sachin-tendulkar – Chasing Tales

A Bayesian view of cricket’s player of series monsters

Imagine this:

Sometimes it rains, sometimes it doesn’t.
You notice that the ground is wet.

Now you ask: “What is the chance that it rained, given that the ground is wet?”

That’s exactly the kind of question Bayes’ Theorem answers.

Think of Bayes’ Theorem as a smart way of changing your mind when new information appears. In life, we start with a belief based on past experience.
Then something new happens. Instead of ignoring it, we usually update what we believe. It’s a part of Probability Theory that helps you combine old information you already have, with new information you have just received.

This is the formula (don’t panic): $P(A∣B) = [P(B∣A)×P(A)] ÷ P(B)$ ¹ ²

It looks mad, doesn’t it? It took me months to be able to remember the Bayes formula, and it took cricket to help me learn it finally. But first, an explanation of what we have above:

In the formula,

A = the thing you care about (Example: It rained). This is your starting belief before you see new evidence. It could be anything, such as, it’s dry season so it won’t rain today.
P(A) is the probability of the starting belief.
B = the evidence you see. (Example: The ground is wet). This is new information.
P(B) is the probability of the new information happening.
the “|” sign in the formula means “given” so P(A|B) will be read as Probability of A given B, meaning that the probability that A is still true given that the new information B is now known (“Now that I see the ground is wet, how likely is it that it rained?”), and P(B|A) is the probability that B is true given that we know that A happened (“If it did rain, how likely is the ground to be wet?”).

Now let’s take some help from cricket WITH MADE UP NUMBERS:

Let’s say India wins 70% of all cricket matches. This is P(A), where A = India wins 70% of all cricket matches, okay?
Now imagine Virat Kohli makes a century in 40% of the matches he plays. This is P(B), where B is Virat’s imaginary (I haven’t checked) century strike rate.
P(A|B) is the probability that India won a match given that Virat hit a century. Let’s keep this at 80%.^{Yes I’m a fan, how did you guess?}
Now the new information is that India has won a match. So given that we now know that India has won a match, what is the probability that Virat hit a century?

So, now,

P(India winning a match for any reason) = 70% = 0.7
P(Virat’s century in a winning or losing cause) = 40% = 0.4
P(India winning given that Virat has hit a century) = 80% = 0.8
So, if we know India has won, what is the probability that Virat hit a century?

P(Virat’s Century given that India has won) = [P(Virat’s century in a winning or losing cause) × P(India winning given that Virat has hit a century)] / P(India winning a match for any reason)

or P(Virat Century|India Win) = [P(Century) × P(India Win| Virat Century)] / P(India Win)

P(Virat century∣India wins)= (0.8×0.4) / 0.70 ≈ 0.457 = 45.7%

I know this is all new and complex for many readers (it took me lots of effort and a Virat-inspired intervention to learn this too), so take your time to read it again if you need to, as many times as might help.

Player of Series Monsters
At this point I want you to know that Cricinfo doesn’t have a list of women cricketers in decreasing order of player of series awards like they do for the men. There’s also a paucity of tabulated data available for women’s cricket generally. So I’m concentrating only on the men. The list of men is clearly documented, as mentioned:

Name	PoS Awards (Tests, ODIs, T20Is)
Virat Kohli (India)	22
Sachin Tendulkar (India)	20
Shakib Al Hasan (Bangladesh)	17
Jaques Kallis (South Africa)	15
David Warner (Australia)	13
Sanath Jayasuriya (Sri Lanka)	13

Of these, I got Perplexity AI to do some data finding and number crunching for me for Virat, Sachin, and Shakib for ODIs.

Bayes USING REAL NUMBERS
When the team won, how often was this player the reason?

Player	Team	Definition of W	Definition of C	P(W) base win%³	P(C) frequency of centuries	P(W \| C) centuries in wins⁴
Kohli	India (ODI)	India win when Kohli in XI	Kohli scores ODI century	0.616	~0.18 (1 per 5.65 inns)	~0.83 (44 of 53 hundreds)
Tendulkar	India (ODI)	India win when Tendulkar in XI	Tendulkar scores ODI century	0.505	~0.11 (1 per 9.22 inns)	~0.67 (33 of 49 hundreds)
Shakib⁵	Bangladesh (ODI)	Bangladesh win (overall ODI record)	Shakib scores ODI century (bat)	~0.36	~0.03 (7 in 234 inns)	~0.77 (7 of first 9 tons)

Player details⁶ ⁷

Here’s the Bayes calculation:

Player	Team	P(W) base win%	P(C)	P(W \| C)	P(C \| W) calculated	Interpretation
Kohli	India (ODI)	0.616	0.18	0.83	0.24 (24%)	~24% of India ODI wins with him include a Kohli hundred
Tendulkar	India (ODI)	0.505	0.11	0.67	0.14 (14%)	~14% of India ODI wins with him include a Tendulkar hundred
Shakib	Bangladesh (ODI)	0.36	0.03	0.77	0.07 (7%)	~7% of all Bangladesh ODI wins include a Shakib hundred

Bayes calculation for Virat, Sachin, and Shakib

What this means

Virat Kohli in a strong India: One in every four ODI wins arrives with a Kohli century inside it. He does not just bat well; he bats well in a machine that is already built to win. His centuries are the accelerant on a fire that’s already burning. When India wins, there’s a strong chance he is the one who decided the margin, the pace, the emotional tone of the chase.
Sachin Tendulkar in a medium India: One in every seven wins contains a Tendulkar century. He played across eras—through the ’90s when Indian cricket was still finding its feet, through the 2000s when it became a force. His centuries had to do more heavy lifting because the team around him was less consistently dominant. The win probability bump he created had to be steeper, had to arrive at moments when India could genuinely lose without him.
Shakib Al Hasan in a historically weaker Bangladesh: One in every fourteen overall Bangladesh ODI wins includes a Shakib century—but here’s the insight: when he does score a hundred, Bangladesh almost never lose that game (6 of 7). On a much thinner winning base, his performances are load‑bearing. He is not the beneficiary of team strength; he is the architect of team possibility.

Shakib is kind of amazing in this that 6 of his 7 centuries have come in wins, and it got me curious about how many 50+ scores have these gents made in wins, but that data is not available in a clean Bayes format.

Kohli and Tendulkar sit on mountains of 50+ scores in ODIs – over a hundred each when you add fifties to centuries.⁸ Where they differ is in what happens after fifty.⁹ Kohli’s conversion rate from 50 to 100 in ODIs is significantly higher than Sachin’s. Once he’s crossed fifty, he tends to keep going, especially in chases. Part of that is temperament – an almost obsessive refusal to give away his wicket once set – but a big part is structural: India in his era often had deeper batting, was better at chasing (or he was better at chasing anyway), and capable partnerships.

Tendulkar’s 50+ scores, by contrast, sit in a very different ecosystem. He played long stretches of his career in teams that were less stable, so his fifties often had to be the innings and the platform at the same time. The conversion to hundreds is lower not because the intent wasn’t there, but because the conditional environment around him – partners, match situations, opposition attacks – made it much harder to keep going at the same rate. Yet even as “just” fifties, those scores were repeatedly the spine that held up India’s innings.

Bangladesh’s baseline ODI win percentage is far lower than India’s. That means:

A Shakib 50 – even without going on to a hundred – does outsized work.
His 50+ scores in tournaments like the 2019 World Cup (where he reeled off one high‑impact innings after another) are not just “good knocks”; they are the narrow ledges on which Bangladesh’s entire chase or defence balances.

And because he does this as an all‑rounder, a fifty for Shakib often comes with 10 overs of spin as well, and Bangladesh tend to look competitive almost exactly on the days Shakib has a good outing.

So much of cricket is about context, and this post reinforced that for me. Virat Kohli doesn’t just score centuries; he does so in a system that consistently wins, amplifying his influence. Sachin Tendulkar carried innings for teams that sometimes struggled, meaning his 50+ scores were often the backbone of a win rather than just the flourish. And Shakib Al Hasan? In a team with fewer wins overall, his big performances don’t ride on a strong machine — they create the machine.

Sources

How does MRF decide whose bat to sponsor?

MRF, originally Madras Rubber Factory, started as a balloon manufacturer and grew into India’s largest tyre company. Over the years, the group diversified into sporting goods, with active involvement in cricket kits, bats, gloves, and a significant marketing footprint in Indian and, to a limited extent, global sporting culture.¹ Over time their bat sponsorship has come to represent a potential enthronement, if not outright coronation of the Indian cricket’s next king. It’s fairly entertaining that MRF, once just a tyre company, now doubles as a premium sporting label—with 350+ retail outlets across India as of 2025.²

I’ve wondered about how MRF chooses, or chooses not to, sponsor someone’s bat, especially since their quick switch to sponsor Shubman Gill’s bat. And yet, the selection is not quite destiny: of the 11 players who have carried an MRF bat, 5 were asked to return it. That’s a 45% failure rate.

Also, two things: 1. The tables are pictures because I’m not mucking about with WordPress tables with this much data. It’s an absurdity. 2. I’ve done my best to check the age figures since it was relevant to this post, but I haven’t checked the cricket stats much.

The Cricketers
Sachin Tendulkar (India)
Brian Lara (WI),
Steve Waugh (Australia),
Gautam Gambhir (India)
Rohit Sharma (India)
Virat Kohli (India),
Sanju Samson (India),
Shikhar Dhawan (India),
AB de Villiers (SA),
Prithvi Shaw (India),
Mignon du Preez (SA),³
Shubman Gill (India)

The Logic
There is clearly a statistical basis for screening the candidates. Each of the cricketers finally offered the bat had a highly successful year 3 years before they got the sponsorship call. The first mottle appears two years before the sponsorship is offered, with Rohit Sharma not quite having a year to remember. One year before the sponsorship, performances from Rohit Sharma and Gautam Gambhir started fading. They were still offered sponsorships, though, so MRF was willing to bet they would pick up, and also be culturally relevant in the future.

Word on the cricketing streets is that MRF spots its talents early in their career, but the average age at the beginning of player sponsorships comes out to be 26.67, with Prithvi Shaw being the earliest pick at 17 (or 18) years old, and Steve Waugh the senior most at 36. Removing these outliers returns an average age of… 26.67 years, and removing anyone who was sponsored before 2010 makes for an average of 25.38 years.

Age of MRF bat sponsorees at the beginning and end of their tenures

It’s obvious that the original three foreign icons (Lara, Waugh, AB) were established greats when they got the MRF deal; the rest, especially Indian batters, were mostly in their 20s. Given that batters usually come into their own around 27-29 (my personal opinion), and can certainly be prodigious well into the 30s, this is consistent with MRF’s search for the next (Indian) batting legend. To be noted, all the averages tallied above fall around or before the age of 27.

These are the statistical inputs I’ve been able to spot for the champaigne:

Insatiability, 850–1,200+ runs/year in Tests or ODIs for at least one of the years before signing.
Consistent 100s in decisive or pressure games (World Cups, series deciders).
ICC event hundreds and being among top run scorers seems to be a trademark.
Youth milestones and early leadership (U19 or domestic tournament MVPs- Kohli, Dhawan, Gill, and Shaw were all U19 heroes)
Multi-format prowess, such as hundreds in all formats by 25.
Longevity (sustained form) or a steep climb in performance

The Magic
MRF’s track record of signing “the next big thing” is so consistent, it borders on magic:

They chose Tendulkar just before he ruled the 90s and 00s.
Bet on Virat as he broke records and changed Indian cricket’s mindset.
Handed Gill the baton right before a record-shattering run in 2025, including 4 consecutive Test hundreds and a string of 20→100 conversions unparalleled among peers, although this was an obvious signing with Virat retiring right before the series, and Gill now the heir apparent to the Indian No. 4 position, and the Test captain).
Timing is critical. MRF’s model aims to find the next star on the rise- locking in ambassadors just as they shift from prodigy to global icon (e.g., Sachin before he became Sachin, Kohli before captaincy explosion).

MRF therefore seems to filter for improvement arcs, multi-format ability, and brand values- not just averages. But cricketing “auras” also matter- hence Kohli, Gill (not just Indian and prodigious, but also temperamentally dignified, in possession of impressive communication skills, the worlds best ODI batter and other top performances in his age cohort, and the Indian Test captain) over otherwise comparable international stars like Dravid (diluted the Indian audience, not a superstar when compared to Sachin), Kallis (not Indian, and not as popular in India as AB), Sangakkara (see Kallis), Laxman (same as Dravid, but also confined to Tests), MS Dhoni (Not an era defining batter), KL Rahul (beautiful, inconsistent), Yashaswi Jaiswal (incredible story but not as established as Shubman, has not yet shown all format ability, although watch out for this in the future), Rishabh Pant (Likely not considered an era defining batter, but is also Spidey, and that doesn’t fit the brand image), Abhishek Sharma (maybe soon?). Ambassadors are chosen not only for statistics, but also for embodying resilience (Tendulkar’s comebacks), toughness (Kohli’s chases), artistic mastery (Lara’s flair), performance (Dhawan’s ICC tournament performances), or next-gen inspiration (Shaw, Samson, Gill). Jaiswal and Pant’s exclusions highlight that charisma alone isn’t enough- they’re watching form across formats, market potential, and personality fit. Not sponsoring MS indicates they’re not too swayed by long term captaincy or intense fandom or even the number of trophies won as skipper- once again, it’s the batting output that matters.

The Business
MRF’s approach to selecting its bat ambassadors is a nuanced blend of data-driven business strategy, brand vision, and razor-sharp market positioning, refined over decades of cricketing association. India is MRF’s largest tyre and sporting market, and cricket is India’s premier sport. MRF therefore focuses on pan-Indian cricket icons as ambassadors to maximise its cultural and commercial return on investment. This also means that non Indians rarely get the MRF sticker.

A selection of players who were not MRF bat ambassadors, and why I think that was so

By not sponsoring too many players simultaneously- and never directly competing with its own ambassadors for limelight- MRF ensures its bat sticker is always exceptional, not generic. The sustained, highly visible association with generational talents strengthens brand recall far beyond the cricket field- from tyre showrooms to street cricket bats. So concerned is MRF with its bat’s legacy, the company has divided its brand into three- the Genius bat for the artists and prodigies (Tendulkar, Kohli, AB, Gill), the Conqueror bat for those known for their grit (Steve Waugh), and the Wizard bat for Brian Lara.

MRF is always looking a generation ahead. As one ambassador (Tendulkar, Kohli) nears twilight, MRF signs the next rising phenom (Gill over Jaiswal, as the latter had not yet ticked every box), displaying continuity and reducing sponsorship risk, while ensuring ongoing cultural presence, with each transition becoming a media/ marketing event in itself. The brand’s investment is offset by massive earned media (“free” advertising) via on-field heroics, social media virality, and generational recall—no other bat sticker is as instantly recognized in world cricket.

Note: This post earlier included Sir Hadlee, but I’ve not been able to find any credible sources for it, so I’ve removed any mention of him, and redone the calculations.

Sources
1. MRF Ltd. – Fortune India
2. MRF Sports
3. @mdpminx22 on Instagram

Measuring greatness in sport

Humans like to measure things, and we like to be right… we insist on both nearly all the time, in fact. We often also like sport. Yet, in the sports I follow, there is no one player who can unequivocally be named the Greatest of All Time (GOAT).

The GOAT debate is always engaging, since it paints more of a picture of the person or persons making their case, rather than the athlete or team they are advocating for.

To my mind, there’s no real way to find one athlete who is better than all others, because no athlete ever has the same journey. Why is this important? Because a girl playing sport will always have more barriers to performance than a boy of the same age, socioeconomic status, and innate talent. Kids starting off playing the same sport will have very different paths by being born in different countries- and I’m not even speaking of the differences between developed and not so developed nations – think of the difference in coaching availability for a young tennis player in Spain to one in, say, New Zealand.

Let’s talk about what makes an athlete good.

i. Win-loss % – The most important standard to determine whether an athlete is good or not. Clearly, athletes who play team sports have a disadvantage, and their personal records will determine whether they have contributed to the team’s cause through their career or not.

ii. Inherent Talent – How fast a person can run, how their body works, how they process the knowledge about sport and apply it through the filter of their own personality are all usually inbuilt, and very individual to any person.

iii. Coachability – Are they open to learning new skills?

So aside from exceptional results in the criteria discussed above, what makes me think of a player as a great, or even a GOAT aspirant? Here’s my (nominal) list:

● Biomechanics – How an athlete moves is imprinted in peoples minds. All athletes in a sport learn the same movements, but how those movements interact with any of their

● Motivation – The best of the best are self motivated, and much more so than the regular person. They constantly wish to improve, and they work to do it.

● Ambition – The more ambitious an athlete is, the higher up they climb.

● Focus – They have their eyes on the prize and nothing can distract them from it.

● Sportspersonship – They’re not nasty. They care enough about their sport that they understand their opponent’s effort. Also, they enjoy their opponents’ successes, at least purely from a love-of-their-sport point of view, even if it encumbers them with additional scoreboard pressure.

● Transcendence – Athletes who transcend their team, their sport, their nationality. They have fans across all lines.

● Provocating other fandoms – If you know, you know. Athletes have reached the pinnacle of their sport infuriate fans of other GOAT contenders in the same sport, especially if they play in overlapping timelines.

● Popularity – They bring new fans and new players to their sport.

● They transform their sport – they change how their sport is played. The way they approach the sport and play it is so transformative, their colleagues change how they play and coaches and think tanks have to alter their baselines and expectations from other players.

While all spoortspersons are (correctly) judged on results, there are some who get better results. My second list are the qualities that propel good athletes to great ones.

Share this:

Share this:

Share this: