| Description | Findings |
| Quantifying the link between Test and First Class averages | CC D1 avg of 40 is worth 31 in Tests |
| Explaining the Underperformance of Overseas batsmen in County Cricket | English conditions mean SA / NZ / Aus batsmen find it easiest to slot into county cricket |
| Using CricViz False Shot % as an alternative to Averages | Proportion False shots times wickets per False Shot times Strike Rate equals average |
| Batting: 35 is the new 40 | 35 is a decent Test average. Most players averaging 35-40 should keep their place |
| England’s current Test batting, in the context of the last 20 years | Technique for putting a team in context – take sum of top seven players’ averages, adjusted for age |
| Kohli’s ODI run ranges are as expected for a phenomenal batsman | Ignore a player’s distribution of scores. Focus on their average. |
| Should Jennings’ expected average be reduced after the Bridgetown Test? | Take a big sample size over a smaller one. There’s good opening bowlers in county cricket, don’t rush to judge someone based on a few Tests. |
| England Lions – red ball selection analysis | “A” teams should pick players close to Test standard, not just exciting young guns |
| Modelling tail end batting | Expected value of the tenth wicket: Weaker batsman average + 20% of the difference between both batsmen’s averages. Link and Link |
| Home Advantage | Home advantage gets bigger as a series goes on Home advantage is worth 14% on average. Link and Link |
| University matches – statistical analysis | The gap between counties and universities is about 73%. Too significant for these matches to be useful practice. |
| ODI trends | Higher averages allow more risk taking which drives up strike rates |
| ODI boundary hitting | Six hitting is rare (<2% of balls) until after the 35th over |
| ODI dropped catch impact | Impact of dropped catch is biggest at the start of the innings |
| Matchups in ODIs | Opening with a spinner reduces the rest each bowler gets in the innings. Also features a nice visualisation of bowling spells. |
| Pool together associate nations to make a competitive team | Link |
| Analysis of England ODI players at Lord’s | The regional county cricket structure means northerners may have very little experience of southern grounds |
| Should Buttler bat up the order in ODIs? | Move Buttler up the order if second wicket falls after 30th over. Generally, be more fluid with batting orders |
| Comparing Jofra Archer and Ryan Higgins | Ryan Higgins is massively under-rated. It’s easy to miss players who chip in with 2-45 every time. |
| Could Woakes open the batting in Tests? | I concluded “maybe”. This is interesting, because it would now be easy to answer with my ball-by-ball database sourced from Cricsheet. |
| Lyon vs Moeen Ali by innings | Lyon amazing in the first innings, not great in the 4th. Ali the opposite. I missed the point that fourth innings spin gets more rewards in England that Australia. |
| Do hundreds matter? | No. |
| Sibley or Roy? | Openers on debut score three runs more per match than expected: feel free to throw players in if they’re good enough. |
| Mythbusting: Vaughan and Trescothick selected for England despite modest First Class Records | It’s a myth |
| England’s bowling options | Bowling options. England have gone on to pick most of these players – showing they are (mostly) using county data |
| Debutants in Away Tests have shorter careers | Start away from home, have a weaker average, have a shorter career (avg six Tests vs nine for home debutants) |
| Recovery time in One Day Cricket | Fewer than 2 rest days between 50 over games costs you 10 runs in the field |
| Northamptonshire’s Promotion Drivers | Nice template for reviewing why Northants had such a good season. |
| Duck analysis | Not sure what my point was. |
| On the decline of Test Batting being driven by T20 | Top order Test batting declined after white ball scoring speeds increased |
| Batting: All County Cricketers Rated | Dan Lawrence was 46th on the list, now in the Test team |
| County grounds ranked by ease of batting | FC averages should be adjusted for where someone’s home ground is. Surry easy. Canterbury hard. |
| Opening batsmen: the divergence of ODI and Test players | ODI averages now a poor predictor of Test averages |
| Boost to average from batting down the order | Boost to average from batting down the order |
| Getting your eye in across formats | Has a chart for the three formats |
| The case against Zak Crawley | I savage the selectors. Then wonder if they might have played a blinder when Crawley hit 267. I end up proposing to use judgement to rate players within their range of plausible averages (see error bars analysis below). Link And Link |
| Rating Wicket Keepers | Using byes per 100 overs, % of dismissals, batting average to judge keepers |
| Test batting: do some players gain an extra boost at home? | Unable to find extra home advantage for openers when playing at home. |
| Some flawed analysis of leg spin and off spin | I misunderstood some Cricinfo data showing what scores batsmen were on when dismissed (I thought it was their average). Link and Link |
| Best bowlers of the last 50 years | Methodology to appraise bowlers based on who they got it. This is a way of going beyond averages (which are a bit blunt). This approach calculates what the impact a bowler had on a batsman’s performance. |
| How many innings before an average is accurate? | Averages after 30 innings are surprisingly weak indicators of averages over the rest of a player’s career. Even 30 innings are too few to judge a T20 player’s career SR Volatility by year in average can be explained by low sample sizes. xW can smooth that out |
| How much recent data should you use when assessing a bowler? | Last four years looks like the best balance between sample size and stale data |
| Reasons to play in “A” tours | Four reasons to pick players: Stay sharp in off season, suited to those particular conditions, gain tour experience, or just people already in the country after white ball tours. |
| How to win a super over | Strategies for Super Over success, based on analysis of all Super Overs to date |
| Test cricket’s evolution and professionalism | I have a theory that as the talent pool increases there are fewer extreme performances. My analysis showed Test cricket improved markedly from 1930 to 1960 on this measure. |
| Adding error bars to averages | Formula: 1 Standard Deviation = Average x (Wickets ^ -0.5) |
| Batting ability in Test cricket is not normally distributed (it just looks like it is). | A poorly explained argument of something I think is true. |
| IPL analysis | T20 death overs scoring rates are driven by boundary %. But – a handful of batsmen can strike 150+ with low boundary percentages. Big hitters should refuse singles. |
| Do right-left pairings score faster in ODIs? | Right-Left combinations don’t impact strike rates |
| Test partnerships – does it matter who bats with whom? | No. |
| Pace bowlers struggle in back to back Tests | 7% increase in bowling average if playing in back to back Tests |
| Test bowling averages by month in England | Spinners average measurably less as the English summer goes on |
| Top innings bowler in Tests | One for the gamblers – trends in the top bowler market |
| Conferences: what we can learn from the 2020 Bob Willis Trophy | Putting 18 counties at the same level would leave too big a gap between FC and Test standard in England. |
| Rating the Blast teams … Lancashire’s batting is better than it looks | A strong bowling attack means small chases, which can trash batsmen’s stats by giving them lower Strike Rates than they would otherwise have. |
| The ODI “who is winning?” formula | Stole a formula from @cric_analytics and stuck it in my model as a check |
| The perils of batsmen switching counties | Moving counties late in career negatively impacts a batsman’s stats, possibly through loss of home advantage |
| T20 batting: running out of steam | Balls per wicket data can be used to work out in running how aggressive batsmen can be in T20 without having to resort to letting the tail bat |
| DRS: The story so far | Myths and truths from analysing a database of DRS data |
| Country vs Country matchups in Test Cricket | Home advantage for specific pairs of countries |
Red Ball Data 