ODIs December 7, 2009

Innings Power Factor: a new measure for ODI innings

Alex Tierno had suggested that I create a new factor for ODI innings, incorporating three features of an ODI innings: runs, scoring rate and contribution to team score

This piece was written in collaboration with Alex Tierno

I have attempted something new for "It Figures" in this article. Almost on a continuous basis, many of the readers have offered suggestions for analysis. Some of these have been answered as a response to the comment. Some require creation and publishing of tables in existing articles. Once in a while I get a suggestion which warrants a separate article. This is the first one created based on this premise. In future when such an idea comes up, I will do a similar publishing.

This is based on a suggestion made by Alex Tierno a few months back. I was tied up with various things and only now could I do justice to the suggestion. Alex, in consultation with me, has also has polished the idea with some tweaking recently.

Alex has suggested that I create a new factor for ODI innings which he called "Destructive index". I have called that the "Innings Power Factor". This is a single factor which incorporates the three major features of an ODI innings: runs, scoring rate and contribution to team score.

I will respond to reader comments in a general manner prior to publishing. However Alex can respond to these in a summary fashion after publishing.

The formula used is

Innings Power Factor (IPF) = Runs scored * Scoring rate * % of Team score.

The more I studied this the more I was impressed with the simplicity and effectiveness of this as a measure of ODI innings. The higher each of these factor is, the more the value of the innings. At the same time, the introduction of the % of Team score moderates the factor as exampled below.

Let us take two examples. a 50 in 20 balls would get 125 points using the first two factors. A 125 in 125 balls would also result in a value of 125 points. However the % of Team score for the first innings is likely to be 15-25% and 40-50% for the second. This takes care of higher valuation of higher scores.

It should be noted that this factor, being a pure batting one, does not take into account team strengths, bowling quality, pitch type, innings status, result et al. If all these factors are introduced it will become another Ratings exercise. So please do not send any comments on the exclusion of these factors. In a way this is similar to the 100s-50s. A 100 is a hundred irrespective of when, where and who it was scored against. I also like this measure since it does not have the 99 to 100 problem I have earlier talked about.

This is an unforgiving measure and requires all three factors to work together to finish with a reasonable value. Cameos tend to lose out. At the end of the article I have done a table which takes into account only the first two values.

I briefly toyed with the idea of having a fourth factor, the Result (1.1/1.0 or 1.0/0.9). I gave up for two reasons. It penalizes Coventry/Tendulkar/Hayden/RASmith/Ponting et al unfairly. They could not have done anything more. Also in the top-100, 85 are wins, so this factor will not have any great impact.

The analysis is done in two parts. In the first part, all the innings are analysed and the IPF calculated, sequenced and the table drawn up. By a perusal of this table I have determined that an IPF of 70 (100 off 60 out of 240) translates into an outstanding performance and one above 40 (80 off 50 out of 250) is a very good performance. Also IPF values above 10 (50 off 50 out of 250) translate into good performances. At the other end, only IPF values of below 2.0 might be termed unsuccessful innings. These summaries are posted into the player data and Player tables are drawn up.

1. Top ODI performances ordered by IPF (Runs * S/R * % TS) : > 50.0

No MtId Year Player Name          IPF  For  Vs I Runs(Balls) S/R  %TS TmScre Res

1.2660 2007 McCullum B.B 192.5 Nzl Bng 2 80*( 28) 285.7 84.2% [ 95] Won 2.1209 1997 Saeed Anwar 152.9 Pak Ind 1 194 (146) 132.9 59.3% [327] Won 3.2873 2009 Coventry C.K 150.0 Zim Bng 1 194*(156) 124.4 62.2% [312] 4.0264 1984 Richards I.V.A 146.0 Win Eng 1 189*(170) 111.2 69.5% [272] Won 5.0216 1983 Kapil Dev N 146.0 Ind Zim 1 175*(138) 126.8 65.8% [266] Won 6.1236 1997 Ijaz Ahmed 146.0 Pak Ind 2 139*( 84) 165.5 63.5% [219] Won 7.1652 2000 Jayasuriya S.T 140.2 Slk Ind 1 189 (161) 117.4 63.2% [299] Won 8.2290 2005 Dhoni M.S 139.5 Ind Slk 2 183*(145) 126.2 60.4% [303] Won 9.0457 1987 Richards I.V.A 131.8 Win Slk 1 181 (125) 144.8 50.3% [360] Won 10.2824 2009 Sehwag V 131.3 Ind Nzl 2 125*( 74) 168.9 62.2% [201] Won 11.1049 1996 Kirsten G 130.2 Saf Uae 1 188*(159) 118.2 58.6% [321] Won 12.1207 1997 Jayasuriya S.T 125.3 Slk Ind 2 151*(120) 125.8 65.9% [229] Won 13.0169 1983 Gower D.I 125.2 Eng Nzl 1 158 (118) 133.9 59.2% [267] Won 14.2082 2004 Gilchrist A.C 117.4 Aus Zim 1 172 (126) 136.5 50.0% [344] Won 15.1523 1999 Tendulkar S.R 113.3 Ind Nzl 1 186*(151) 123.2 49.5% [376] Won 16.2581 2007 Gilchrist A.C 113.2 Aus Slk 1 149 (104) 143.3 53.0% [281] Won 17.1010 1995 Lara B.C 112.4 Win Slk 1 169 (129) 131.0 50.8% [333] Won 18.2420 2006 Boucher M.V 111.8 Saf Zim 1 147*( 68) 216.2 35.2% [418] Won 19.2349 2006 Gibbs H.H 110.2 Saf Aus 2 175 (111) 157.7 40.0% [438] Won 20.2923 2009 Tendulkar S.R 109.5 Ind Aus 2 175 (141) 124.1 50.4% [347]

Readers, myself included, would be surprised at the top entry. However a careful perusal of McCullum's blitzkrieg, about which I had come out with an article recently, justifies the position. A middling score, boosted by an unbelievable scoring rate and an amazingly high % of Team score has propelled this innings to the top. Those who question why McCullum's innings outshines Richards'/Jayasuriya's/Anwar's/Kapil's masterpieces should note that McCullum's innings meets Alex's "destructiveness" characteristic to a T.

Then come the 6 famous innings by Anwar/Coventry/Richards/Jayasuriya/Dhoni/Kapil. The odd innings which splits these six is Izaz Ahmed's Lahore demolition of India.

In the top 37 100+ innings, Richards and Jayasuriya have four innings each, Tendulkar has three and Gilchrist and Lara have two each.

Out of the 446 70+ innings, 238 (53.4%) are in the first innings.

To view the complete IPF list, please click here.

Now let us see the player tables.

2. IPF Summary by Batsmen: Ordered by average IPF value

SNo.Batsman             Cty Inns  Runs <-Innings Power Factor->
> 10 75+ 50+ 10+   Avge

1.Zaheer Abbas Pak 60 2572 20 0 5 15 13.29 2.Richards I.V.A Win 167 6721 58 5 5 48 13.10 3.Tendulkar S.R Ind 425 17178 138 7 20 111 12.53 4.Gayle C.H Win 200 7430 55 5 11 39 11.89 5.Trescothick M.E Eng 122 4335 34 1 5 28 10.52 6.Gilchrist A.C Aus 279 9619 72 5 9 58 10.42 7.Smith G.C Saf 147 5613 49 2 4 43 10.17 8.Lara B.C Win 289 10406 80 6 6 68 10.00 9.Pietersen K.P Eng 85 3179 28 0 1 27 9.93 10.Hayden M.L Aus 155 6132 41 2 1 38 9.90

Two 80s greats, Zaheer Abbas and Richards lead this table with averages exceeding 13.00. Richards has achieved this in over 150 innings. However note the high average of Tendulkar, 12.53 achieved in 425 innings. Then come a string of modern ODI stalwarts.

To view the complete file, please click here.

3. IPF Summary: Ordered by number of above average IPF values ( > 10)

SNo.Batsman             Cty Inns  Runs  
> 10(!!)  75+ 50+ 10+
No   %

1.Tendulkar S.R Ind 425 17178 138-32.5 7 20 111 2.Jayasuriya S.T Slk 429 13377 99-23.1 8 14 77 3.Ponting R.T Aus 321 12310 90-28.0 1 9 80 4.Inzamam-ul-Haq Pak 350 11739 86-24.6 0 7 79 5.Ganguly S.C Ind 300 11363 83-27.7 3 7 73 6.Lara B.C Win 289 10406 80-27.7 6 6 68 7.Kallis J.H Saf 281 10410 78-27.8 0 5 73 8.Dravid R Ind 313 10765 76-24.3 0 3 73 9.Gilchrist A.C Aus 279 9619 72-25.8 5 9 58 10.de Silva P.A Slk 296 9284 71-24.0 0 5 66

Tendulkar has 138 innings which meet the 10 points cut-off, 7 of these are the higher level performances exceeding 70 points. Jayasuriya follows with 99 performances, 8 at the top level and then follows Ponting with 90. Inzamam-ul-haq, Ganguly and Lara follow next. The presence of that Sri Lankan great, de Silva, in no.10 position is heart-warming. Two days during early-1996 are justification for this place.

To view the complete file, please click here.

4. IPF Summary: Ordered by % of differential (success-failure) performances

(IPF values < 2.0) - (IPF values > 10.0)

SNo.Batsman Cty Inns Runs <-Innings Power Factor--> > 10(!!) < 2 (??) Diff No % No % %

1.Zaheer Abbas Pak 60 2572 20-33.3 23-38.3 5.00 2.Richards I.V.A Win 167 6721 58-34.7 69-41.3 6.59 3.Hussey M.E.K Aus 102 3623 29-28.4 38-37.3 8.82 4.Pietersen K.P Eng 85 3179 28-32.9 37-43.5 10.59 5.Smith G.C Saf 147 5613 49-33.3 66-44.9 11.56 6.Greenidge C.G Win 127 5134 39-30.7 55-43.3 12.60 7.Tendulkar S.R Ind 425 17178 138-32.5 192-45.2 12.71 8.Hayden M.L Aus 155 6132 41-26.5 63-40.6 14.19 9.Ponting R.T Aus 321 12310 90-28.0 137-42.7 14.64 10.Jones D.M Aus 161 6068 45-28.0 70-43.5 15.53

Since the number of matches varies considerably, I have also introduced a % value, which is the IPFs / ODI Inns. Richards leads in this measure with 34.7%, followed by Pietersen with 34.1%, Smith with 34.0%, Zaheer Abbas with 32.5% and Tendulkar with a high 32.5% despite playing 425 innings. This means that these great players produced a very good batting performance once in three innings. That is really something. Now the chronicle of failures. Mike Hussey has failed to deliver in only 38.2% of the innings, Zaheer Abbas 38.3% and Michael Bevan, 39.8%. It can be seen that most of these batsmen play in the middle order.

Now comes a composite value which is the % failure - % success. The lower this value is the more effective the batsman is. The above table has been ordered in the increasing order of this difference %.

Zaheer Abbas is the top batsman with a differential % value of just 5%. The great Richards follows next with 6.59% and then two modern greats, Pietersen and Hussey, with differential % below 10. Two olden day greats, Greenidge and Jones, split the four modern giants, Smith, Tendulkar, Hayden and Ponting.

The more I see the table the more I feel that this is the single table which encompasses the ODI greats in full.

To view the complete file, please click here.

5. Top ODI performances ordered by IPF-2 (Runs * S/R) : > 125.0

No MtId Year Player Name         IPF-1 For Vs  I Runs(Balls) S/R  Res

1.2420 2006 Boucher M.V 317.8 Saf Zim 1 147* ( 68) 216.2 Won 2.1090 1996 Jayasuriya S.T 276.2 Slk Pak 1 134 ( 65) 206.2 Won 3.2349 2006 Gibbs H.H 275.9 Saf Aus 2 175 (111) 157.7 Won 4.0457 1987 Richards I.V.A 262.1 Win Slk 1 181 (125) 144.8 Won 5.1125 1996 Shahid Afridi 260.1 Pak Slk 1 102 ( 40) 255.0 Won 6.1209 1997 Saeed Anwar 257.8 Pak Ind 1 194 (146) 132.9 Won 7.2349 2006 Ponting R.T 256.2 Aus Saf 1 164 (105) 156.2 8.2272 2005 Vincent L 246.5 Nzl Zim 1 172 (120) 143.3 Won 9.2774 2008 Yuvraj Singh 244.2 Ind Eng 1 138* ( 78) 176.9 Won 10.2873 2009 Coventry C.K 241.3 Zim Bng 1 194* (156) 124.4

Alex also wanted me to do a calculation excluding the third moderating factor, the % of Team score. In other words make this a pure batting individual factor. The above table is an intriguing one. Again, it is a surprise to see Boucher on top. However his is a big century at a scoring rate above 2.00. Similarly Jayasuriya's innings finds its place. It is amazing that a score as low as Afridi's 102 has found its place in the top-10.

Out of the 379 125+ innings, 264 (70%) are in the first innings. This is a marked change to the reasonably equal split for IPF. Possibly the uncertainty of the target for the first innings might have contributed to this disparity.

In the revised table there is only one change. Kapil Dev has secured 221.92 points for his 175* and moves to 21st place. The complete table has not been replaced.

To view the complete file, please click here.

Let me thank Alex for an excellent idea. I request the readers to come out with a similar factor for bowling performances. Wickets/Economy rate seems quite simple but possibly the readers could improve on this. No outside-bowling parameters please.

I will now give serious considerations to some of Seshasayee's excellent suggestions. I have already done the one on Test players' continuous streaks. The tables have been incorporated in my previous article.

The next one is an intriguing one. Sesha wanted me to analyse the next 2/3 years' programmes and do a projection of Test runs and wickets. My initial reaction was to avoid opening this Pandora's box because of the expected reactions of certain types of readers. Then I realized that this would only be an analysis and I should do this without worrying about the reactions of readers. However this is a tough one and the first thing I have to do is to prepare a complete matrix of tours for the next 2/3 years.

Another of Sesha's suggestions is for me to an analysis on player combinations (2-11) who have played in most number of Tests. Again, another tough one but worth doing because of the novelty and insights it would bring.

Anantha Narayanan has written for ESPNcricinfo and CastrolCricket and worked with a number of companies on their cricket performance ratings-related systems

Comments have now been closed for this article

  • testli5504537 on February 25, 2010, 10:47 GMT

    SRT's 147-ball 200* ranks #9 in Table 1 @136, and #4 in Table 5 @272. It lasted full 50 overs, and 200 is the highest score so far. Was it his greatest ever ODI knock? Of the recent vintage, I think 117* and 138 supercede it, considering the importance of occasion & circumstances.

    I think 150-ball 225 is a possibility in ODI's. That will score 337 on Table 5, and somewhere between 150 and 200 on Table 1. [[ Alex I am not sure how many people would be reading the blog published a few months back. I think his 175 is a greater innings considering all points. In fact I am thinking of doing an analysis of 175+ innings. Ananth: ]]

  • testli5504537 on January 6, 2010, 16:16 GMT

    Hi Ananth, I know that things like 'bowling strength' takes this into consideration in some of your analyses, but can we all agree that it is time to ignore all matches that include Zim and Bang in genuine criket stats?? In this analysis, yes the McCullum inns was amazing, but it is really more like an A-list than an true ODI inns. When considering personal stats, players like Murali and Kallis have major Z/B boosts, and really, it does not reflect on true career averages when Murali takes 176 wickets@15 in these games. I wouldn't mind keeping Z/B if these teams simply went through a transition period before becoming true test powers (Similar to Sri Lanka in the 80's), but apart from a couple of years for Zim, these teams have never been remotely competitive. Ho about you just do analyses that exclude Z/B in the future?? [[ Michael The Bangladeshi bowling, the McCullum mauling notwithstanding, is quite good and ranks at par with many an estabilished side. Mortaza, Shahdat, Abdul Razzaq, Md Rafeeque and now Shakib-al hassan. It is their batting which is below-par. Ananth: ]]

  • testli5504537 on December 28, 2009, 19:17 GMT


    The top 2 bowling performances in ODI history have the Bowling Performance Factor calculated and listed below:

    McGrath 7/15 vs Namibia - (3.21/2.14)*(8.4/6)*(7)*(25)/(10)= 36.75 Vaas 8/19 vs Zimbabwe - (2.42/2.37)*(9.4/6)*(8)*(30)/(10)= 38.39

    The huge difference between the ranges compared to the earlier listed performances and their BPFs is interesting, and worth exploring.

    Also, while the avg. per wicket figure at first appeared important, it somehow felt right to leave out from the BPF calculations.

    Havent tested the formula extensively yet, but I feel it would be worth getting others' and your views on.

  • testli5504537 on December 28, 2009, 19:16 GMT

    The top 2 bowling performances in ODI history have the Bowling Performance Factor calculated and listed below:

    McGrath 7/15 vs Namibia - (3.21/2.14)*(8.4/6)*(7)*(25)/(10)= 36.75 Vaas 8/19 vs Zimbabwe - (2.42/2.37)*(9.4/6)*(8)*(30)/(10)= 38.39

    The huge difference between the ranges compared to the earlier listed performances and their BPFs is interesting, and worth exploring.

    Also, while the avg. per wicket figure at first appeared important, it somehow felt right to leave out from the BPF calculations.

    Havent tested the formula extensively yet, but I feel it would be worth getting others' and your views on.

  • testli5504537 on December 28, 2009, 19:13 GMT

    Ananth and Alex - great work with the IPF/DI. For the Bowling Power Factor, the following formula may be looked at:

    Bowling Performance Factor = (Inns Economy/Bowler's Economy)*(Inns SR/Bowler's SR)*(No. of wickets taken)*(Sum of Points of Wicket-Positions taken)/(Total Innings Wickets) where:

    Wicket-Positions 1-4 are worth 5 points each Wicket-Positions 5-7 are worth 3 points each Wicket-Positions 8-11 are worth 1 point each

    For example, taking Anil Kumble's 6/12 against the West Indies in the Hero Cup 1994, Kumble's Bowling Performance Factor would have been

    (3.06/1.94)*(24.1/6.16)*(6)*(12)/(10)= 44.43

    A few other top bowling performances' (in my opinion) factors are calculated and listed:

    Walsh 5/1 vs Sri Lanka - (1.92/0.22)*(17.1/5.4)*(5)*(7)/(10)= 96.72 Bond 6/23 vs Australia - (4.16/2.3)*(33.3/10)*(6)*(24)/(9)= 96.36 Mendis 6/13 vs India - (4.37/1.62)*(23.7/8)*(6)*(20)/(10)= 95.89 Murali 7/30 vs India - (4.62/3)*(29.3/8.57)*(7)*(21)/10= 77.39


  • testli5504537 on December 19, 2009, 13:59 GMT

    Ananth, your point on quality of wickets and destructive impact is well taken. Kapil and co in WC 85 were terrific in opening inroads so the spinners were never under pressure. One thought - could you just look at the top 25 wicket takers from this perspective? If batsman #1 is dismissed the bowler gets 11 points and if batsman #11 is dismissed the bowler gets 1 point. The aggregate then is divided by the number of wickets taken in career and you get the quality index of the bowler. Basic kernel, surely can be developed further. Wait your thoughts.

  • testli5504537 on December 19, 2009, 4:48 GMT

    xolile: Quite correct about the stage of an innings as far as determining "destructiveness" of a spell is concerned.A 5 wicket haul early up would normally be worth more than a similar haul at the end of an innings. Abhi: Quite correct about runs given away during a destructive spell, especially early up. The flip side,however,is say a 5 wicket haul at the death when batsmen are simply throwing their bats around. So, again "xolile"'s argument needs to be factored in.

  • testli5504537 on December 18, 2009, 10:01 GMT

    good analysis but i have one problem with it. the analysis counts the destructiveness of the inning and for the same the formula runs*sr*% of team score seems right

    But the average destructiveness of a batsman over his entire career can't be calculated by his average ipf score

    this is because your ipf is a exponential index (because ipf = runs scored are cubed and divided by balls faced & team score)

    so i strongly disagree with table 2 ordered by average ipf value and suggest this:

    career ipf = career runs*career strike rate*(career runs/total team runs in matches in which player was part of).

    these info must be easily available by statsguru and will be a better index for career destructiveness!

    the reason is that suppose a player with 1 100+ ipf inn & plenty of 7 ipf innings gets rewarded over a player with plenty of 9 ipf innings on basis of a single innings

    this gets corrected in the new formula as suggested & is based on the very parameters you have used 4 ipf

  • testli5504537 on December 15, 2009, 10:20 GMT

    Ananth - on bowler's destructiveness, please see if the following appeals to you, assuming the bowler takes N wickets while defending a total:

    destructiveness = (a_1+...a_N) + overs bowled*(#overs bowled/allowed quota)*(#overs bowled* RRR- runs given)

    where a_i: expected "net" runs saved by taking i-th wicket, RRR: run-rate required by the opposition to win the match. Now, a_i subject to interpretation. For example,

    a_i = 0.3*(Term 1+ Term2 + Term 3), where Term 1 = average*average SR*average %TS Term 2 = runs*SR*%TS Term 3 = Term2 applied to the current partnership.

    Term 1 captures how well he bats on average, Term 2 captures how well he was in this innings, and Term 3 captures how dangerous the partnership was. Now, many variations can be tried. Suppose you are defending 250 in 50 overs. Hence, on average, you can allow at most 25 runs/partnership, 25 runs/batsman, 30 deliveries/wkt. You can use this to calibrate a_i. [[ Alex The one thing I admired about your Batting destructiveness factor was its inherent simpilicity and the abiliity for people like Satvik to say he would create the index for ODI innings while watching the match. That is what people would have done while watching yesterday's run-feast which passed off as a match. The formula you have suggested goes the other way. It is too complicated. We have to come out with an easily understandable and calculable factor. Ananth: ]]

  • testli5504537 on December 14, 2009, 13:44 GMT

    Ref Navin Agarwal's comment. Its a good case study of the hypothesis I had suggested. I had searched on my account and generated one example. India vs Aus WC 1983 first match. Aus 320-9 in 60 overs, Kapil 5-43 in 12. THAT should get somewhere on the bowling index. Ananth, your take please. [[ Pankaj I am afraid this is only an average performance. 1. The Australian scoring rate was 5.33 and Kapil's was 3.5. Certainly better but not the huge difference we see in many other innspells. 2. Kapil took the first wicket, then came back towards the end and picked up wkts 6-9. He came back at 250 or so for 5. So this is a below-avge collection of wickets. Compare this with Kapil's own 4 for 30 against Australia in the 1985 B&H. 3 of the 4 wickets were top wickets and India won. That Australia was also a stronger team. Let me give you the Rating pts for some other project I am doing. The 5 for 43 gets 290 and 4 for 30 gets 350. Just to give you a comparison. Ananth: ]]

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