Beyond the obvious stats: Advanced metrics to gauge IPL 2024 performance


It is well known that the Indian Premier League (IPL) is a source of excitement due to its explosive batting, thrilling finishes, and new stars. But for serious fans and discerning analysts, the excitement lies in going deeper – discovering the stories behind the figures.

Established metrics like batting average, economy rate in bowling, and strike rate are quite useful but do not take one far beyond a glance into what makes great performers very different from others within this high-speed T20 format.

In this post, we’ll take a look at a range of advanced metrics designed to shed greater light on IPL 2024’s star players. And no, it is certainly not going to be business as usual!

Batting performance: It’s more than just runs

True strike rate: A player’s strike rate (number of runs scored per 100 balls faced) might suggest their intentions with the bat but neglects the risks they have taken. 

True Strike Rate addresses this by factoring in how often batsmen get dismissed–their frequency of getting out. Given that getting out ends a batter’s chance to score significantly reduces their ability to score fast.

Dot ball percentage: “Attack always wins matches” has been IPL’s watchword. Dot balls or deliveries where runs aren’t scored are against such an ethos. 

A higher dot ball % may hide issues such as trouble picking up certain bowlers’ deliveries by a batter or struggling for timing or slow deliveries.

Boundary percentage: Every run is not equal here. One who keeps finding the ropes much more consistently than another person who mostly singles accumulate becomes way more valuable. 

Boundary percentage shows this amount; i.e., how many fours and sixes form part of the total number of runs made by a particular Batman.

Expected runs (xR): This advanced metric builds on strike rate by considering delivery type faced and fielding positions set. For instance, hitting a full toss to the boundary has a greater ‘expected run’ value than flicking an outside edge through slips for four. xR helps to find out those batters who maximize their scoring chances better than other players.

Bowling beyond wickets and economy

False shot percentage: Sometimes the best bowlers aren’t necessarily the ones with the most wickets, but those that induce mistakes. False shot % calculates how often a bowler makes batsmen play risky, less controlled strokes. 

This helps analysts identify bowlers who put batters under constant pressure even if the wickets column doesn’t always reflect it.

Control rate: Instead of determining economy rate which shows efficiency in limiting runs, Control Rate is about how much control a bowler possesses over his or her deliveries – taking into account wides and no-balls only within the hands of the bowler alone. 

A low Control Rate may indicate that a bowler is good at containing runs but weak in maintaining line and length thus making it easy for his opponents to score.

Death bowling specialists: Who keeps their cool in those pressure-filled slog overs? A player’s economy rate and wickets taken in the last 5 overs reveal much about how they handle late-innings fire-power. Identifying death bowling experts is crucial in T20 format like T20 cricket.

Expected wickets (xW): Inspired by xR in batting, Expected Wickets provide a more accurate evaluation of bowling competency or skill. The analysis considers the kind of deliveries bowled which include (length, line, speed, and variation) and the batsman who is facing them and comes up with the likelihood of a wicket occurring. 

A bowler with a big difference between XW and actual wickets might be slightly unfortunate or might require further examination of his execution.

Fielding: The overlooked skill

In the Indian Premier League (Tata IPL), great fielding moments make all the difference between winning and losing matches. Traditionally though it has been the hardest part to quantify. But that is changing:

Fielding runs saved: Catches and run-outs are noticeable but modern tracking helps assess runs saved through excellent ground fielding or athletic stops short of boundary ropes. Fielding Runs Saved is an indicator of overall fielding performance.

Situational Analysis: Reading the match context

Besides individual attributes; advanced metrics allow us how different players perform under diverse match conditions thereby making us tactically one step ahead.

Required Run Rate (RRR) Analysis: How well batsmen handle RRR pressure is a crucial stat. Looking at strike rates and control percentages for batters and bowlers across various stages in RRR climbing (low, medium, high) tells us who thrives when stakes are high and who falters when it matters most.

Matchup Analysis: IPL happens to be about many matchups – pace vs spin, left-handers against right-handers, etc. Evaluating success rates for batter vs bowler can help teams plan better. It could also change everything if you notice that someone struggles against leg-spinning or that there’s a guy who always gets out certain types of batters.

Ground dimensions: Every IPL ground has unique characteristics; some suit batsmen while others favor bowlers. Analyzing player performance tailored to specific grounds paints a clearer picture. A power hitter might be unstoppable on a smaller ground but struggle in one with bigger boundaries.

The emergence of ‘impact’ metrics

Many new stats aim to provide a single number encapsulating a player’s overall value. While debatable, they provide interesting talking points:

Smart stats: Numerical ratings are created by certain sites using complex computer algorithms that take into account different factors such as situational importance and recency amongst others. These ‘smart scores’ are intended to give an overview of the impact with one glance.


Win Probability Added (WPA): Designed around principles borrowed from baseball, WPA tries to express how much of an increase or decrease in the likelihood of their team winning is brought about by a single action by a player like making a big score or taking multiple wickets at once. It is still developing within cricket but it aims to put some tangible measure on game-changers.


‘Replacement Player’ concept: Some metrics try to establish what the average value is for any IPL player, and then compare each individual against that benchmark. Being above this baseline gives you a positive ranking indicating that you are offering more than “replacement” quality cricket.

Data’s limitations and the human factor

Bear in mind that advanced metrics have limitations; they cannot tell everything about the game. Cricket has always been a sport where fine margins make all the difference.

Sample size matters: Advanced metrics can be skewed by very small sample sizes (say just two or three games worth of batsman’s performance). In order for them to be reliable, a long-term view is key.

‘Intangibles’ exist: Not every aspect of T20 success can be quantified – leadership qualities and the ability to perform under pressure or raise fellow teammates are just some examples missing from stats books.

Cricketing intuitions: In no way should advanced metrics replace the cricketing wisdom of scouts, coaches, and experienced analysts.


IPL Analysis – What the future beholds?

As data collection and analytics progress, so will our understanding of IPL performance. Here are some things you should watch for:

Wearable technology: Details on bowler release speeds, batter’s bat speed and fielding agility will be available through player tracking devices.

Machine learning: AI algorithms can improve their abilities to identify patterns, predict player potential, and give highly informed tactical suggestions that reflect real-time data if it is available.

A note for fans

The Tata IPL experience becomes even more exciting with advanced metrics.  Look at the numbers beyond the surface and ask yourself these questions: How does this batter handle the rising RRR? Which bowler has a knack for choking run chases in the death overs? It’s like watching a whole different game!

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