Budget Draft: ODI Nations

Man, one of the only reason I love doing these drafts is to read @Aislabie 's analysis. Amazing work again
Thank you; there'll be more to come as well as I'm going to do a pick-by-pick VARP analysis over the next couple of days

But wouldn't that make it a weak spin attack?

BTW nice analysis, i enjoyed the drafts
Arguably so, yes; it'd certainly be a pace oriented team. You could maybe go for Ajantha Mendis or Saqlain Mushtaq instead of Shoaib if you wanted a spinner.
 
@Aislabie

Thanks for the team.


While his team is one of the best statistically, factoring in my personal bias to my favourite players, here is what my team would look like.

:eng: :wkb: Jonny Bairstow
:aus: :bat: Matthew Hayden
:ind: :bat: Virat Kohli :c:
:nep: :ar: Paras Khadka
:ned: :ar: Ryan ten Doeschate
:nam: :bat: Craig Williams
:pak: :ar: Shahid Afridi
:ken: :ar: Thomas Odoyo
:saf: :bwl: Dale Steyn
:sco: :bwl: Safyaan Sharif
:wi: :bwl: Joel Garner

What's more surprising for me is that the team does match somewhat to what my team would have looked like. Khadka was a sure pick for me the moment CK picked up Lamichanne. And so was Dale Steyn (as he is one of my favourite bowlers).

Well, I was torn between Mark Waugh, Adam Gilchrist and Hayden for opening position. Going with Haydos, owing to his superios List A record.
As for Bairstow, 110 strike rate, 50+ average in ODI cricket. What else do you need in an opener. And while he may not keep regularly in ODIs, he is not a bad keeper.

Also swapped out Akhtar for Afridi, to get more balance in the side. Went with Safyaan Sharif owing to his great stats in both ODI and List A cricket.
 
:x: One definite criticism that can be levelled at this team is that it's full of accumulators. The entire top four and Shakib are all players who score their runs between the wickets, as opposed to past the boundary. Leaves a lot of responsibility on Garry Sobers.
I think Sanga can definitely act as a hitter if given the licence.
 
:eng: :wkb: Jonny Bairstow
:aus: :bat: Matthew Hayden
I confess I had entirely assumed that both these players were gone already and didn't check them. I'm going to edit these picks in because I like your team a lot
 
@Yash.
1. :eng: :wk: Jonny Bairstow
2. :aus: :bat: Matthew Hayden
3. :ind: :bat: Virat Kohli
4. :nep: :ar: Paras Khadka
5. :ned: :ar: Ryan ten Doeschate
6. :nam: :bat: Craig Williams
7. :pak: :ar: Shahid Afridi
8. :ken: :ar: Thomas Odoyo
9. :saf: :bwl: Dale Steyn
10. :sco: :bwl: Safyaan Sharif
11. :wi: :bwl: Joel Garner

:tick: You started by building your team around Kohli, Tendo and Garner which is an outstanding recipe for success.
:tick: Bairstow and Hayden would be one of the very best opening pairs in the entire draft, and you picked both up as spares at the end.
:x: Apart from Garner and Steyn, the seam attack is a bit of a weakness. But "apart from Garner and Steyn" is a hell of a qualifying statement.
 
VARP Analysis: Important Information

WELL, WHAT IS IT THEN?
VARP (Value Above Replacement Player) is a metric that I devised to assess a player's performance compared to an average replacement player in the same matches. VARP is expressed as a percentage, for example, a player whose performances are 50% better than a replacement player in the same role would have a VARP of +50%. A player whose performances are 50% worse than a replacement player in the same role would be expressed as having a VARP of -50%. For the sake of clarity, I'll be presenting that with :up: and :down: arrows.

VARP is not a foolproof indication of ability. If a player played in an era of slower scoring, then a strike rate of 90 would stand out far more than it would in the modern ODI game. Similarly, if a player has played mostly in games with a lower standard of cricket being played, then their performances will likely result in a more favourable VARP score. This reflects the fact that a replacement player for (for instance) Bermuda could be expected to be much worse than a replacement player for... well pretty much anyone else.

The idea of this statistic is similar to OPS+ and ERA+ in baseball.

HOW IS IT CALCULATED?
The first step to calculating VARP is to calculate each player's performance rating. Regardless of a player's role, their performance rating is calculated in the same way: runs²/(wickets*balls). For a bowler, lower performance rating is better; for a batsman, a higher performance rating is better. The performance rating isn't normalised in any way, so it's not especially valuable on its own. It is, however, useful for comparative purposes.

To calculate a player's VARP, you will also need the combined performance rating of everyone else who took on a comparable role in matches featuring the player. A player's VARP reflects how much better or worse their performance rating is than the performance rating of the aggregated "replacement player". For batsmen, this is calculated as self/replacement; for the replacement player, this is calculated as replacement/self.

As with most things I've created a spreadsheet to do the pain-in-the-arse mathsy bit for me with the following function:

=(((J2*J2)/(I2*K2))/(((M2-J2)*(M2-J2))/((L2-I2)*(N2-K2)))%-100
The above formula is for a batting VARP. Some of brackets are probably not strictly necessary, but better safe than sorry. The below formula is for a bowling VARP:
=1/(((J2*J2)/(I2*K2))/(((M2-J2)*(M2-J2))/((L2-I2)*(N2-K2)))%-100

Role definition is important: it's not possible to statistically define accumulators versus hitters without coding knowledge that I lack, so I'm using batting positions. Therefore, the roles are as follows:
  • Batting (opener) - Opening batsmen; positions one and two.
  • Batting (top order) - Positions three and four.
  • Batting (middle order) - Positions five and six.
  • Batting (lower order) - Positions seven and eight.
  • Bowling (seamer) - For all bowlers defined as "pace" bowlers, even the slow ones.
  • Bowling (spin) - For all bowlers defined as "spin" bowlers.
  • Bowling (varied) - For bowlers who bowl both pace and spin; compared against all bowlers.
My plan is to go through each pick, and analyse the VARP of each player. I will also assign each pick a semi-objective star rating based on how good of a pick I think it is, but I fully respect that anyone may very well disagree with my sentiment.

Oh I'm also going to obnoxiously tag everyone who might be interested:
@ahmedleo414 @Akshay. @Bevab @blockerdave @CerealKiller @El Loco @qpeedore @VC the slogger @Yash.
 
VARP Analysis: Important Information

WELL, WHAT IS IT THEN?
VARP (Value Above Replacement Player) is a metric that I devised to assess a player's performance compared to an average replacement player in the same matches. VARP is expressed as a percentage, for example, a player whose performances are 50% better than a replacement player in the same role would have a VARP of +50%. A player whose performances are 50% worse than a replacement player in the same role would be expressed as having a VARP of -50%. For the sake of clarity, I'll be presenting that with :up: and :down: arrows.

VARP is not a foolproof indication of ability. If a player played in an era of slower scoring, then a strike rate of 90 would stand out far more than it would in the modern ODI game. Similarly, if a player has played mostly in games with a lower standard of cricket being played, then their performances will likely result in a more favourable VARP score. This reflects the fact that a replacement player for (for instance) Bermuda could be expected to be much worse than a replacement player for... well pretty much anyone else.

The idea of this statistic is similar to OPS+ and ERA+ in baseball.

HOW IS IT CALCULATED?
The first step to calculating VARP is to calculate each player's performance rating. Regardless of a player's role, their performance rating is calculated in the same way: runs²/(wickets*balls). For a bowler, lower performance rating is better; for a batsman, a higher performance rating is better. The performance rating isn't normalised in any way, so it's not especially valuable on its own. It is, however, useful for comparative purposes.

To calculate a player's VARP, you will also need the combined performance rating of everyone else who took on a comparable role in matches featuring the player. A player's VARP reflects how much better or worse their performance rating is than the performance rating of the aggregated "replacement player". For batsmen, this is calculated as self/replacement; for the replacement player, this is calculated as replacement/self.

As with most things I've created a spreadsheet to do the pain-in-the-arse mathsy bit for me with the following function:

=(((J2*J2)/(I2*K2))/(((M2-J2)*(M2-J2))/((L2-I2)*(N2-K2)))%-100
The above formula is for a batting VARP. Some of brackets are probably not strictly necessary, but better safe than sorry. The below formula is for a bowling VARP:
=1/(((J2*J2)/(I2*K2))/(((M2-J2)*(M2-J2))/((L2-I2)*(N2-K2)))%-100

Role definition is important: it's not possible to statistically define accumulators versus hitters without coding knowledge that I lack, so I'm using batting positions. Therefore, the roles are as follows:
  • Batting (opener) - Opening batsmen; positions one and two.
  • Batting (top order) - Positions three and four.
  • Batting (middle order) - Positions five and six.
  • Batting (lower order) - Positions seven and eight.
  • Bowling (seamer) - For all bowlers defined as "pace" bowlers, even the slow ones.
  • Bowling (spin) - For all bowlers defined as "spin" bowlers.
  • Bowling (varied) - For bowlers who bowl both pace and spin; compared against all bowlers.
My plan is to go through each pick, and analyse the VARP of each player. I will also assign each pick a semi-objective star rating based on how good of a pick I think it is, but I fully respect that anyone may very well disagree with my sentiment.

Oh I'm also going to obnoxiously tag everyone who might be interested:
@ahmedleo414 @Akshay. @Bevab @blockerdave @CerealKiller @El Loco @qpeedore @VC the slogger @Yash.

This has just reminded me of that Kaggle dataset.

I have a lot of Azure credits, so I'm going to have a play around in machine learning studio. I'm also interviewing a few Machine Learning interns for my company - maybe I'll set this as a 2nd interview task: tell me who's the best?
 
This has just reminded me of that Kaggle dataset.

I have a lot of Azure credits, so I'm going to have a play around in machine learning studio. I'm also interviewing a few Machine Learning interns for my company - maybe I'll set this as a 2nd interview task: tell me who's the best?
I'd be really interested in what someone with actual technical knowledge would come up with from such a task! Like I know I'm pretty good with spreadsheets, but I suspect that's no match for actual machine learning systems
 
This has just reminded me of that Kaggle dataset.

I have a lot of Azure credits, so I'm going to have a play around in machine learning studio. I'm also interviewing a few Machine Learning interns for my company - maybe I'll set this as a 2nd interview task: tell me who's the best?

If you can get this working, that would be incredible...
 
VARP Analysis: Shakib Al Hasan

@CerealKiller
6. :ban: :ar: Shakib Al Hasan

Cost: :slvo: 2
Batting VARP (middle order): :up: 18.81%
Bowling VARP (spin): :up: 16.58%

Pick Rating: ★★


Shakib Hasan is one of the very best two-point players available, and is unusual in being a top-quality option with both bat and ball. On those grounds alone, he's a hard pick to argue with. That said, his VARP numbers are not uniquely good like you might want for a first pick - but that alone doesn't make him even nearly a bad choice.
 
VARP Analysis: Viv Richards

@Aislabie
3. :wi: :ar: Viv Richards

Cost: :goldo: 3
Batting VARP (top order): :up: 157.50%
Bowling VARP (spin): :down: 1.57%

Pick Rating: ★★


It probably seems a bit rich to straight away five-star my own pick, but it would have been the same whoever had picked Sir Viv. Among three-point players with his sample size, a VARP of over 150% is something I haven't found anyone else to have. That said, selecting him as a stock bowler with a negative VARP is perhaps not ideal.
 
VARP Analysis: Tatenda Taibu

@qpeedore
7. :zim: :wk: Tatenda Taibu

Cost: :slvo: 2
Batting VARP (lower order): :down: 4.28%

Pick Rating:


I personally didn't rate this pick at all when it happened; Taibu quite obviously takes on the firefighter role which is the one least measurable by statistics. But even then, Taibu's stats aren't great. Taibu is a bit of a weird case study though - in that he could never bat higher than seven in teams like this, but in his weak Zimbabwe team he'd bat at four. He certainly has qualities that can't be measured by his stats (keeping, leadership), but he was a weird first pick.
 
My hypothetical team for @Yash. is wildly different from the one @Aislabie came up with.

:ban::bat:Tamim Iqbal:slvo:

Bangladesh's greatest batsman is one of the best players one could have picked in the silver bracket and he was unfortunate to not get picked earlier. His relatively low strike-rate can be explained by his team playing on predominantly bowler-friendly, old-school ODIs where his role is to simply bat through and make a big contribution. While he is not in the same class as that of a certain Indian opener for becoming increasingly dangerous the longer he stays at the crease, his playing style means that Kohli can look forward to having a poor man's Rohit to partner him.

:afg::wk:Mohammad Shahzad:slvo:

You've got a slow starter in Tamim and a player who prefers to rotate strike rather than go for boundaries until he is settled. The best player to complement this duo will be Shahzad whose ODI numbers do not reflect his true talent due to Afghanistan requiring him to bat more consistently. Free from such burdens in this lineup though, Shahzad will do his best impression of a 2015 McCullum and approach ODIs like he does in T20s and T10s to give more breathing room for the rest of the top order.

:aus::ar:Andrew Symonds:goldo:

Time for the big guns. First up is Symonds who was the best middle order batsman in the 2000s and for a period the best ODI cricketer Australia had. Imagine the carnage he could cause in a modern ODI where he has complete license to go big. His bowling is more than adequate should he be required too.

:pak::ar:Imran Khan:goldo::c:

The closest someone can come to Flintoff's record is Pakistan's greatest all-rounder who shall also be the captain of this team. Expect to see him frequently get promoted ahead of Symonds if the team needs a more steady presence or even up to three should Shahzad lose his wicket almost immediately and Kohli needs to be protected from an early dismissal. Even down at six, in a more batting friendly era he has the ability to score quickly with his ability to hit sixes. While he wasn't as good as in tests, his bowling is still world-class and is only bettered by Hadlee in the quartet of all-rounders.

:nam::ar:Gerrie Snyman:bro:

Judging Snyman from the five games he played in the 2003 World Cup as a fresh twenty-one year old would do one of the greatest associate talents a huge disservice. His talents are far better shown by his List A record as every single game of his after 2003 could not merit ODI status due to his nation's status. Starting out as an opening pacer who could bat a bit, Snyman blossomed into one of the most devastating middle-order all-rounders in associate cricket who could also bowl decent seam and occasionally off-breaks too.

:usa::bwl:Rusty Theron:bro:

@qpeedore dropped his name in one of his posts if I'm correct and I did expect him to get snapped up after that. While his record for the USA could be better the current version of him is nowhere near close to the bowler who got an IPL contract and played for South Africa. That version had retired in 2015 after persistent injuries and if you had the opportunity to pick a Proteas pacer with a good record for just one point, you would jump at it.

:saf::bwl:Imran Tahir:goldo:

Tahir is arguably the most outstanding spinner in white ball cricket over this decade. He has the consistency and longevity besides games versus quality opposition that his competitors don't have and in a trade where your effectiveness drops once your variations are 'figured out', his excellence for so long is something to applaud and all of this is despite him having a late start to his South African career. To make this inclusion even more effective, Shahzad is already well used to keeping to another wrist-spinner who bowls extremely quickly and loves his googlies and should have no problem adapting to Tahir.


This gives a playing XI of

  1. :ban::bat:Tamim Iqbal:slvo:
  2. :afg::wk:Mohammad Shahzad:slvo:
  3. :ind::bat: Virat Kohli:goldo:
  4. :ned::ar: Ryan ten Doeschate:slvo:
  5. :aus::ar:Andrew Symonds:goldo:
  6. :pak::ar:Imran Khan:goldo::c:
  7. :nam::ar:Gerrie Snyman:bro:
  8. :ken::ar: Thomas Odoyo:slvo:
  9. :usa::bwl:Rusty Theron:bro:
  10. :wi::bwl:Joel Garner:goldo:
  11. :saf::bwl:Imran Tahir:goldo:


So how does it compare with the other team? The opening is a definite downgrade even if this duo would work well together. In exchange for that however, Kohli wouldn't have to suffer PTSD with a relatively weak middle-order yet again and you get an extra bowling option while gaining a definite upgrade in the spin department. All of the five all-rounders offer tremendous depth in both batting and bowling and good luck trying to score runs from Imran's reverse-swinging and Garner's pinpoint yorkers at the death. Tendo is in his favoured position and role while you have three dangerously explosive players to tee off from the platform that Iqbal and Kohli will build. The only other flaw I can point out is Shahzad's inexperience with keeping to real quality pace as he has kept to only one truly fiery pacer before.
 

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