It is a well-established fact that Test matches cannot be won alone. You need contribution from batsmen, bowlers and fielders alike. Hence, calling a batsman a match-winner in Tests might be a little pretentious.

But if you explore the statistics of certain batsmen, you would find that their team has rested on their shoulders throughout their career. They definitely did not win their teams Test matches on their own, but they did contribute a lot more than anyone else in Test wins for their teams.

- The percentage of Man of the Match awards in the total matches played
- The percentage of Man of the Series awards in the total series played
- The difference between the average of the batsman in wins and the average of his team in wins
- The percentage of centuries out of the total centuries that resulted in wins
- The percentage of centuries scored in the total number of wins for his team
- The number of times the batsman top scored for his team in wins as a percentage of total matches won
- The number of times the batsman scored more than 40% of the team runs in wins as a percentage of the total wins
- The amount of impact a batsman had in wins

Note that the younger pool of batsmen such as Virat Kohli, Steve Smith and Angelo Mathews fail to make the cut since their sample size is comparatively too low.

**Man of the Match awards**

This is one of the easiest and most straightforward ways of estimating a batsman’s match-winning ability. The more Man of the Match awards you have, the greater is the match-winning ability of a batsman.

No prizes for guessing who has the highest number of Man of the Match awards in Tests among the current crop of batsmen. Kumar Sangakkara leads the way with 16 awards, with the second in the list – Chris Gayle and Younis Khan – having won only half the number of awards as Sanga.

Since the number of matches played by each player differs, let’s look at the number of Man of the Match awards won as the percentage of the total number of matches played. Again, Sanga tops the chart having won the Man of the Match award in 12.3% of the games. Paksitan’s Younis Khan is stalking Sanga, having won an award in 8.16% of the games.

Player | Mat | Awards | Percentage |
---|---|---|---|

AB de Villiers (SA) | 98 | 5 | 5.10 |

AN Cook (Eng) | 114 | 5 | 4.39 |

BB McCullum (NZ) | 94 | 5 | 5.32 |

CH Gayle (WI) | 103 | 8 | 7.77 |

HM Amla (SA) | 82 | 6 | 7.32 |

KC Sangakkara (SL) | 130 | 16 | 12.31 |

MJ Clarke (Aus) | 109 | 7 | 6.42 |

Younis Khan (Pak) | 98 | 8 | 8.16 |

**Man of the Series awards**

Just like the Man of the Match awards, the number of Man of the Series awards too functions as a benchmark to evaluate the match-winning ability of a batsman. Winning the Man of the Series award means the batsman has put up a string of match-winning performances throughout a series.

Australian Test skipper Michael Clarke tops the table with 5 Man of the Series awards, with AB de Villiers, Kumar Sangakkara and Younis Khan clinging onto the second spot with four awards each. But by the percentages, Sangakkara has fared the worst among Cook, Amla, Clarke, De Villiers and Younis Khan, having won a Man of the Series award only in 7.4% of the series.

Clarke has done prominently well, winning an award in 13.5% of the series. De Villiers is at the second spot with a Man of the Series award in 11.11% of the series.

Player | Series | Awards | MOS % |
---|---|---|---|

AB de Villiers (SA) | 36 | 4 | 11.11 |

AN Cook (Eng) | 34 | 3 | 8.82 |

HM Amla (SA) | 33 | 3 | 9.09 |

KC Sangakkara (SL) | 54 | 4 | 7.41 |

MJ Clarke (Aus) | 37 | 5 | 13.51 |

Younis Khan (Pak) | 42 | 4 | 9.52 |

**Difference between player’s average and team’s average in wins**

The difference between the average of a batsman in wins and the average of his team in wins would indicate how much better a batsman has done than his team mates in wins. Younis Khan averages 75.4 in wins, which is 32.3 more than that of his team. Meanwhile the southpaw from Sri Lanka has an average of 74.58 in victories, 26.65 more than that of his team mates.

Players | Batsman’s average in wins | Team’s average in wins | Difference |
---|---|---|---|

Younis Khan (Pak) | 75.4 | 43.1 | 32.3 |

KC Sangakkara (SL) | 74.58 | 47.93 | 26.65 |

AB de Villiers (SA) | 65.93 | 46.82 | 19.11 |

HM Amla (SA) | 62.62 | 46.53 | 16.09 |

AN Cook (Eng) | 60.54 | 45.22 | 15.32 |

IR Bell (Eng) | 57.77 | 45.71 | 12.06 |

MJ Clarke (Aus) | 56.27 | 45.06 | 11.21 |

DA Warner (Aus) | 55.02 | 44.84 | 10.18 |

BB McCullum (NZ) | 48.43 | 40.32 | 8.11 |

**Top scores in victories**

Ending up as the highest run getter in a Test match victory invariably makes a batsman a genuine match-winner. So if we could extract the number of times a batsman has top scored for his team in victories, it would give us an idea about the match-winning ability of a batsman. Here, the top score is calculated as an aggregate of the runs scored in both innings of a Test match.

The stylish Lankan left hander once again rocks the zenith, having been the top scorer in 16 matches. De Villiers follows him with 13 top scores in 50 Test wins.

If you go by the percentages, once again Sanga comes out looking good, with top scores in 30.769% of the wins. Pakistan’s ace batsman trounces De Villiers here, having ended up with top scores in 27.02% of the games. Younis has been the top scorer in 10 of 37 victories whereas AB de Villiers has managed to do the same in 13 of 50 victories.

Players | No. of wins | Top scores | Percentage |
---|---|---|---|

KC Sangakkara (SL) | 52 | 16 | 30.77 |

Younis Khan (Pak) | 37 | 10 | 27.03 |

AB de Villiers (SA) | 50 | 13 | 26 |

DA Warner (Aus) | 20 | 5 | 25 |

IR Bell (Eng) | 45 | 9 | 20 |

AN Cook (Eng) | 47 | 9 | 19.15 |

MJ Clarke (Aus) | 61 | 10 | 16.39 |

BB McCullum (NZ) | 28 | 4 | 14.29 |

HM Amla (SA) | 44 | 5 | 11.36 |

**Contribution to team’s total in wins**

The flip side of the above methodology is that being the top scorer does not necessarily mean that the concerned batsman has contributed more towards victory. To know how much a batsman has contributed towards his team’s victory, let’s look at the number of times a batsman has scored more than 40% of the team runs in victories.

(The runs scored through extras have been ignored here).

Player | No. of times contributed more than 40% of runs | No. of wins | Percentage |
---|---|---|---|

KC Sangakkara (SL) | 7 | 52 | 13.46 |

DA Warner (Aus) | 1 | 20 | 5 |

HM Amla (SA) | 2 | 44 | 4.55 |

Younis Khan (Pak) | 1 | 37 | 2.70 |

IR Bell (Eng) | 1 | 45 | 2.22 |

AN Cook (Eng) | 1 | 47 | 2.13 |

AB de Villiers (SA) | 1 | 50 | 2 |

MJ Clarke (Aus) | 1 | 61 | 1.64 |

The legendary left-hander leads the way once again, having scored more than 40% of the runs in 7 wins. No other batsman even comes close to him; Amla is the only other batsman who has done it more than once.

Even by the law of percentages, Sangakkara sits comfortably at the top having scored 40% the runs in 13.5% of the wins.

**Percentage of centuries that resulted in victories**

Calculating the number of centuries that result in victories is one of the easiest ways of standardizing the match-winning ability of a batsman. Going by the numbers, Sangakkara tops the chart with 19 match-winning centuries. But by percentage, De Villiers leads the way with 71.42% of his victories resulting in victories.

Player | 100 | centuries in victories | Percentage |
---|---|---|---|

AB de Villiers (SA) | 21 | 15 | 71.43 |

IR Bell (Eng) | 22 | 15 | 68.18 |

MJ Clarke (Aus) | 28 | 17 | 60.71 |

HM Amla (SA) | 23 | 12 | 52.17 |

AN Cook (Eng) | 27 | 14 | 51.85 |

Younis Khan (Pak) | 29 | 15 | 51.72 |

KC Sangakkara (SL) | 38 | 19 | 50 |

*Minimum 20 centuries

**Percentage of wins in which a batsman scored a century**

Deciphering the number of centuries a batsman has scored in his team’s victories is another parameter that is useful in measuring the batsman’s match-winning capacity. Pakistan’s Younis Khan has scored a century in 40.5% of his team’s victories. David Warner trails him with 40%.

Sangakkara is third in the list, having accomplished it in 36.5% of the games.

Player | Centuries | Matches won during his time | Percentage |
---|---|---|---|

Younis Khan (Pak) | 15 | 37 | 40.54 |

DA Warner (Aus) | 8 | 20 | 40 |

KC Sangakkara (SL) | 19 | 52 | 36.54 |

IR Bell (Eng) | 15 | 45 | 33.33 |

AB de Villiers (SA) | 15 | 50 | 30 |

AN Cook (Eng) | 14 | 47 | 29.79 |

MJ Clarke (Aus) | 17 | 61 | 27.87 |

HM Amla (SA) | 12 | 44 | 27.27 |

BB McCullum (NZ) | 6 | 28 | 21.43 |

**Impact in wins**

This is by far the best way to analyse the match-winning ability of a batsman. As mentioned above, a great batsman is not necessarily a great match-winner. A team should depend on a batsman to a great extent for him to be termed a genuine match-winner. So how do you find out how much a team depends on a batsman?

If a batsman has a very high average in wins, that means he has contributed a lot to his team’s wins. But there are batsmen who have had high averages in defeats too. What this signifies is that, despite the gargantuan numbers, their innings didn’t have much impact in the outcome of the game.

So the difference between average in wins and average in defeats would give you the impact a batsman has on his team, for a higher average in wins and lower average in defeats would indicate that the team has been reliant on that batsman’s performance.

David Warner of Australia, for an example, averages 55.02 in wins and 43.36 in defeats. This clearly shows that his batting, despite taking a downward path in defeats, didn’t have a major impact in the results of the matches.

But let’s not make it too simple.

Another factor to consider is how the team as a whole has fared. Averaging higher as a batsman when the team averages higher cannot be considered a trait of a match-winner.

So a more efficient way of calculating the impact is by finding the difference between the average of the batsman and the team in wins and defeats separately and finding the difference between the values obtained for both wins and defeats.

Players | Batsman’s avg in wins | Team’s avg in wins | Difference | Batsman’s avg in defeats | Team’s avg in defeats | Difference | Difference between wins and defeats |
---|---|---|---|---|---|---|---|

Younis Khan (Pak) | 75.4 | 43.1 | 32.3 | 35 | 23.64 | 11.36 | 20.94 |

KC Sangakkara (SL) | 74.58 | 47.93 | 26.65 | 35.25 | 24.22 | 11.03 | 15.62 |

AB de Villiers (SA) | 65.93 | 46.82 | 19.11 | 34.77 | 26.05 | 8.72 | 10.39 |

AN Cook (Eng) | 60.54 | 45.22 | 15.32 | 29.14 | 24.16 | 4.98 | 10.34 |

IR Bell (Eng) | 57.77 | 45.71 | 12.06 | 26.33 | 24.32 | 2.01 | 10.05 |

MJ Clarke (Aus) | 56.27 | 45.06 | 11.21 | 31.47 | 26.14 | 5.33 | 5.88 |

BB McCullum (NZ) | 48.43 | 40.32 | 8.11 | 25.96 | 23.69 | 2.27 | 5.84 |

HM Amla (SA) | 62.62 | 46.53 | 16.09 | 35.83 | 25.06 | 10.77 | 5.32 |

DA Warner (Aus) | 55.02 | 44.84 | 10.18 | 43.36 | 24.53 | 18.83 | -8.65 |

From the above chart it is obvious that David Warner has had the least impact in his team’s performance. He averages 43.36 in defeats while his team averages 24.53. This elucidates the fact that his batting doesn’t have a great impact on the outcome of the game.

The Pakistani right-hander has the highest impact; there is a difference of 20.9 in the difference between his average and the team’s in wins and defeats. He averages 32.3 higher than his team in wins and the difference falls down to 11.36 in defeats, which shows that he has a tremendous impact on the outcome of a match.

Thus far, we have looked at eight different factors that govern a batsman’s match-winning ability. An easy way of finding out the winner is to add up everything and find out who has the highest total.

But not all eight factors are equal. For instance, Warner has scored a century in 40% of Australia’s Test wins, but his impact in the results has been very low.

So to find the weighted average match-winning ability of a batsman, let’s first find out the mean of each record and then compute the percentage of deviation.

MOM (%) | 7.002% |
---|---|

MOS (%) | 9.91% |

Difference between avg in wins | 16.78% |

Top scores in victories (%) | 21.11% |

Contribution to winning score (%) | 3.74% |

Centuries resulting in wins (%) | 58.01% |

Wins in which a century was scored (%) | 31.86% |

Impact | 8.41% |

Now, we know the average numbers, so let’s compute the percentage of deviation from the mean value for each batsmen. The percentage of deviation is calculated by dividing a batsman’s record by the mean value and multiplying the answer by 100.

Player | Centuries in wins | Centuries resulting in wins | Diff. in avg in wins | MOM% | MOS% | High contribution | Impact | Top score |
---|---|---|---|---|---|---|---|---|

Younis Khan (Pak) | 127.23 | 89.16 | 192.48 | 116.58 | 96.09 | 72.18 | 248.86 | 128.03 |

KC Sangakkara (SL) | 114.67 | 86.19 | 158.81 | 175.76 | 74.73 | 359.52 | 185.63 | 145.76 |

AB de Villiers (SA) | 94.15 | 123.13 | 113.88 | 72.86 | 112.10 | 53.41 | 123.48 | 123.17 |

AN Cook (Eng) | 93.48 | 89.38 | 95.88 | 62.63 | 89.02 | 56.82 | 122.88 | 90.71 |

MJ Clarke (Aus) | 87.46 | 104.66 | 91.29 | 91.71 | 136.34 | 43.78 | 69.88 | 77.66 |

HM Amla (SA) | 85.59 | 89.94 | 71.87 | 104.49 | 91.72 | 121.4 | 63.22 | 53.83 |

BB McCullum (NZ) | 67.25 | 0 | 66.8 | 75.96 | 0 | 0 | 69.4 | 67.67 |

IR Bell (Eng) | 104.61 | 117.53 | 60.66 | 0 | 0 | 59.35 | 119.43 | 94.74 |

DA Warner (Aus) | 125.54 | 0 | 48.33 | 0 | 0 | 133.54 | -102.8 | 118.43 |

*Note that certain players have a 0 deviation, since the concerned record was too low to be reckoned as a sufficient sample space.

Now that we have the percentage of deviation, let’s assign different weights to different records according to their importance, and find the weighted average of the percentages.

Below is the list of records in the descending order of importance to compute the match-winning ability of a batsman. I have allocated a number starting from 8 in the descending order to each record to find out the weightage each record would have in the final value to be calculated.

Record | Index | Weightage |
---|---|---|

Impact | 8 | 22.2 |

Contribution | 7 | 19.4 |

Top Scores | 6 | 16.67 |

MOS | 5 | 13.89 |

MOM | 4 | 11.11 |

Diff. in avg in wins | 3 | 8.33 |

Centuries resulting in wins | 2 | 5.56 |

Centuries scored in total wins | 1 | 2.78 |

Your priority list might vary, and if you want to find out who the greatest match-winner is according to your list, all you need to do is find the product of each record and its weightage and divide by 100. Then add the result for each record to find the weighted average.

So according to my list, here is what I got.

Player | Centuries in wins | Centuries resulting in wins | Diff. in avg (wins) | MOM% | MOS% | High contribution | Impact | Top Score | Weighted Average |
---|---|---|---|---|---|---|---|---|---|

KC Sangakkara (SL) | 3.18 | 4.78 | 13.23 | 19.53 | 10.38 | 69.90 | 41.25 | 24.28 | 186.54 |

Younis Khan (Pak) | 3.53 | 4.95 | 16.04 | 12.95 | 13.34 | 14.03 | 55.3 | 21.33 | 141.48 |

AB de Villiers (SA) | 2.61 | 6.83 | 9.49 | 8.09 | 15.57 | 10.39 | 27.44 | 20.52 | 100.94 |

AN Cook (Eng) | 2.6 | 4.97 | 7.99 | 6.96 | 12.36 | 11.05 | 27.3 | 15.11 | 88.33 |

HM Amla (SA) | 2.38 | 4.99 | 5.99 | 11.61 | 12.74 | 23.6 | 14.05 | 8.97 | 84.33 |

MJ Clarke (Aus) | 2.43 | 5.81 | 7.61 | 10.19 | 18.93 | 8.51 | 15.53 | 12.94 | 81.95 |

IR Bell (Eng) | 2.91 | 6.52 | 5.06 | 0 | 0 | 11.54 | 26.54 | 15.78 | 68.35 |

BB McCullum (NZ) | 1.87 | 0 | 5.57 | 8.44 | 0 | 0 | 15.42 | 11.27 | 42.57 |

DA Warner (Aus) | 3.49 | 0 | 4.03 | 0 | 0 | 25.96 | -22.84 | 19.73 | 30.37 |

Predictably, Sangakkara establishes his status as the greatest match-winner among current batsmen. But what surprises me is Younis Khan’s underrated match-winning ability. The world waxes eloquent about Sangakkara, Amla and De Villiers but the accomplishments of the Pakistani great are not paid much heed.

In a brittle line up, the Pakistani stalwart’s achievements should be cherished. Carrying a team’s batting single-handedly is an enormous task. Many greats have succumbed to the pressure of doing so.

Sangakkara, despite not getting the amount of accolades he merits, has somehow let the world know of his prowess. But Younis Khan still spends his life in limbo. When will the world recognize the Pakistani’s incredible match-winning ability?

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