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September 14, 2013

Great ODI recoveries

Anantha Narayanan
Andy Bichel and Michael Bevan starred in the famous World Cup win against England in 2003  © Getty Images
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ODI wins achieved from the brink of disaster

The year 2012: Still fresh in the memory of many a football follower. Arsenal, yes, we are talking about the "team", played Reading FC. Arsene Wenger showed his disdain for this lesser cup by selecting a team with many second XI players. Reading were all over Arsenal and were 4-0 up in 37 minutes. An Arsenal win was as unlikely as an Indian win over Brazil in football. Theo Walcott reduced the deficit by half time. Then the recovery started. Arsenal made it 4-2, but only a minute of play remained. Two goals were scored in the last minute to restore parity at 4-4. In the extra time, the floodgates opened. Arsenal scored three goals and Reading once, for the match to finish 7-5. Wenger could smile once again.

Move back 55 years to 1957. Charlton FC is 1-5 down with 26 minutes remaining. Half the stadium has left the ground. Then Johnny Summers scored four goals in 17 minutes and John Ryan followed up with two more goals to more than compensate the additional Huddersfield goal. The match ended in a 7-6 win for Charlton, the greatest comeback in recorded football history and the narrowest win in English football history. In a frenetic second half, ten goals were scored.

A sunny Sunday during July 1999. Paul Lawrie started the last round of the British Open, ten strokes behind the leader, Jean Van de Velde. How does one explain this to the non-golf persona? Let me say it is the equivalent of a four-goal deficit at half time or a 300-run deficit at the end of the first innings. Lawrie had a terrific round of 67, Van de Velde had a monstrous meltdown and the regulation 18 holes ended in a tie between Lawrie, Van de Velde and Justin Leonard. It was poetic justice that Lawrie won the claret jug, winning the play-off. He completed the biggest comeback in major championship and PGA Tour history by coming back from ten strokes behind in the final round.

Finally let us use the time machine to roll a few years forward. Sunny Melbourne, January 2002. Australian Open Final between Jennifer Capriati, seeded No. 1 and Martina Hingis, seeded at No. 3. This had been a tournament of upsets, the top four men's seeds not lasting beyond second round. Twenty-four hours later the unfancied 16th seed, Thomas Johansson would win the men's singles. Hingis won the first set comfortably and broke Capriati twice to lead 4-0. Capriati fought back and took the final to a tie-breaker. Hingis led 6-2 and now had four championship points. Capriati saved them all, and went on to win the second set. She was broken by Hingis but then won five straight games to win an extraordinary match. This is the only time a Grand Slam title had been won after saving four match points.

This preamble would have given readers an idea about the theme of this article. I will be looking at ODI matches in which teams were so far behind that some of the betting companies stopped taking bets and half the stadia emptied. Then they slowly clawed their way back and won the match. I look at the top ten recoveries in depth in this article and provide a potted summary of a few other recoveries.

Although this is seemingly an anecdotal article, I will not do my usual selection of matches based on my memory, knowledge aided by visual inspection of the scorecards and some analysis. This is going to be 100% objective and analytical and based on new measures developed for this type of analysis. So readers can rest be assured that no match will be left out.

For reasons briefly explained in this paragraph, I will only look at the second innings and chasing wins. The first innings is difficult to define in view of the absence of a clear target. The target in front of the first batting team is a notional one which varies from period to period and place to place. A 250, which was an excellent score during 1980 at Headingley, would seem wholly insufficient during 2010 in Faisalabad. Not just the arbitrary nature of the target, but it would be difficult to get a correct handle on the situation in the first innings.

Let us say a team is 50 for 4, batting first. Way below the requirement to reach 250, the notional target. Let us say this team reaches 150 and then dismisses the opponents for 120 winning the match. This clearly indicates an awful pitch. So the 50 for 4 is far better than it looks. Taking the other side, let us say a team is 100 for 1. No doubt an excellent situation; they reach 300 and the other team chases down this score in 40 overs for the loss of two only wickets. The 100 for 1, which was seemingly a very good position, was rather inadequate. Hence the first innings is excluded in all matches. At a later date I might find a way to solve all these complex situations.

So I will consider only successful chases. Even there, we have a huge population of 1691 innings. As I have already mentioned, I am going 100% analytical and objective. How do I do this?

At any point in the game, in the second innings, there is a clear target in front of the chasing team. The innings has 11 clear markers in the form of innings beginning and loss of each successive wicket. It is clear that the situation is at a defining point at the fall of a wicket and keeps on improving until the next wicket falls. There are two types of resources available. Wickets and balls. The wicket-related data is available for all the 3400+ matches. However, balls available for the team is available only for the recent 1600 matches. However, I am able to bring that factor into the equation because the limiting resource is the one which is lower.

The wickets resource is the more important one since my calculations prove that at no time in the later part of the innings does the balls remaining become the limiting resource. I am going to compare the target in front of the team and the wicket resource available using two metrics - Target Resources Factor-Wickets (TRF-W) and Target Resources Factor-Balls (TRF-B) - to get a handle of the situation. I compare this with the ratio between the target in front and balls available just to complete the analysis. Just to give an example of the importance of TRF-W. For the TRF-B value to be above 3.00, a scenario like the following needs to be there. The batting team needs to score 36 runs in 12 balls and achieve that win. To locate such instances we need ball-by-ball data, which is some time away.

Wicket resource! Easier said than done. Each wicket carries a different value. The first wicket carries a high value and the last wicket, a fairly low value. To associate correct values for each wicket, I have determined the resource utilised percentage value at the fall of each wicket in every match played, compiled and averaged the same and got a set of values across 3410 matches. The final values seem very sound since there are over 6800 innings to work with. The values are given below. These values are somewhat similar to the D/L table values. However, I suggest that readers should not compare these with the D/L values. The learned academic duo has their methods and I have mine. They are fixing target scores. I am analysing target scores. This table is going to be a very useful one for many future analyses.

Wkt  Res-Utl%  Res-Avl%

1. 17.53% 82.47% 2. 30.87% 69.13% 3. 45.36% 54.64% 4. 57.97% 42.03% 5. 68.84% 31.16% 6. 77.39% 22.61% 7. 84.37% 15.63% 8. 90.16% 9.84% 9. 95.33% 4.67% 10. 100.00% 0.00%

The target in front is determined through a linear function, as also the balls available resource. Since there have been over a hundred rule changes in the 40-plus years of ODI existence, there is no point trying to incorporate these rule changes into either target or balls working. The linear mappings are simple and effective. These three values are determined at the fall of each wicket and a ratio arrived at by dividing the task in front by the resource available. This ratio is 1.00 at the beginning of the innings and becomes 0.00 at the fall of the last wicket. None of the matches that we have considered will reach this stage since we are only looking at chasing wins. A ratio above 1.00 indicates a tough task and a ratio below 1.00 is an easier task. Let me explain this through a few examples.

Target Score-at-FoW Target-% BallsRes% TRF-B  WktRes-%  TRF-W

200 20/2( 60) 90.0 80.0 1.12 69.13 1.30* 200 50/0( 60) 75.0 80.0 0.94* 100.00 0.75 200 100/5(150) 50.0 50.0 1.00 31.16 1.60* 300 40/1( 90) 86.7 70.0 1.23* 82.47 1.05 300 200/6(210) 33.3 30.0 1.11 22.61 1.47* 300 210/8(240) 30.0 20.0 1.50 9.84 3.04*
It is clear that situation 2 is favourable to the batting team and others not so good. The last one is quite a desperate one. If a team won from this situation, it would be quite creditable. In the second and fourth situations, the restricting factor is the balls resource. However it is very likely that the balls resource is likely to be a factor only in low wicket situations. It is almost certain that when more wickets are lost, the wickets lost would prove to be a much more critical factor than balls remaining. The factor values appended with * are the limiting values.

Out of the 3408 matches, there were 1663 wins by wickets and these teams went through well over 10000 wicket-fall situations. Out of these only ten situations were so desperate that the TRF was over 3.0. These are the matches featured here. There were 18 other matches which had situations between 2.5 and 3.0 and their potted scores are also provided. Please note that there might be more than one very tough situations (even TRF values exceeding 3.0) for one match. But the worst one in each match has been selected.

It should be noted that D/L matches are also covered here. In fact, there are two D/L matches in this lot of 29. Of course, there might have been multiple target changes within an innings, but that is not documented anywhere.

Finally let me emphasise that this is a pure scorecard-based analysis. No information beyond the scorecard is needed. Other contextual factors such as relative team strengths, batting and bowling strengths, quality of batsmen at the crease, importance of the match etc are not relevant to this analysis.

Javed Miandad, Lance Klusener, Brendan Taylor, Shivnarine Chanderpaul, Ed Rainsford and Ryan McLaren have won ODI matches with sixes off the last ball. It is possible that the TRF-B in these matches at the beginning of the last ball was as high as 6. But the purpose of this analysis is much more than identifying such instances.

First let us look at a table containing the details of ten matches.

List of matches in which the teams recovered from TRF situations of 2.5 and above
MatchIdFoW ScrBallsDLTgtMaxFB ScrSB ScrBlsFTRF-BTgtFWktFTRF-W
Featured
3065107/8152 240300239/8243/90.4931.1230.5540.0985.632
26203/9 0 267360266/7267/90.0000.0000.2400.0475.133
2499231/9262 285300284/4286/90.1271.4960.1890.0474.057
1028 74/7 0 173258172/9173/90.0000.0000.5720.1563.661
1976135/8226 205300204/8208/80.2471.3840.3410.0983.470
2922187/9269 222300221/9222/90.1031.5260.1580.0473.376
3323140/8193 209300208 ao209/90.3570.9260.3300.0983.355
2182147/8202 218300217 ao218/80.3270.9970.3260.0983.310
241 92/7 0 178300177/8180/90.0000.0000.4830.1563.091
2794 6/5 48 153300152 ao153/80.8401.1440.9610.3123.083
Included
2617114/7143 213300212 ao213/70.5230.8880.4650.1562.974
2632 64/6113 194300193 ao195/80.6231.0750.6700.2262.966
1799 82/6129 246300245/8248/80.5701.1700.6670.2262.951
2455178/9230DL206252223/8205/90.0871.5570.1360.0472.911
2797 44/6118 125300124 ao127/80.6071.0680.6480.2262.869
1537 71/6130 196294195 ao196/80.5581.1430.6380.2262.823
2403134/8228 185300184 ao185/80.2401.1490.2760.0982.802
83 61/6 0 164300163 ao164/80.0000.0000.6280.2262.780
679158/8 0 216300215 ao217/90.0000.0000.2690.0982.729
676152/9 0 174330173/8175/90.0000.0000.1260.0472.707
2375 89/7175DL154264157/9153/70.3371.2520.4220.1562.700
3358133/7222 230300229/9230/80.2601.6220.4220.1562.698
88 80/6 0 204300203/7207/90.0000.0000.6080.2262.691
3161 92/6134 226300225/8228/70.5531.0720.5930.2262.625
31 39/6 0 94360 93 ao 94/60.0000.0000.5850.2262.590
3127169/8238 226300225 ao227/80.2071.2200.2520.0982.563
2634 49/5 65 231300230 ao233/60.7831.0060.7880.3122.528
2265 95/6156 221300220/8221/60.4801.1880.5700.2262.524

There are ten matches which had TRF values exceeding 3.0 and these are featured here. A brief perusal of the scorecards will clearly reveal how tough the task for the chasing team was. Most of these situations have occurred at 7/8/9 wickets down and only one has been at the fall of the fifth wicket. The TRF-B values are also calculated and shown in this table. The table is self-explanatory. The potted scores for the other 18 matches are available in the downloadable document which is in text format and can be viewed by Notepad or similar editor.

The potted scores of the top ten matches, along with brief commentaries, are detailed below.

1. ODI # 3065. Australia vs Sri Lanka.
Played on 3 November 2010 at Melbourne Cricket Ground.
Sri Lanka won by 1 wicket. Mom: Matthews A.D.
Australia: 239 for 8 wkt(s) in 50.0 overs
   MEK Hussey          71*( 91)
   NLTC Perera         8.0  0  46  5
Sri Lanka: 243 for 9 wkt(s) in 44.2 overs
   AD Matthews          77*( 84)
   SL Malinga          56 ( 48)
   XJ Doherty         10.0  1  46  4
The match at the top of the list is of recent vintage and still fresh in everyone's memory. At MCG, Australia posted a very competitive total of 239 and reduced Sri Lanka to 107 for 8. Only 9.84% of resources are available and 55.4% of target runs are yet to be scored. This leads to a TRF of 5.632, the highest in ODI history, for winning teams. Angelo Mathews and Lasith Malinga got together and set up arguably the most exciting stand in all ODI cricket and added 132 runs. Then, with four runs to go, Malinga is run out. Muttiah Muralitharan came and swatted the second ball for four, taking Sri Lanka to the most unlikely win amongst 3400-plus ODI matches.
2. ODI # 26. Pakistan vs West Indies.
Played on 11 June 1975 at Edgbaston, Birmingham.
West Indies won by 1 wicket. Mom: Sarfraz Nawaz.
Pakistan: 266 for 7 wkt(s) in 60.0 overs
   Majid Khan          60 ( 90)
   Mushtaq Mohammad    55 ( 82)
   Wasim Raja          58 ( 87)
West Indies: 267 for 9 wkt(s) in 59.4 overs
   CH Lloyd            53 ( 76)
   DL Murray           61*( 95)
   Sarfraz Nawaz      12.0  1  44  4
The first World Cup in 1975. An important league match. Pakistan post an imposing total of 266. West Indies are devastated by Sarfraz Nawaz and slump to 89 for 5, 166 for 8 and finally, 203 for 9. The key factors are 24.8% of target runs to be scored and 4.67% of resources available, a very high TRF of 5.133. Also, nine wickets down, so no second chance like the first match. Deryck Murray and Andy Roberts put together, arguably, the best last-wicket partnership ever, of 64 runs, and West Indies script an unlikely win. They went on to win that World Cup, the next, and only their disdain of India prevented them from completing a hat-trick of World Cup wins.

This was one of the matches in which even the early situations such as 151 for 7 and 166 for 8 produced TRF values exceeding 2.75. But the worst situation was at the fall of the ninth wicket.

3. ODI # 2499. Kenya vs Ireland.
Played on 2 February 2007 at Ruaraka Sports Club Ground, Nairobi.
Kenya won by 1 wicket (with 6 balls remaining). Mom: Odoyo T.M.
Ireland: 284 for 4 wkt(s) in 50.0 overs
   WTS Porterfield    104*(131)
   KJ O'Brien         142 (123)
Kenya: 286 for 9 wkt(s) in 49.0 overs
   N Odhiambo          66 ( 82)
   TM Odoyo            61*( 36)
   AC Botha            9.0  0  42  4
   WK McCallan        10.0  2  36  4
Minnows they might be but Kenya and Ireland produced a cracker of match. Ireland, helped by two hundreds by William Porterfield and Kevin O'Brien, set Kenya a huge task of 285. Kenya lost wickets steadily and were at 231 for 9. The key numbers were 18.9% and 4.67%. The TRF was 4.057. Then Thomas Odoyo played a magnificent innings of 61 in 36 balls, supported by Hiren Varaiya, who faced ten balls. Kenya won by a wicket with an over to spare. The TRF based on balls was 1.496.
4. ODI # 1028. Australia vs West Indies.
Played on 1 January 1996 at Sydney Cricket Ground.
Australia won by 1 wicket. Mom: Reiffel P.R.
West Indies: 172 for 9 wkt(s) in 43.0 overs
   CL Hooper           93*( 96)
Australia: 173 for 9 wkt(s) in 43.0 overs
   MG Bevan            78*( 88)
   CEL Ambrose         9.0  3  20  3
New Year's day at the SCG. West Indies, tied down by Paul Reiffel and Shane Warne, managed to reach 172 for 9 in the allotted 43 overs. Curtly Ambrose ripped through the Australian top order and they were soon struggling at 74 for 7. The TRF worked out to 3.661, with the constituent values being 57.2% and 15.63%. Michael Bevan then played one of the best finishing innings ever. He added 83 with Reiffel and nursed Warne and Glenn McGrath to take Australia to a win with nothing but a wicket to spare. Australia were 169 for 9 with a ball to go and Bevan smashed a four through long-on. Truly, a memorable finish.
5. ODI # 1976. Australia vs England.
Played on 2 March 2003 at St George's Park, Port Elizabeth.
Australia won by 2 wickets. Mom: Bichel A.J.
England: 204 for 8 wkt(s) in 50.0 overs
   AJ Stewart          46 ( 92)
   AJ Bichel          10.0  0  20  7
Australia: 208 for 8 wkt(s) in 49.4 overs
   MG Bevan            74*(126)
   AR Caddick          9.0  2  35  4
World Cup 2003 played at South Africa. Andy Bichel, producing one of two greatest spells of fast bowling in a World Cup (who can forget Gary Gilmour's 6 for 14 in 1975), limited England to 204 for 8. The Australian batsmen failed to Andy Caddick and Ashley Giles and were floundering at 135 for 8. That man, Bevan, steady at one end, was joined by the bowler of the World Cup: Andy Bichel. The TRF was 3.470 (34.1% and 9.84%). Bevan and Bichel finished off the job on hand themselves, reaching 208 for 8, winning by two wickets. McGrath's debatable batting skills were not needed.
6. ODI # 2922. Bangladesh vs Zimbabwe.
Played on 5 November 2009 at Zohur Ahmed Chowdhury Stadium, Chittagong.
Bangladesh won by 1 wicket. Mom: Naeem Islam.
Zimbabwe: 221 for 9 wkt(s) in 50.0 overs
   BRM Taylor         118*(125)
Bangladesh: 222 for 9 wkt(s) in 49.0 overs
   Naeem Islam         73*( 90)
Again, two unfancied teams. Brendan Taylor, with an excellent hundred, helped Zimbabwe reach a modest 221 for 9. Bangladesh, with some atrocious running between the wickets, were looking down the barrel at 187 for 9. The TRF was 3.376 (15.8% & 4.67%). Naeem Islam was already batting well at 40. He farmed the strike beautifully, allowing Nazmul Hossain to face only four balls and took Bangladesh to a one-wicket win, with an over to spare.
7. ODI # 3323. South Africa vs New Zealand.
Played on 19 January 2013 at Boland Park, Paarl.
New Zealand won by 1 wicket. Mom: Franklin J.E.C.
South Africa: 208 all out in 46.2 overs
   F du Plessis        57 ( 72)
New Zealand: 209 for 9 wkt(s) in 45.4 overs
   JEC Franklin        47*( 61)
   R McLaren           8.4  0  46  4
We finally come to 2013. South Africa are dismissed for 208 through a wonderful bowling performance by Mitchell McClenaghan. But New Zealand could not face Lonwabo Tsotsobe and Ryan McLaren. They were at 140 for 8, which produced the highest TRF of 3.355 (33.0% and 9.84%). The situation at 105 for 7 was only slightly better. James Franklin and Kyle Mills added 47 and paved the way. Still, the ninth wicket fell at 187. Franklin scored all the 22 runs for the last wicket and garnered an excellent one-wicket win.
8. ODI # 2182. England vs West Indies.
Played on 25 September 2004 at The Brit Oval, London.
West Indies won by 2 wickets. Mom: Bradshaw I.D.R.
England: 217 all out in 49.4 overs
   ME Trescothick     104 (124)
West Indies: 218 for 8 wkt(s) in 48.5 overs
   S Chanderpaul       47 ( 66)
   A Flintoff         10.0  0  38  3
England reached an average total of 217, aided by a hundred from Marcus Trescothick. The English bowlers struck regularly and reached 147 for 8. This produced a TRF of 3.310 (32.6% & 9.84%). The unlikely pair of Courtney Browne and Ian Bradshaw got together and scripted an unlikely win for West Indies, adding 71 priceless runs.
9. ODI # 241. Pakistan vs West Indies.
Played on 28 January 1984 at Adelaide Oval.
West Indies won by 1 wicket. Mom: Marshall M.D.
Pakistan: 177 for 8 wkt(s) in 50.0 overs
   Wasim Raja          46 ( 40)
West Indies: 180 for 9 wkt(s) in 49.1 overs
   MD Marshall         56*( 84)
   Wasim Raja         10.0  1  33  3
   Abdul Qadir        10.0  1  34  3
Pakistan and West Indies produced another thriller. Pakistan reached a below-par total of 177. West Indies were up the creek without a paddle at 72 for 7. The TRF was 3.091 (48.3% and 15.63%). Malcolm Marshall donned the unlikely role of a batting saviour and added the remaining 88 runs in partnerships with Eldine Baptiste, Michael Holding and Wayne Daniel.
10. ODI # 2794. Bangladesh vs Sri Lanka.
Played on 16 January 2009 at Shere Bangla National Stadium, Mirpur.
Sri Lanka won by 2 wickets. Mom: Sangakkara K.C.
Bangladesh: 152 all out in 49.4 overs
   Raqibul Hasan       43*(107)
Sri Lanka: 153 for 8 wkt(s) in 48.1 overs
   KC Sangakkara       59 (133)
   M Muralitharan      33*( 16)
   Nazmul Hossain     10.0  3  30  3
The last in this lot of featured matches, producing TRF values above 3.0, was played recently in Bangladesh. Bangladesh reached a poor total of 152. It looked like a cakewalk for Sri Lanka. They had reckoned without Nazmul Hossain and Shakib Al Hasan. The first five batsmen scored 2, 0, 0, 1 and 1. The score was 6 for 5 leading to a TRF of 3.091 (96.1% and 31.16%). Then Kumar Sangakkara steadied the innings with Jehan Mubarak. Both of them got out and the score became 114 for 8. The TRF was quite high even now but not as bad as 6 for 5. Then Murali took over. With an unconventional innings of 33 in 16 balls, he saw Sri Lanka through. This is the only instance of a TRF value exceeding 3.0, with the loss of only five wickets.

I have created a document file with details of all matches in which the TRF values exceeded 2.5. This includes multiple occurrences within the same match. This document also includes the potted scores of the 18 matches which contained TRF values between 2.5 and 3.00. To download/view the document, please CLICK HERE.

While I was working on this article I realised that this analysis has a lot of implications for evaluation of live matches. I hope no broadcaster picks up the idea from here without giving me credit! Let me give a few examples from recent matches.

1. Ireland: 269. England: 48 for 4. The TRF-W was 1.95 (82.22/42.03). England won from this position. But they would not have made it to a list of top 50 matches.
2. Australia: 315. England: 103 for 5. The TRF-W was 2.14 (66.77/31.16). But they did not win.
3. Australia: 315. England: 169 for 8. The TRF-W was 4.72 (46.52/9.84). But they did not win.

So this is only a theoretical exercise at the end of the match if the chasing team did not win. But it indicates the difficulty of the task ahead of the teams and has a lot of relevance during a match. It also puts in perspective what the teams featured here achieved.

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

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ABOUT THE AUTHOR

Anantha Narayanan
Anantha spent the first half of his four-decade working career with corporates like IBM, Shaw Wallace, NCR, Sime Darby and the Spinneys group in IT-related positions. In the second half, he has worked on cricket simulation, ratings, data mining, analysis and writing, amongst other things. He was the creator of the Wisden 100 lists, released in 2001. He has written for ESPNcricinfo and CastrolCricket, and worked extensively with Maruti Motors, Idea Cellular and Castrol on their performance ratings-related systems. He is an armchair connoisseur of most sports. His other passion is tennis, and he thinks Roger Federer is the greatest sportsman to have walked on earth.

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