The Minor League Cricket Player Impact rankings, developed independently by CricSims founder Tom Nielson, calibrate the contributions of each player by adjusting raw match metrics (runs, wickets, etc) with key factors that impact performance. Critically, utilizing ball-by-ball data, these rankings factor in the impact of the pitch surface (artificial or natural turf) on batting and bowling along with accounting for the value of each individual batter or bowler’s contribution in a match situation, allowing for a holistic analysis of performance. See below for a full explanation of the rankings.

View 2021 Player Impact Rankings

**Ground Impacts**

The most important consideration when assessing Minor League Cricket performance is knowing where players are performing: about half of all matches are played on artificial wickets, and the other half on more traditional natural turf wickets. Artificial wickets tend to be more batting friendly than turf wickets, which needs to be considered when comparing the performance of players at the grounds they have played at across the season. In addition, other ground-specific factors such as boundary distance or outfield speed/surface impact the difficulty of scoring runs or taking wickets.

In this analysis, a simple method is used to determine the impact of each ground on scoring: a comparison of actual performance at each ground to expected performance based on match situations that occurred at that ground. Using ball-by-ball data, we can calculate how many runs above or below average each ground plays on each ball. For example, batter friendly Param Veers Cricket Field in Atlanta scores at a whopping 0.29 runs per ball above average. At the opposite end, the turf wicket at BPL Stadium in the Chicago suburbs scores at -0.21 runs per ball below average. This 0.5 run per ball difference implies that the average innings at Param Veers Cricket Field is ~60 runs higher than an average innings at BPL Cricket Stadium.

**Bowler Impact Rankings**

Traditional cricket stats simply present runs and wickets side-by-side or in the form of an average. But that still leaves some questions unanswered: would you rather have a bowler averaging 20 at an economy of 6.00 or a bowler averaging 30 at an economy of 4.50? In the limited-overs game, the answer may not be immediately clear. Estimating the run value of a wicket can allow us to represent a bowler’s performance with one number.

*Estimating the Run Value of a Wicket*

To estimate the run value of a wicket, based on ball-by-ball data for all Minor League Cricket matches, we can determine the average number of runs remaining in an innings at the beginning of each over, dependent on number of wickets lost.

For example, a team who has lost no wickets at the start of the third over would expect to score another 123.3 runs on average. A team who has lost one wicket at the start of the third over would expect to score another 113.7 runs on average. So if you lose your first wicket in the second over, your expected runs for the match have dropped by -9.6 (as you are expected to score 113.7 more runs rather than 123.3). The value of that wicket for the bowling team was a -9.6-run drop in the opponent’s expected score.

Obviously, wickets taken early or when you’ve already taken a few are more valuable than getting a third wicket in the last few overs. All in all, the average wicket in Minor League Cricket is worth approximately **-4.7 runs**. Doing similar math for T20I or IPL matches would get you closer to -4 runs, indicating that wickets are slightly more valuable in Minor League Cricket than major T20 leagues.

*Adjusting for Match State of Bowler Appearances and Location of Match*

Bowler usage strategy has a huge impact on a bowlers’ figures. In the ninth over with a couple of wickets down, the probability of another wicket is something like 3-4%. But if you’re bowling in the last couple of overs, wicket probability shoots up to 9%, along with dramatic increases to run rate. It’s important to account for match state when analyzing a bowler’s figures, to properly give credit to bowlers bowling in more difficult situations (or take some credit away from bowlers that mop up the opponent’s tail).

Similarly, we need to account for the fact that some bowlers play more matches at batter or bowler friendly grounds. This is especially true for Minor League Cricket, where there’s more extreme variation due to the presence of both turf and artificial wickets. As noted above, a bowler with a lot of overs at Param Veers Cricket Field needs to be given some credit to account for the fact that their job is harder.

*Determining Bowler Value*

Now we can determine each bowler’s impact per over. Essentially, we start with the runs conceded by a bowler and subtract the number of wickets multiplied by the average run value of a wicket. This gives us “adjusted runs conceded”, which can be used to calculate an adjusted economy rate (adjusted runs conceded divided by overs bowled). We can then compare to their expected adjusted economy rate based on the match state and location of their overs bowled. This will finally give us a nice clean metric – runs allowed per over relative to the average bowler.

**Batter Impact Rankings**

The methodology here is similar to the bowling analysis, where we compare a batter’s actual runs and outs to the average batter’s runs and outs in the same match situations, in addition to accounting for the ground impacts discussed earlier. Wickets are still worth an average of -4.7 runs, same as in the bowling analysis. Also the same as in the bowling analysis, it is important to account for the match situations a batter appears in: a player that opens the batting is in a much different tactical environment than a player batting in the final overs. Batters don’t bat for a set number of balls or overs, so batting impact will be calculated on a per-match basis. A batter with a +5.0 batting impact per match is increasing their team’s final score by +5 runs compared to the average batter.

**Overall Player Impact Rankings**

Overall Impact Rankings combine both batting and bowling performance to give a single all-round performance metric for the season. To combine both batting and bowling, we’ll look at Impact as an aggregate measure, not controlling for the number of overs bowled or balls faced.

The batting statistics in the Impact Rankings show the number of innings and balls faced for the batter, as well as the season long impact of the batter (i.e., number of runs the batter is adding for his team on top of the average batter’s performance). On the bowling side, it’s innings bowled in, number of overs, and the season long impact of the bowler (i.e., number of runs the bowler is taking off opponent totals compared to the average bowler). Finally, the overall impact is calculated by batting impact minus bowling impact.