quite poor drop rates.
Some other differences between the previous analysis:
- Several of the "worst" fielders actually have drop rates better than the average, notably Graeme Smith (11.9%), Michael Clarke (13.9%), VVS Laxman (14.5%), Younis Khan (14.9%) and Darren Bravo (15.8%).
- Conversely, relatively few of the "best" fielders have relatively higher than expected drop rates. Stuart Broad (10%) and Faf du Plessis (20%) are notable exceptions here.
Note that the analysis does not take into account the actual number of catches, unlike viriya's which assigns a certain number of points for all catches. Whether or not this is a valid methodology is up for debate. I can see the benefits of both. For me catching a simple chance is exactly the same as a batsman playing a forward defensive shot - there should be no reward at all for this, but dropping these chances should be a noteworthy event. On the other hand, can it really be said that Rahim is a better gloveman than Dhoni when Dhoni has had more than 3 times the number of chances? I also have defined a cut-off number of chances for fielders so in a way I am also taking into account longevity here.
By the way, McCullum's drop rate is 10.9% from 165 chances and ABDV's is 6.4% from 172 chances.
My personal opinion is that we need a much better quality of data to even be able to assess catches, let alone fielding. Drop rates are quite valuable though and should be included as part of a more formal analysis.
- all the parsed data is accounted for and is the ground truth (probably not the case but the best we have)
- the drop rate percentage relates to the number of simple chances dropped (according to viriya, tough drops are ignored)
I only include fielders who have had 15 or more catching chances and wicketkeepers who have had 50 or more catching chances. It should be noted that Brendon McCullum and ABDV aren't included in my analysis because I cannot separate the catches and drops for fielding and keeping roles. I'm not sure how difficult it is to do this but keeping and non-keeping roles should definitely be analysed separately. In any case, this leaves 50 fielders and 10 wicketkeepers.
There is another huge caveat: the website only shows the best and worst fielders so a large amount of data is missing and the averages I use are likely to be skewed. Basically, it's a bad sample. On the other hand, (although I haven't seen the data) perhaps a lot of the missing fielders are ones that have a low amount of catching chances. If I can get all that data I can refine the results further.
The analysis focuses on dropping of simple chances only. It could therefore be interpreted as "The Most/Least Dependable Catchers". Clearly for a full analysis the taking of tough chances should be included to get a more accurate idea of catching in general. This could be done if I had individual data for the number of tough chances a fielder gets. It does not take into account batsman ability as I assume it is irrelevant. Some preliminary statistics:
- The total drop rate for all fielders is 19.2% and 7.9% for all wicketkeepers. It seems rather high. This could be due to a number of factors - Cricinfo commentary not reflecting the actual status of drops, parsing issues or missing data for fielders. Take this with a grain of salt.
- Standard deviations for the drop rates of fielders and keepers are 10.7% and 3.5% respectively. So the data is quite varied. Unsurprising given the data is taken from the best and worst fielders.
Lowest drop rates (most dependable catchers):
1. Herschelle Gibbs - 2.6% from 39 chances
2. Jamie How - 5.3% from 19 chances
3. Kane Williamson - 5.6% from 36 chances
4. Harbhajan Singh - 5.9% from 17 chances
5. Andrew Symonds - 6.25% from 16 chances
6. Daniel Vettori - 6.25% from 16 chances
7. Chris Rogers - 6.7% from 15 chances
8. Sourav Ganguly - 6.7% from 15 chances
9. Ashwell Prince - 7.1% from 42 chances
10. Martin Guptill - 8.6% from 35 chances
Highest drop rates (least dependable catchers):
1. Umar Gul - 47.1% from 17 chances
2. Kirk Edwards - 37.5% from 16 chances
3. Peter Siddle - 36.8% from 19 chances
4. Umar Akmal - 36.8% from 19 chances
5. Runako Morton - 34.8% from 23 chances
6. Daniel Flynn - 33.3% from 15 chances
7. Imran Farhat - 33.3% from 33 chances
8. Ishant Sharma - 33.3% from 27 chances
9. Shakib al Hasan - 31.8% from 22 chances
10. Steven Smith - 30% from 30 chances
For keepers:
1. B.J. Watling - 2.1% from 95 chances
2. Prasanna Jayawardene - 4.7% from 150 chances
3. Mark Boucher - 4.9% from 224 chances
4. Brad Haddin - 6.4% from 265 chances
5. Mushfiqur Rahim - 8.75% from 80 chances
6. MS Dhoni - 8.9% from 280 chances
7. Denesh Ramdin - 9.5% from 189 chances
8. Matt Prior - 10.1% from 266 chances
9. Kamran Akmal - 10.5% from 133 chances
10. Adam Gilchrist - 14.3% from 84 chances
Surprising that Steve Smith and Adam Gilchrist both have quite poor drop rates.
Some other differences between the previous analysis:
- Several of the "worst" fielders actually have drop rates better than the average, notably Graeme Smith (11.9%), Michael Clarke (13.9%), VVS Laxman (14.5%), Younis Khan (14.9%) and Darren Bravo (15.8%).
- Conversely, relatively few of the "best" fielders have relatively higher than expected drop rates. Stuart Broad (10%) and Faf du Plessis (20%) are notable exceptions here.
Note that the analysis does not take into account the actual number of catches, unlike viriya's which assigns a certain number of points for all catches. Whether or not this is a valid methodology is up for debate. I can see the benefits of both. For me catching a simple chance is exactly the same as a batsman playing a forward defensive shot - there should be no reward at all for this, but dropping these chances should be a noteworthy event. On the other hand, can it really be said that Rahim is a better gloveman than Dhoni when Dhoni has had more than 3 times the number of chances? I also have defined a cut-off number of chances for fielders so in a way I am also taking into account longevity here.
By the way, McCullum's drop rate is 10.9% from 165 chances and ABDV's is 6.4% from 172 chances.
My personal opinion is that we need a much better quality of data to even be able to assess catches, let alone fielding. Drop rates are quite valuable though and should be included as part of a more formal analysis.
viriya
International Captain
I'm definitely missing some data - the good thing is with time it will only get better. Another issue is there will be cases of misattribution when more than one fielder's name is in the text - this is a much tougher issue to resolve without more complicated natural language processing methods (still doable).
Keeping track of tough chances a fielder faces sounds like a good idea - maybe for a separate (great catches)/(tough chances) stat.
Nice overview of the data there.
viriya
International Captain
This should be the result of other factors like great catches, direct hits, misfields, missed stumpings etc.
Daemon
Request Your Custom Title Now!
From the OP I gathered that you were trying to measure the quality of a fielder.
viriya
International Captain
I'm trying to measure fielder value. I think that's a combination of skill, results and impact. tbh, if you disagree with my ratings, just focus on the non-subjective measures and stay happy. Ratings systems are not gonna please everyone anyway. That's not the point of the exercise, it's about getting the actual previously non-existent data.
Last edited:
RossTaylorsBox
Cricket Web: All-Time Legend
Yeah this data will greatly improve the analysis of catching. There's a lot you can do with it depending on the methodology you use.
viriya
International Captain
Only spot checks.. not practical for me to review 8 years worth of Test and ODI data (300MB of text).
I'll check the Steve Smith drops to see if there are any misattributions/issues. Any cases where the data seems off that you can point out will only make things better.. Rerunning everything only takes a couple hours so fixes can be implemented quickly.